0:\r\n choices.append(key)\r\n await self.player.send_embed_to_user()\r\n await game_ref.update_all()\r\n action = await self.player.select_command(choices)\r\n my_turn, completed = await self.process_option(game_ref, action)\r\n if (completed):\r\n if action in self.current_actions:\r\n self.current_actions[action] = self.current_actions[action] - 1\r\n await game_ref.update_all()\r\n\r\n #await asyncio.sleep(0.1)\r\n await game_ref.send_announcement(\"Turn end.\")\r\n await self.check_effects('after', 'turn', {'this_piece':self}, game_ref)\r\n print(\"End OF TURN.\")\r\n return None\r\n # universal options.\r","def getAction(self, state):\n # Pick Action\n legalActions = self.getLegalActions(state)\n action = None\n \"*** YOUR CODE HERE ***\"\n # util.raiseNotDefined()\n if random.random() < self.epsilon:\n action = random.choice(legalActions)\n else:\n action = self.getPolicy(state)\n return action","def get_action(obs, player_x, player_y):\n # shot if player close to goal\n if player_x > 0.5:\n if player_y > 0:\n if Action.TopRight not in obs[\"sticky_actions\"]:\n return Action.TopRight\n else:\n if Action.BottomRight not in obs[\"sticky_actions\"]:\n return Action.BottomRight\n return Action.Shot\n # high pass if player far from goal\n else:\n if Action.Right not in obs[\"sticky_actions\"]:\n return Action.Right\n return Action.HighPass","def obtain_action(self, timestep):\r\n\t\t# Generates a random number for deciding between performing a random or\r\n\t\t# deterministic action.\r\n\t\trandom_num = random.random()\r\n\r\n\t\tif random_num < self.epsilon:\r\n\t\t\t# Random action taken.\r\n\t\t\treturn random.randint(0, self.num_actions-1)\r\n\r\n\t\telse:\r\n\t\t\t# Deterministic action taken, where a random action index is\r\n\t\t\t# selected among the action indexes with the maximum Q value\r\n\t\t\t# estimate.\r\n\t\t\treturn np.random.choice(np.argwhere(self.player_Q == self.player_Q.max()).flatten()).item()","def getAction(self, gameState):\n \"*** YOUR CODE HERE ***\"\n\n bestchoice = \"Stop\"\n value = float(\"-inf\")\n i = 0\n actlist = gameState.getLegalActions(0)\n while i < len(actlist):\n action = actlist[i]\n arg1 = self.minValue(gameState.generateSuccessor(0, action), 1, self.depth)\n maxVal = max(value, arg1)\n if value < maxVal:\n value = maxVal\n bestchoice = action\n i = i + 1\n return bestchoice","def get_action(obs, player_x, player_y):\n if Action.Sprint in obs[\"sticky_actions\"]:\n return Action.ReleaseSprint\n return Action.HighPass","def decision():\n return random.choice(['GoToNormal','GoToSleep'])","def get_action(self, state):\n return random.choice(state.get_legal_actions(self.index))","def chooseAction(self, gameState):\n actions = gameState.getLegalActions(self.index)\n\n # You can profile your evaluation time by uncommenting these lines\n # start = time.time()\n values = [self.evaluate(gameState, a) for a in actions]\n # print 'eval time for agent %d: %.4f' % (self.index, time.time() - start)\n\n maxValue = max(values)\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\n\n foodLeft = len(self.getFood(gameState).asList())\n\n return random.choice(bestActions)","def getAction(self, gameState):\n\t\t\"*** YOUR CODE HERE ***\"\n\t\treturn self.expectimax_value(gameState, 1, 0)\n\t\tutil.raiseNotDefined()","def get_user_input(self, game, hand, message, allowed_actions):\n return 'hit'","def get_user_input(self, game, hand, message, allowed_actions):\n if self.first_turn:\n hand = self.hands[0]\n if hand.cards == 2:\n card1, card2 = hand.cards\n if card1.get_value() == card2.get_value():\n return 'split'\n return 'double'\n else:\n return 'stand'","def getAction(self, gameState):\n \"*** YOUR CODE HERE ***\"\n return self.expectimax(gameState, 0, self.depth)[1]","def action(self, action_space, observation, info): # pylint: disable=no-self-use\n _ = observation # not using the observation for random decision\n _ = info\n\n this_player_action_space = {Action.FOLD, Action.CHECK, Action.CALL, Action.RAISE_POT, Action.RAISE_HALF_POT,\n Action.RAISE_2POT}\n _ = this_player_action_space.intersection(set(action_space))\n\n action = None\n return action","def play_against_random(self, action):\n state, status, done = self.step(action)\n if not done and self.turn == 2:\n state, s2, done = self.random_step()\n if done:\n if s2 == self.STATUS_WIN:\n status = self.STATUS_LOSE\n elif s2 == self.STATUS_TIE:\n status = self.STATUS_TIE\n else:\n raise ValueError(\"???\")\n return state, status, done","def get_action(obs, player_x, player_y):\n # if player is surrounded\n if obs[\"memory_patterns\"][\"go_around_opponent_surrounded\"]:\n return Action.HighPass\n if Action.Sprint not in obs[\"sticky_actions\"]:\n return Action.Sprint\n return obs[\"memory_patterns\"][\"go_around_opponent\"]","def get_action(self, state):\r\n if len (state.actions()) == 1:\r\n # dbstate = DebugState.from_state(state)\r\n # print (dbstate)\r\n self.queue.put(state.actions()[0])\r\n return\r\n if state.ply_count < 2:\r\n action = random.choice(state.actions())\r\n else:\r\n action = self.uct_search(state).action\r\n # dbstate = DebugState.from_state(state)\r\n # print (dbstate)\r\n if action is None:\r\n print(\"Incorrect action\")\r\n action = random.choice(state.actions())\r\n self.queue.put(action)","def getAction(self, game, state):\n if self.getUnknownCard(state) is None:\n baseVal = self.getBase(state)\n counts = self.getCounts(state)[baseVal]\n if counts[0] > counts[1]:\n return dnUtil.Action.Higher\n elif counts[0] < counts[1]:\n return dnUtil.Action.Lower\n else:\n if dnUtil.random.random() > 50:\n return dnUtil.Action.Higher\n else:\n return dnUtil.Action.Lower\n elif self.getLoseBool(state):\n return dnUtil.Action.Exit\n else:\n nextVal = self.getUnknownCard(state)\n nextCounts = self.getCounts(state)[nextVal]\n deckSize = sum(nextCounts)\n high, low, tie = nextCounts\n\n if high > low:\n winrate = high / deckSize\n elif high < low:\n winrate = low / deckSize\n else:\n winrate = 0.5\n\n risk = game.getRisk()\n if self.expectancyPcnt(winrate) > self.expectancyPcnt(risk / 100):\n return dnUtil.Action.Continue, winrate * 100\n else:\n return dnUtil.Action.Exit, winrate * 100","def get_action(obs, player_x, player_y):\n if Action.Sprint in obs[\"sticky_actions\"]:\n return Action.ReleaseSprint\n return Action.Shot","def getAction1(self, state):\n # Pick Action\n ############################################################################################################ Eric Changed state to self.index\n\n legalActions = state.getLegalActions(self.index)\n #print \"LEGAL ACTIONS IN GETACTION1 IN QLEARNINGAGENT: \", legalActions\n action = None\n \"*** YOUR CODE HERE ***\"\n if len(legalActions) == 0:\n return None\n coinTruth = util.flipCoin(self.epsilon)\n if coinTruth:\n acToReturn = random.choice(legalActions)\n #print \"GETACTION1 IN QLEARNINGAGENT COINTRUTH IS TRUE, ACTION IS : \", acToReturn\n return acToReturn\n\n\n\n #util.raiseNotDefined()\n acToReturn = self.computeActionFromQValues(state)\n #print \"GETACTION1 IN QLEARNINGAGENT COINTRUTH IS FALSE< ACTION IS : \", acToReturn\n return acToReturn","def getAction(self, state):\n # Pick Action\n legalActions = self.getLegalActions(state)\n action = None\n\n \"\"\"Description:\n Use util.flipCoin, if return true then randomly choice from legalAction\n if flase, then sue getPolicy to get best policy action\n \"\"\"\n \"\"\" YOUR CODE HERE \"\"\"\n if len(legalActions) == 0:\n return action # None\n \n if util.flipCoin(self.epsilon):\n ''' exploration function (not work well)''' \n# posPol = util.Counter()\n# for a in legalActions:\n# if self.getQValue(state,a) >= 0:\n# posPol[a] = -1*self.getQValue(state, a) + (1000/(self.vitCount[(state,a)]+0.0001))\n# #print \"posPol[\", a, \"]= \",posPol[a]\n# #posPol[a] = (self.getQValue(state, a) * self.epsilon** self.vitCount[(state,a)]) + ( self.epsilon/(self.vitCount[(state,a)]+0.1) )\n# if len(posPol) == 0:\n# action = random.choice(legalActions)\n# else:\n# action = posPol.argMax() # random.choice(posPol.keys())\n ''' Random exploration '''\n action = random.choice(legalActions)\n else:\n action = self.getPolicy(state)\n \n \"\"\" END CODE \"\"\"\n\n return action","def getAction(self, gameState):\n \"*** YOUR CODE HERE ***\"\n\n bestchoice = \"Stop\"\n value = float(\"-inf\") \n alpha = float(\"-inf\")\n beta = float(\"inf\")\n i = 0\n actlist = gameState.getLegalActions(0)\n while i < len(actlist):\n action = actlist[i]\n arg1 = self.minValue(gameState.generateSuccessor(0, action), 1, self.depth, alpha, beta)\n maxVal = max(value, arg1)\n if maxVal > beta:\n bestchoice = action\n break\n alpha = max(alpha, maxVal)\n if maxVal > value:\n value = maxVal\n bestchoice = action\n i = i + 1\n return bestchoice","def _select_action(self):\n if self.eval_mode:\n self._log_values()\n epsilon = self.epsilon_eval\n else:\n epsilon = self.epsilon_fn(\n self.epsilon_decay_period,\n self.training_steps,\n self.min_replay_history,\n self.epsilon_train)\n if random.random() <= epsilon:\n # Choose a random action with probability epsilon.\n return random.randint(0, self.num_actions - 1)\n else:\n # Choose the action with highest Q-value at the current state according\n # to the current head.\n return self._compute_q_argmax()","def sample_action(self, creature, combat_handler):\n enemy = self.determine_enemy(creature=creature, combat_handler=combat_handler)\n current_state = self.get_raw_state(\n creature=creature,\n enemy=enemy,\n combat_handler=combat_handler\n )\n num_attacks_used = current_state[0][NUM_ATTACKS_USED]\n if num_attacks_used < 1:\n action = creature.get_action(\"Arrow Shot\")\n else:\n action = creature.get_action(\"end_turn\")\n\n return action, None, None","def get_action(obs, player_x, player_y):\n if player_y > 0:\n if Action.Top not in obs[\"sticky_actions\"]:\n return Action.Top\n else:\n if Action.Bottom not in obs[\"sticky_actions\"]:\n return Action.Bottom\n if Action.Sprint in obs[\"sticky_actions\"]:\n return Action.ReleaseSprint\n return Action.ShortPass","def select_action(self, state):\n\t\treturn sample(range(0, self.action_space), 1)[0]","def chooseAction(self, gameState):\n actions = gameState.getLegalActions(self.index)\n\n # You can profile your evaluation time by uncommenting these lines\n # start = time.time()\n values = [self.evaluate(gameState, a) for a in actions]\n # print 'eval time for agent %d: %.4f' % (self.index, time.time() - start)\n\n maxValue = max(values)\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\n\n return random.choice(bestActions)","def get_random_action():\n # Define an array containing the available actions for the UAV\n # in the final work, takeoff and land must be added\n action_list = ['left', 'right', 'forward', 'backward', 'stop', 'descend']\n # Choose a random action within the array\n #action_index = STDrandom.randint(0, len(action_list) - 1)\n # forward,backward,left,right, stop and land\n probability_descend = 0.25\n probability = (1 - probability_descend)/ (len(action_list) -1)\n action_probability = [probability, probability, probability, probability, probability, probability_descend]\n action = np.random.choice(action_list, 1, p=action_probability)[0]\n #action_index = STDrandom.randint(0, 10)\n #action = action_list[action_index]\n\n return action","def get_action(obs, player_x, player_y):\n if Action.Right not in obs[\"sticky_actions\"]:\n return Action.Right\n return Action.ShortPass","def getAction(self, state):\n # Pick Action\n legalActions = self.getLegalActions(state)\n action = None\n \"*** YOUR CODE HERE ***\"\n length_legalActions = len(legalActions) #Find length of allowed actions\n\n if length_legalActions == 0: #To check if no legal action is possible, that is incase of terminal state\n action = None #set action as none and return from here\n return action\n\n epsilon = self.epsilon #to get the epsilon value\n\n if util.flipCoin(epsilon): #util.flipcoin returns binary variable with probability p of success by using util.flipCoin(p), which returns True with probability p and False with probability 1-p.\n action = random.choice(legalActions) #Choosing randomly from list of allowed actions\n return action\n\n action = self.getPolicy(state) #Without probability epsilon we should take best policy action. getPolicy function calls the computeActionFromQValues function which gives us the best action to take in a state\n\n #util.raiseNotDefined()\n\n return action","def getAction(self):\n # Module player is always assumed player #0\n state = [0] * (4+self.game.numPlayers*2)\n state[0] = (0,1)[self.game.roles[0] == \"Werewolf\"]\n state[1] = (0,1)[self.game.roles[0] == \"Villager\"]\n state[2] = (0,1)[self.game.turnnum == 0]\n state[3] = (0,1)[self.game.turnnum == 1]\n for i in range(len(self.game.claim)):\n state[4+i*2+0] = (0,1)[self.game.claim[i] == \"Werewolf\"]\n state[4+i*2+1] = (0,1)[self.game.claim[i] == \"Villager\"]\n #state[4+i*2+0] = (0,1)[self.game.roles[0] == \"Werewolf\"]\n #state[4+i*2+1] = (0,1)[self.game.roles[0] == \"Villager\"]\n self.module.reset()\n output = self.module.activate(state)\n result = None\n if (self.game.turnnum == 0):\n if output[0] > output[1]: result = \"Werewolf\"\n else : result = \"Villager\"\n else:\n votes = output[2:]\n result = drawGibbs(votes, self.temperature) + 1\n #print (\"votes, result\", votes, result)\n #print ()\n #print (\"input\", state)\n #print (self.game.stateStr())\n #print (\"output\", output, result)\n #print ()\n return [self.pnum, result]","def choose_action(self, board, possible_actions):\r\n self._print_board(board)\r\n while True:\r\n user_choice = int(input(\"Which Field?\"))\r\n if user_choice in possible_actions:\r\n return user_choice\r\n else:\r\n print('Action not possible!')","def chooseAction(self, gameState):\n probabilities = self.assignProbablities(gameState)\n #print probabilities\n prob, bestProbabilityAction = max(probabilities)\n return bestProbabilityAction","def get_action_from_user(self) -> ActionType:\n if self.wait_for_explicit_human_action:\n while len(self.renderer.pressed_keys) == 0:\n self.renderer.get_events()\n\n if self.key_to_action == {}:\n # the keys are the numbers on the keyboard corresponding to the action index\n if len(self.renderer.pressed_keys) > 0:\n action_idx = self.renderer.pressed_keys[0] - ord(\"1\")\n if 0 <= action_idx < self.action_space.shape[0]:\n return action_idx\n else:\n # the keys are mapped through the environment to more intuitive keyboard keys\n # key = tuple(self.renderer.pressed_keys)\n # for key in self.renderer.pressed_keys:\n for env_keys in self.key_to_action.keys():\n if set(env_keys) == set(self.renderer.pressed_keys):\n return self.action_space.actions[self.key_to_action[env_keys]]\n\n # return the default action 0 so that the environment will continue running\n return self.action_space.default_action","def getAction(self, gameState):\n \"*** YOUR CODE HERE ***\"\n return self.expectimax(gameState,self.depth * 2,0,True)[1]\n util.raiseNotDefined()","def action_menu(player):\n\n\tclear_screen()\n\n\trun_game_log(player, game_log)\t# runs the run_game_log function which gets output from game_log class\n\n\tprint('1. Move')\n\tprint('2. Show Map')\n\tprint('3. Show Player Inventory')\n\tprint('4. Show Player Stats')\n\tprint('5. Exit to Main Menu')\n\n\tpossible_choices = ['1','2','3','4','5']\n\tactive = True\n\n\twhile active:\n\t\tselection = input('\\nNow I shall... ')\n\t\tif selection in possible_choices:\n\t\t\tactive = False\n\t\t\treturn int(selection)\t# return always exits a function, right? so active = False is redundant?\n\t\telse:\n\t\t\tprint('That\\'s not one of the menu options!')","def chooseAction(self, gameState):\n\n actions = gameState.getLegalActions(self.index)\n obs = gameState.getAgentDistances()\n for o in self.opponents:\n self.observe(o, obs[o], gameState)\n self.displayDistributionsOverPositions(self.distributions)\n\n # You can profile your evaluation time by uncommenting these lines\n start = time.time()\n values = [self.evaluate(gameState, a) for a in actions]\n print 'eval time for agent %d: %.4f' % (self.index, time.time() - start)\n\n maxValue = max(values)\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\n\n #self.elapseTime(gameState)\n\n return random.choice(bestActions)","def getAction(self, gameState):\n \"*** YOUR CODE HERE ***\"\n #the return value of \"result\" function is (action, score) pair\n a = self.result(gameState,0)[0]\n return a\n util.raiseNotDefined()","def getAction(self, gameState):\n \"*** YOUR CODE HERE ***\"\n return self.minimax(gameState, 0, self.depth)[1]","def select_action(self, state: str) -> Action:\n rnd_num = self._random.random()\n p = 1.0 - self.epsilon\n if rnd_num > p:\n action = self._random.random_choice() \n else:\n action = max(self.Qs[state], key=lambda x: self.Qs[state][x])\n if self.epsilon_decay == True:\n self.turns += 1\n if self.turns < self.end_epsilon_decay:\n self.epsilon -= self.decay_value \n return action","def getAction(self, gameState):\n\t\t\"*** YOUR CODE HERE ***\"\n\t\treturn self.minimax_value(gameState, 1, 0)\n\t\tutil.raiseNotDefined()","def get_action(obs, player_x, player_y):\n return Action.Left","def perform_action(self, action):\n \n assert self.is_valid_action(action)\n \n # Save the action.\n self.action = action\n \n #the slight strategy of the opponent\n if self.reward==rLose :\n observation = self.observation\n else:\n observation = random.choice([oRock,oPaper,oScissor])\n \n #determine the result of the game and get the reward\n if action == aRock:\n if observation == oRock:\n reward= rDraw\n elif observation == oPaper:\n reward= rLose\n elif observation == oScissor:\n reward= rWin\n elif action == aPaper:\n if observation == oRock:\n reward= rWin\n elif observation == oPaper:\n reward= rDraw\n elif observation == oScissor:\n reward= rLose\n elif action == aScissor:\n if observation == oRock:\n reward= rLose\n elif observation == oPaper:\n reward= rWin\n elif observation == oScissor:\n reward= rDraw\n \n \n #Store the observation and reward in the environment.\n self.observation = observation\n \n self.reward = reward\n \n \n return (observation, reward)\n # end def","def get_action(obs, player_x, player_y):\n return Action.HighPass","def getAction(self, state):\n # Pick Action\n legalActions = self.getLegalActions(state)\n if len(legalActions) == 0:\n return None\n elif util.flipCoin(self.epsilon):\n return random.choice(legalActions)\n else:\n return self.getPolicy(state)","def chooseAction(self, gameState):\r\n actions = gameState.getLegalActions(self.index)\r\n\r\n # You can profile your evaluation time by uncommenting these lines\r\n # start = time.time()\r\n values = [self.evaluate(gameState, a) for a in actions]\r\n # print 'eval time for agent %d: %.4f' % (self.index, time.time() - start)\r\n\r\n maxValue = max(values)\r\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\r\n\r\n foodLeft = len(self.getFood(gameState).asList())\r\n\r\n if foodLeft <= 2:\r\n bestDist = 9999\r\n for action in actions:\r\n successor = self.essor(gameState, action)\r\n pos2 = successor.getAgentPosition(self.index)\r\n dist = self.getMazeDistance(self.start,pos2)\r\n if dist < bestDist:\r\n bestAction = action\r\n bestDist = dist\r\n return bestAction\r\n\r\n return random.choice(bestActions)","def getAction(self, gameState):\n \"*** YOUR CODE HERE ***\"\n a = self.result(gameState,0)[0]\n return a\n util.raiseNotDefined()","def getAction(self, gameState):\n \"*** YOUR CODE HERE ***\"\n a = self.result(gameState,0)[0]\n return a\n util.raiseNotDefined()","def get_attack(self, pykemon):\n #Show the moves list using pykemon specific move names\n print(\"\\nWhat would you like to do...\")\n print(\"(1) - \" + pykemon.moves[0])\n print(\"(2) - \" + pykemon.moves[1])\n print(\"(3) - \" + pykemon.moves[2])\n print(\"(4) - \" + pykemon.moves[3])\n choice = int(input(\"Please enter your move choice: \"))\n\n #Formatting\n print()\n print(\"-----------------------------------------------------------------------------\")\n\n return choice","def chooseAction(self, gameState):\n\n actions = gameState.getLegalActions(self.index)\n\n values = [self.evaluate(gameState, a) for a in actions]\n\n maxValue = max(values)\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\n\n return random.choice(bestActions)","def chooseAction(self, gameState):\n\n ####print \"chooseAction Called\"\n\n #self.lastEatenFood = None\n\n\n actions = gameState.getLegalActions(self.index)\n\n ##print \"\\nNEW ACTION\\n--------\"\n\n # You can profile your evaluation time by uncommenting these lines\n # start = time.time()\n values = [self.evaluate(gameState, a) for a in actions]\n # ###print 'eval time for agent %d: %.4f' % (self.index, time.time() - start)\n\n maxValue = max(values)\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\n\n \n\n return random.choice(bestActions)","def chooseAction(self, gameState):\n myState = gameState.getAgentState(self.index)\n myPos = myState.getPosition()\n ghosts = self.getGhosts(gameState)\n\n if self.lastState:\n myLastState = self.lastState.getAgentState(self.index)\n \n ghosts = self.getGhosts(gameState)\n if len(ghosts) > 0:\n minDistToGhost = min([self.getMazeDistance(myPos, a.getPosition()) for a in ghosts])\n if not myState.isPacman and myLastState.isPacman and minDistToGhost <= 3 and self.specificPath == []:\n path, target = self.getAlternativePath(gameState, minPathLength=5)\n self.specificPath = path\n self.targetPos = target\n \n if len(self.specificPath) > 0:\n return self.specificPath.pop(0)\n elif self.isStucking(gameState):\n actions, target = self.getAlternativePath(gameState, minPathLength=5)\n if len(actions) > 0:\n self.specificPath = actions\n self.targetPos = target\n return self.specificPath.pop(0)\n else:\n actions = gameState.getLegalActions(self.index)\n return random.choice(actions)\n\n actions = gameState.getLegalActions(self.index)\n actions.remove('Stop')\n\n if len(ghosts) > 0:\n distToGhost = min([self.getMazeDistance(myPos, a.getPosition()) for a in ghosts])\n if not self.isOppoentsScared(gameState) and myState.isPacman and distToGhost <= 6:\n safeActions = self.getSafeActions(gameState)\n if len(safeActions) > 0:\n actions = safeActions\n\n values = [self.getQValue(gameState, a) for a in actions]\n maxValue = max(values)\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\n bestAction = random.choice(bestActions)\n \n self.doAction(gameState, bestAction)\n\n return bestAction","def random_play(state, player):\n import random\n actions = YoteRules.get_player_actions(state, player, reward_move=state.rewarding_move)\n choice = random.choice(actions)\n return choice","def choose_action(self, board, possible_actions):\r\n pass","def action(self):\n obs = self.observation\n\n action = None\n try:\n if SETTINGS_DEAD_CANT_THINK and obs.respawn_in > -1:\n self.debugMsg(\"Sleeping\")\n return (0,0,False)\n\n # Check if agent reached goal.\n if self.goal and point_dist(self.goal, obs.loc) < self.settings.tilesize:\n self.goal = None\n\n # If agent already has a goal\n # check if the motivation is still accurate\n if self.goal:\n self.validateMotivation()\n\n # Drive to where the user clicked\n if self.selected and self.observation.clicked:\n self.motivation = MOTIVATION_USER_CLICK\n self.goal = obs.clicked\n\n if self.goal is None:\n if self.strategy == STRATEGY_DEFENCE:\n action = self.action_defend()\n elif self.strategy == STRATEGY_OFFENCE:\n action = self.action_offence()\n else:\n action = self.action_normal()\n else:\n self.debugMsg(\"Goal already found: (%d,%d)\" % self.goal)\n except Exception:\n self.goal = None\n# self.debugMsg(\"Goal: %s, exception: %s\" % (self.goal, exp), True)\n \n if self.goal is None:\n self.goal = obs.loc\n\n self.updateTrendingSpot()\n if action is None:\n if self.goal == obs.loc:\n return (0,0,False)\n else:\n return self.getActionTriple()\n else:\n return action","def get_action(obs, player_x, player_y):\n if (random.random() < 0.5 and\n Action.TopRight not in obs[\"sticky_actions\"] and\n Action.BottomRight not in obs[\"sticky_actions\"]):\n return Action.TopRight\n else:\n if Action.BottomRight not in obs[\"sticky_actions\"]:\n return Action.BottomRight\n return Action.ShortPass","def choose_action(self, agent_data):\r\n action_value_estimates = agent_data[\"action_value_estimates\"]\r\n roll = random.uniform(0,1)\r\n if roll <= self.epsilon:\r\n action = random.choice( list( range(0,len(action_value_estimates))))\r\n else:\r\n action = self.argmax_with_random_tiebreaker(action_value_estimates)\r\n return action","def chooseAction(self, gameState):\n actions = gameState.getLegalActions(self.index)\n\n # You can profile your evaluation time by uncommenting these lines\n # start = time.time()\n values = [self.evaluate(gameState, a) for a in actions]\n # print 'eval time for agent %d: %.4f' % (self.index, time.time() - start)\n\n maxValue = max(values)\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\n\n foodLeft = len(self.getFood(gameState).asList())\n\n if foodLeft <= 2:\n bestDist = 9999\n for action in actions:\n successor = self.getSuccessor(gameState, action)\n pos2 = successor.getAgentPosition(self.index)\n dist = self.getMazeDistance(self.start, pos2)\n if dist < bestDist:\n bestAction = action\n bestDist = dist\n return bestAction\n\n return random.choice(bestActions)","def get_random_action(self) -> ActionType:\n return self.action_space.sample()","def chooseAction(self,state):\r\n #generate float btwn 0-1\r\n choice = random.random()\r\n \r\n #choose according to that number\r\n if choice > self.epsilon:\r\n return(self.maxQ(state)[1])\r\n else:\r\n #choose randomly\r\n return(self.actions[random.randrange(0,len(self.actions))])","def chooseAction(self,state):\r\n #generate float btwn 0-1\r\n choice = random.random()\r\n \r\n #choose according to that number\r\n if choice > self.epsilon:\r\n return(self.maxQ(state)[1])\r\n else:\r\n #choose randomly\r\n return(self.actions[random.randrange(0,len(self.actions))])","def chooseAction(self, gameState):\n\n actions = gameState.getLegalActions(self.index)\n # actions.remove(Directions.STOP)\n # You can profile your evaluation time by uncommenting these lines\n # start = time.time()\n values = [self.evaluate(gameState, a) for a in actions]\n # print 'eval time for agent %d: %.4f' % (self.index, time.time() - start)\n maxValue = max(values)\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\n\n foodLeft = len(self.getFood(gameState).asList())\n if foodLeft <= 2:\n bestDist = 9999\n for action in actions:\n successor = self.getSuccessor(gameState, action)\n pos2 = successor.getAgentPosition(self.index)\n dist = self.getMazeDistance(self.start,pos2)\n if dist < bestDist:\n bestAction = action\n bestDist = dist\n return bestAction\n\n return random.choice(bestActions)","def best_action(self, state):\n return random.choice(self.possible_actions)","def getAction(self, gameState):\n \"*** YOUR CODE HERE ***\"\n best_result = self.getexpectimax(gameState, 0, 0, gameState.getNumAgents())\n return best_result[0] # return the result","def action(self, gstate, actions):\n self.log.debug(\"Picking among actions %s\" % actions)\n return actions[0]","def choose_action(self, board):\n options = board.empty_cells\n # to allow exploration, have a small probability of a random move\n p_random = random.random()\n # if the state is not in the table add it\n if (self.sign, board.state) not in self.Q_table.keys() or p_random < self.epsilon:\n values = {}\n for option in options:\n values[option] = random.random()\n self.Q_table[(self.sign, board.state)] = values\n self.action = random.choice(options)\n else:\n values = self.Q_table[(self.sign, board.state)]\n action = max(values, key=values.get)\n self.action = action\n\n # decrease exploration after each action\n if self.epsilon > 0:\n self.epsilon -= 0.0001\n\n return self.action","def user_action():\n\t### This is the function that takes and executes the users choices\n\twhile battle_on:\n\t\tchoosing = True\n\t\twhile choosing:\n\t\t\tmenu(\"general\")\n\t\t\tanswer()\n\t\t\tif ans == \"attack\":\n\t\t\t\tattack(my_pokemon, enemy)\n\t\t\t\tcalc_hp(enemy, \"attack\")\n\t\t\t\tshow_hp(enemy)\n\t\t\t\tprint \" \"\n\t\t\t\treturn\n\t\t\telif ans == \"flee\":\n\t\t\t\tchance = uniform(0, 100)\n\t\t\t\tif chance > 90:\n\t\t\t\t\twin(\"flee\")\n\t\t\t\telse:\n\t\t\t\t\tprint \"You failed to escape!\"\n\t\t\t\t\treturn\n\t\t\telif ans == \"potion\":\n\t\t\t\tuse_potion(my_pokemon)\n\t\t\t\treturn\n\t\t\telse:\n\t\t\t\tprint \"i dont know what you mean :)\"\n\t\t\t\tprint \"lets try again!\"\n\t\t\t\tchoosing = True","def getAction(self, gameState):\n return self.expectimax(gameState, self.depth, 0)","def get_action(obs, player_x, player_y):\n if player_y <= -0.03 or (player_y > 0 and player_y < 0.03):\n if Action.BottomRight not in obs[\"sticky_actions\"]:\n return Action.BottomRight\n else:\n if Action.TopRight not in obs[\"sticky_actions\"]:\n return Action.TopRight\n if Action.Sprint in obs[\"sticky_actions\"]:\n return Action.ReleaseSprint\n return Action.Shot","def get_action():\n print(\"What do you do next?\")\n print(\" m) move\")\n print(\" a) fire an arrow\")\n action = input(\"> \")\n if action == \"m\" or action == \"a\":\n return action\n else:\n print(action + \"?\")\n print(\"That's not an action that I know about\")\n return False","def obtain_action(self, timestep):\r\n\t\treturn random.randint(0, self.num_actions-1)"],"string":"[\n \"def get_action(player):\\n print_action(player)\\n chosen_action_index = int(input('Please indicate your selection from the following list by inputting the number: '))\\n return player.available_actions[chosen_action_index]\",\n \"def get_player_action(self) -> None:\\n print(f\\\"\\\\nYou have: {self.user.hand.cards} totalling to {self.user.hand.value}\\\")\\n while not self.get_game_ending_hands():\\n action = self.validate_input(\\\"Do you want to 1. hit or 2. stand?\\\", ('1', '2'))\\n if action == '1':\\n self.action_hit()\\n elif action == '2':\\n self.action_stand()\\n break\",\n \"def request_action(self):\\n\\n # Determine the computer player's desired action\\n action = \\\"r\\\" if self._current_score < min(25, (100 - (self._total_score + self._current_score))) else \\\"h\\\"\\n # Return the action\\n return action\",\n \"def chooseAction(self, gameState):\\n\\n return \\\"Stop\\\"\\n\\n actions = gameState.getLegalActions(self.index)\\n\\n return random.choice(actions)\",\n \"def get_user_input(self, game, hand, message, allowed_actions):\\n if random.random() < 0.5:\\n return 'hit'\\n else:\\n return 'stand'\",\n \"def chooseAction(self, gameState):\\n\\n actions = gameState.getLegalActions(self.index)\\n\\n action_choose = uct_for_pacman(gameState, self)\\n if action_choose not in actions:\\n return random.choice(actions)\\n print(\\\"此步来自UCT\\\")\\n self.action_last = action_choose\\n return action_choose\",\n \"def chooseAction(self, gameState):\\n actions = gameState.getLegalActions(self.index)\\n\\n '''\\n You should change this in your own agent.\\n '''\\n\\n return random.choice(actions)\",\n \"def chooseAction(self, gameState):\\n actions = gameState.getLegalActions(self.index)\\n\\n '''\\n You should change this in your own agent.\\n '''\\n\\n return random.choice(actions)\",\n \"def chooseAction(self, gameState):\\n actions = gameState.getLegalActions(self.index)\\n\\n ''' \\n You should change this in your own agent.\\n '''\\n\\n return random.choice(actions)\",\n \"def select_user_action():\\r\\n number_of_actions = len(available_actions)\\r\\n hint = \\\"Enter the number of your choice (1..%i):\\\" % number_of_actions\\r\\n choice = input(hint)\\r\\n # Try to convert the input to an integer\\r\\n try:\\r\\n choice_int = int(choice)\\r\\n except ValueError:\\r\\n choice_int = -1\\r\\n if 1 <= choice_int <= number_of_actions:\\r\\n action = choice_int - 1\\r\\n else:\\r\\n action = None\\r\\n return action\",\n \"def get_human_action(self):\\n choice = input(\\n \\\"Ingrese la acción a realizar por el jugador {}: \\\".format(self.get_current_player())\\n )\\n while choice not in [str(action) for action in self.get_legal_actions()]:\\n choice = input(\\\"Acción no válida. Ingrese otra opción: \\\")\\n return int(choice)\",\n \"def choose_action(self):\\n\\n # Set the agent state and default action\\n action=None\\n if len(self.action_sequence) >=1:\\n action = self.action_sequence[0] \\n if len(self.action_sequence) >=2:\\n self.action_sequence=self.action_sequence[1:]\\n else:\\n self.action_sequence=[]\\n return action\",\n \"def request_action(self):\\n\\n # Return the player's input\\n return input(\\\"Enter 'r' to roll the die, or 'h' to hold. What you you like to do? \\\")\",\n \"def get_action(self, state):\\n time.sleep(2.0)\\n return random.choice(state.get_legal_actions(self.index))\",\n \"def choose_random_action(self):\\r\\n return Action.HIT if random.random() <= 0.5 else Action.STICK\",\n \"def choose_action(self):\\r\\n pass\",\n \"def choose_action(self):\\n\\n def is_random_exploration():\\n\\n # 5. Return whether do random choice\\n # hint: generate a random number, and compare\\n # it with epsilon\\n if random.random() < self.epsilon:\\n return True\\n else:\\n return False\\n\\n final_action = ''\\n if self.learning:\\n if is_random_exploration():\\n # 6. Return random choose aciton\\n final_action = self.valid_actions[random.randint(0, 3)]\\n else:\\n # 7. Return action with highest q value\\n final_action = max(\\n self.Qtable[self.state].items(),\\n key=operator.itemgetter(1))[0]\\n elif self.testing:\\n # 7. choose action with highest q value\\n final_action = max(\\n self.Qtable[self.state].items(),\\n key=operator.itemgetter(1))[0]\\n else:\\n # 6. Return random choose aciton\\n final_action = self.valid_actions[random.randint(0, 3)]\\n\\n return final_action\",\n \"def _select_action(self):\\n if self.eval_mode:\\n epsilon = self.epsilon_eval\\n else:\\n epsilon = self.epsilon_fn(\\n self.epsilon_decay_period,\\n self.training_steps,\\n self.min_replay_history,\\n self.epsilon_train)\\n if random.random() <= epsilon:\\n # Choose a random action with probability epsilon.\\n return random.randint(0, self.num_actions - 1)\\n else:\\n # Choose the action with highest Q-value at the current state.\\n if self._interact == 'stochastic':\\n selected_action = self._stochastic_action\\n elif self._interact == 'greedy':\\n selected_action = self._q_argmax\\n else:\\n raise ValueError('Undefined interaction')\\n return self._sess.run(selected_action,\\n {self.state_ph: self.state})\",\n \"def getAction(self, state):\\n # Pick Action\\n \\\"*** YOUR CODE HERE ***\\\"\\n # Epsilon greedy\\n if util.flipCoin(self.epsilon) is True:\\n self.lastAction = random.choice(self.legalActions)\\n else:\\n self.lastAction = self.computeActionFromQValues(state)\\n return self.lastAction\",\n \"def getAction(self, state):\\n # Pick Action\\n \\\"*** YOUR CODE HERE ***\\\"\\n # Epsilon greedy\\n if util.flipCoin(self.epsilon) is True:\\n self.lastAction = random.choice(self.legalActions)\\n else:\\n self.lastAction = self.computeActionFromQValues(state)\\n return self.lastAction\",\n \"def get_result_action(self):\\n motor_re, halt = self.arbitrator.choose_action(self.active_behaviors)\\n return motor_re, halt\",\n \"def chooseAction(self, gameState):\\n actions = gameState.getLegalActions(self.index)\\n actions.remove('Stop')\\n\\n myState = gameState.getAgentState(self.index)\\n myPos = myState.getPosition()\\n invaders = self.getInvaders(gameState)\\n if myState.scaredTimer > 0 and len(invaders) > 0:\\n distToGhost = min([self.getMazeDistance(myPos, a.getPosition()) for a in invaders])\\n if not myState.isPacman:\\n safeActions = self.getSafeActions(gameState, self.defenceBorder)\\n if len(safeActions) > 0:\\n actions = safeActions\\n\\n values = [self.getQValue(gameState, a) for a in actions]\\n maxValue = max(values)\\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\\n bestAction = random.choice(bestActions)\\n \\n self.doAction(gameState, bestAction)\\n\\n return bestAction\",\n \"def get_action(obs, player_x, player_y):\\n if Action.Sprint in obs[\\\"sticky_actions\\\"]:\\n return Action.ReleaseSprint\\n return Action.ShortPass\",\n \"def get_action(obs, player_x, player_y):\\n if Action.Right not in obs[\\\"sticky_actions\\\"]:\\n return Action.Right\\n if Action.Sprint in obs[\\\"sticky_actions\\\"]:\\n return Action.ReleaseSprint\\n return Action.HighPass\",\n \"def getAction(self, gameState):\",\n \"def _choose_action(self):\\n return random.randint(0,self.num_bandits-1)\",\n \"def get_next_action(self):\\n chosen_action = None\\n while chosen_action is None:\\n choice = input('Action: ')\\n chosen_action = KEY_MAP.get(choice)\\n\\n return chosen_action\",\n \"def choose_action(self, game_state):\\n util.raise_not_defined()\",\n \"def obtain_action(self, timestep):\\r\\n\\t\\t# Finds all actions which have not been selected before.\\r\\n\\t\\tzero_action = np.argwhere(self.player_selected_actions == 0).flatten()\\r\\n\\r\\n\\t\\t# Checks if there are any actions which have not been selected before.\\r\\n\\t\\tif zero_action.size:\\r\\n\\t\\t\\t# Returns a random action index that has not been selected before.\\r\\n\\t\\t\\treturn np.random.choice(zero_action).item()\\r\\n\\r\\n\\t\\telse:\\r\\n\\t\\t\\t# Calculates the sum of the Q value estimate and the upper\\r\\n\\t\\t\\t# confidence bound term\\r\\n\\t\\t\\tvalue_list = self.player_Q + self.confidence_level * (np.log(timestep+1) / self.player_selected_actions) ** 0.5\\r\\n\\r\\n\\t\\t\\t# Returns a random action index selected among the action indexes\\r\\n\\t\\t\\t# with the maximum sum.\\r\\n\\t\\t\\treturn np.random.choice(np.argwhere(value_list == value_list.max()).flatten()).item()\",\n \"async def get_action(self, game_ref): # Add other args accordingly.\\r\\n if(self.type==\\\"Leader\\\"):\\r\\n self.player.gain_summon_points()\\r\\n\\r\\n if(self.type==\\\"Creature\\\"):\\r\\n await self.do_auto_skills(game_ref)\\r\\n self.player.gain_fp()\\r\\n self.current_actions = self.generate_commands(game= game_ref)\\r\\n #self.current_actions=await self.check_effects('before', 'command_setting', self.current_actions, None) #Check effects on self.\\r\\n my_turn = True\\r\\n await game_ref.send_announcement(\\\"{}'s turn\\\".format(self.get_name()))\\r\\n await self.check_effects('before', 'turn', {'this_piece':self}, game_ref)\\r\\n while my_turn:\\r\\n choices = []\\r\\n for key, item in self.current_actions.items():\\r\\n print(key)\\r\\n if item > 0:\\r\\n choices.append(key)\\r\\n await self.player.send_embed_to_user()\\r\\n await game_ref.update_all()\\r\\n action = await self.player.select_command(choices)\\r\\n my_turn, completed = await self.process_option(game_ref, action)\\r\\n if (completed):\\r\\n if action in self.current_actions:\\r\\n self.current_actions[action] = self.current_actions[action] - 1\\r\\n await game_ref.update_all()\\r\\n\\r\\n #await asyncio.sleep(0.1)\\r\\n await game_ref.send_announcement(\\\"Turn end.\\\")\\r\\n await self.check_effects('after', 'turn', {'this_piece':self}, game_ref)\\r\\n print(\\\"End OF TURN.\\\")\\r\\n return None\\r\\n # universal options.\\r\",\n \"def getAction(self, state):\\n # Pick Action\\n legalActions = self.getLegalActions(state)\\n action = None\\n \\\"*** YOUR CODE HERE ***\\\"\\n # util.raiseNotDefined()\\n if random.random() < self.epsilon:\\n action = random.choice(legalActions)\\n else:\\n action = self.getPolicy(state)\\n return action\",\n \"def get_action(obs, player_x, player_y):\\n # shot if player close to goal\\n if player_x > 0.5:\\n if player_y > 0:\\n if Action.TopRight not in obs[\\\"sticky_actions\\\"]:\\n return Action.TopRight\\n else:\\n if Action.BottomRight not in obs[\\\"sticky_actions\\\"]:\\n return Action.BottomRight\\n return Action.Shot\\n # high pass if player far from goal\\n else:\\n if Action.Right not in obs[\\\"sticky_actions\\\"]:\\n return Action.Right\\n return Action.HighPass\",\n \"def obtain_action(self, timestep):\\r\\n\\t\\t# Generates a random number for deciding between performing a random or\\r\\n\\t\\t# deterministic action.\\r\\n\\t\\trandom_num = random.random()\\r\\n\\r\\n\\t\\tif random_num < self.epsilon:\\r\\n\\t\\t\\t# Random action taken.\\r\\n\\t\\t\\treturn random.randint(0, self.num_actions-1)\\r\\n\\r\\n\\t\\telse:\\r\\n\\t\\t\\t# Deterministic action taken, where a random action index is\\r\\n\\t\\t\\t# selected among the action indexes with the maximum Q value\\r\\n\\t\\t\\t# estimate.\\r\\n\\t\\t\\treturn np.random.choice(np.argwhere(self.player_Q == self.player_Q.max()).flatten()).item()\",\n \"def getAction(self, gameState):\\n \\\"*** YOUR CODE HERE ***\\\"\\n\\n bestchoice = \\\"Stop\\\"\\n value = float(\\\"-inf\\\")\\n i = 0\\n actlist = gameState.getLegalActions(0)\\n while i < len(actlist):\\n action = actlist[i]\\n arg1 = self.minValue(gameState.generateSuccessor(0, action), 1, self.depth)\\n maxVal = max(value, arg1)\\n if value < maxVal:\\n value = maxVal\\n bestchoice = action\\n i = i + 1\\n return bestchoice\",\n \"def get_action(obs, player_x, player_y):\\n if Action.Sprint in obs[\\\"sticky_actions\\\"]:\\n return Action.ReleaseSprint\\n return Action.HighPass\",\n \"def decision():\\n return random.choice(['GoToNormal','GoToSleep'])\",\n \"def get_action(self, state):\\n return random.choice(state.get_legal_actions(self.index))\",\n \"def chooseAction(self, gameState):\\n actions = gameState.getLegalActions(self.index)\\n\\n # You can profile your evaluation time by uncommenting these lines\\n # start = time.time()\\n values = [self.evaluate(gameState, a) for a in actions]\\n # print 'eval time for agent %d: %.4f' % (self.index, time.time() - start)\\n\\n maxValue = max(values)\\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\\n\\n foodLeft = len(self.getFood(gameState).asList())\\n\\n return random.choice(bestActions)\",\n \"def getAction(self, gameState):\\n\\t\\t\\\"*** YOUR CODE HERE ***\\\"\\n\\t\\treturn self.expectimax_value(gameState, 1, 0)\\n\\t\\tutil.raiseNotDefined()\",\n \"def get_user_input(self, game, hand, message, allowed_actions):\\n return 'hit'\",\n \"def get_user_input(self, game, hand, message, allowed_actions):\\n if self.first_turn:\\n hand = self.hands[0]\\n if hand.cards == 2:\\n card1, card2 = hand.cards\\n if card1.get_value() == card2.get_value():\\n return 'split'\\n return 'double'\\n else:\\n return 'stand'\",\n \"def getAction(self, gameState):\\n \\\"*** YOUR CODE HERE ***\\\"\\n return self.expectimax(gameState, 0, self.depth)[1]\",\n \"def action(self, action_space, observation, info): # pylint: disable=no-self-use\\n _ = observation # not using the observation for random decision\\n _ = info\\n\\n this_player_action_space = {Action.FOLD, Action.CHECK, Action.CALL, Action.RAISE_POT, Action.RAISE_HALF_POT,\\n Action.RAISE_2POT}\\n _ = this_player_action_space.intersection(set(action_space))\\n\\n action = None\\n return action\",\n \"def play_against_random(self, action):\\n state, status, done = self.step(action)\\n if not done and self.turn == 2:\\n state, s2, done = self.random_step()\\n if done:\\n if s2 == self.STATUS_WIN:\\n status = self.STATUS_LOSE\\n elif s2 == self.STATUS_TIE:\\n status = self.STATUS_TIE\\n else:\\n raise ValueError(\\\"???\\\")\\n return state, status, done\",\n \"def get_action(obs, player_x, player_y):\\n # if player is surrounded\\n if obs[\\\"memory_patterns\\\"][\\\"go_around_opponent_surrounded\\\"]:\\n return Action.HighPass\\n if Action.Sprint not in obs[\\\"sticky_actions\\\"]:\\n return Action.Sprint\\n return obs[\\\"memory_patterns\\\"][\\\"go_around_opponent\\\"]\",\n \"def get_action(self, state):\\r\\n if len (state.actions()) == 1:\\r\\n # dbstate = DebugState.from_state(state)\\r\\n # print (dbstate)\\r\\n self.queue.put(state.actions()[0])\\r\\n return\\r\\n if state.ply_count < 2:\\r\\n action = random.choice(state.actions())\\r\\n else:\\r\\n action = self.uct_search(state).action\\r\\n # dbstate = DebugState.from_state(state)\\r\\n # print (dbstate)\\r\\n if action is None:\\r\\n print(\\\"Incorrect action\\\")\\r\\n action = random.choice(state.actions())\\r\\n self.queue.put(action)\",\n \"def getAction(self, game, state):\\n if self.getUnknownCard(state) is None:\\n baseVal = self.getBase(state)\\n counts = self.getCounts(state)[baseVal]\\n if counts[0] > counts[1]:\\n return dnUtil.Action.Higher\\n elif counts[0] < counts[1]:\\n return dnUtil.Action.Lower\\n else:\\n if dnUtil.random.random() > 50:\\n return dnUtil.Action.Higher\\n else:\\n return dnUtil.Action.Lower\\n elif self.getLoseBool(state):\\n return dnUtil.Action.Exit\\n else:\\n nextVal = self.getUnknownCard(state)\\n nextCounts = self.getCounts(state)[nextVal]\\n deckSize = sum(nextCounts)\\n high, low, tie = nextCounts\\n\\n if high > low:\\n winrate = high / deckSize\\n elif high < low:\\n winrate = low / deckSize\\n else:\\n winrate = 0.5\\n\\n risk = game.getRisk()\\n if self.expectancyPcnt(winrate) > self.expectancyPcnt(risk / 100):\\n return dnUtil.Action.Continue, winrate * 100\\n else:\\n return dnUtil.Action.Exit, winrate * 100\",\n \"def get_action(obs, player_x, player_y):\\n if Action.Sprint in obs[\\\"sticky_actions\\\"]:\\n return Action.ReleaseSprint\\n return Action.Shot\",\n \"def getAction1(self, state):\\n # Pick Action\\n ############################################################################################################ Eric Changed state to self.index\\n\\n legalActions = state.getLegalActions(self.index)\\n #print \\\"LEGAL ACTIONS IN GETACTION1 IN QLEARNINGAGENT: \\\", legalActions\\n action = None\\n \\\"*** YOUR CODE HERE ***\\\"\\n if len(legalActions) == 0:\\n return None\\n coinTruth = util.flipCoin(self.epsilon)\\n if coinTruth:\\n acToReturn = random.choice(legalActions)\\n #print \\\"GETACTION1 IN QLEARNINGAGENT COINTRUTH IS TRUE, ACTION IS : \\\", acToReturn\\n return acToReturn\\n\\n\\n\\n #util.raiseNotDefined()\\n acToReturn = self.computeActionFromQValues(state)\\n #print \\\"GETACTION1 IN QLEARNINGAGENT COINTRUTH IS FALSE< ACTION IS : \\\", acToReturn\\n return acToReturn\",\n \"def getAction(self, state):\\n # Pick Action\\n legalActions = self.getLegalActions(state)\\n action = None\\n\\n \\\"\\\"\\\"Description:\\n Use util.flipCoin, if return true then randomly choice from legalAction\\n if flase, then sue getPolicy to get best policy action\\n \\\"\\\"\\\"\\n \\\"\\\"\\\" YOUR CODE HERE \\\"\\\"\\\"\\n if len(legalActions) == 0:\\n return action # None\\n \\n if util.flipCoin(self.epsilon):\\n ''' exploration function (not work well)''' \\n# posPol = util.Counter()\\n# for a in legalActions:\\n# if self.getQValue(state,a) >= 0:\\n# posPol[a] = -1*self.getQValue(state, a) + (1000/(self.vitCount[(state,a)]+0.0001))\\n# #print \\\"posPol[\\\", a, \\\"]= \\\",posPol[a]\\n# #posPol[a] = (self.getQValue(state, a) * self.epsilon** self.vitCount[(state,a)]) + ( self.epsilon/(self.vitCount[(state,a)]+0.1) )\\n# if len(posPol) == 0:\\n# action = random.choice(legalActions)\\n# else:\\n# action = posPol.argMax() # random.choice(posPol.keys())\\n ''' Random exploration '''\\n action = random.choice(legalActions)\\n else:\\n action = self.getPolicy(state)\\n \\n \\\"\\\"\\\" END CODE \\\"\\\"\\\"\\n\\n return action\",\n \"def getAction(self, gameState):\\n \\\"*** YOUR CODE HERE ***\\\"\\n\\n bestchoice = \\\"Stop\\\"\\n value = float(\\\"-inf\\\") \\n alpha = float(\\\"-inf\\\")\\n beta = float(\\\"inf\\\")\\n i = 0\\n actlist = gameState.getLegalActions(0)\\n while i < len(actlist):\\n action = actlist[i]\\n arg1 = self.minValue(gameState.generateSuccessor(0, action), 1, self.depth, alpha, beta)\\n maxVal = max(value, arg1)\\n if maxVal > beta:\\n bestchoice = action\\n break\\n alpha = max(alpha, maxVal)\\n if maxVal > value:\\n value = maxVal\\n bestchoice = action\\n i = i + 1\\n return bestchoice\",\n \"def _select_action(self):\\n if self.eval_mode:\\n self._log_values()\\n epsilon = self.epsilon_eval\\n else:\\n epsilon = self.epsilon_fn(\\n self.epsilon_decay_period,\\n self.training_steps,\\n self.min_replay_history,\\n self.epsilon_train)\\n if random.random() <= epsilon:\\n # Choose a random action with probability epsilon.\\n return random.randint(0, self.num_actions - 1)\\n else:\\n # Choose the action with highest Q-value at the current state according\\n # to the current head.\\n return self._compute_q_argmax()\",\n \"def sample_action(self, creature, combat_handler):\\n enemy = self.determine_enemy(creature=creature, combat_handler=combat_handler)\\n current_state = self.get_raw_state(\\n creature=creature,\\n enemy=enemy,\\n combat_handler=combat_handler\\n )\\n num_attacks_used = current_state[0][NUM_ATTACKS_USED]\\n if num_attacks_used < 1:\\n action = creature.get_action(\\\"Arrow Shot\\\")\\n else:\\n action = creature.get_action(\\\"end_turn\\\")\\n\\n return action, None, None\",\n \"def get_action(obs, player_x, player_y):\\n if player_y > 0:\\n if Action.Top not in obs[\\\"sticky_actions\\\"]:\\n return Action.Top\\n else:\\n if Action.Bottom not in obs[\\\"sticky_actions\\\"]:\\n return Action.Bottom\\n if Action.Sprint in obs[\\\"sticky_actions\\\"]:\\n return Action.ReleaseSprint\\n return Action.ShortPass\",\n \"def select_action(self, state):\\n\\t\\treturn sample(range(0, self.action_space), 1)[0]\",\n \"def chooseAction(self, gameState):\\n actions = gameState.getLegalActions(self.index)\\n\\n # You can profile your evaluation time by uncommenting these lines\\n # start = time.time()\\n values = [self.evaluate(gameState, a) for a in actions]\\n # print 'eval time for agent %d: %.4f' % (self.index, time.time() - start)\\n\\n maxValue = max(values)\\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\\n\\n return random.choice(bestActions)\",\n \"def get_random_action():\\n # Define an array containing the available actions for the UAV\\n # in the final work, takeoff and land must be added\\n action_list = ['left', 'right', 'forward', 'backward', 'stop', 'descend']\\n # Choose a random action within the array\\n #action_index = STDrandom.randint(0, len(action_list) - 1)\\n # forward,backward,left,right, stop and land\\n probability_descend = 0.25\\n probability = (1 - probability_descend)/ (len(action_list) -1)\\n action_probability = [probability, probability, probability, probability, probability, probability_descend]\\n action = np.random.choice(action_list, 1, p=action_probability)[0]\\n #action_index = STDrandom.randint(0, 10)\\n #action = action_list[action_index]\\n\\n return action\",\n \"def get_action(obs, player_x, player_y):\\n if Action.Right not in obs[\\\"sticky_actions\\\"]:\\n return Action.Right\\n return Action.ShortPass\",\n \"def getAction(self, state):\\n # Pick Action\\n legalActions = self.getLegalActions(state)\\n action = None\\n \\\"*** YOUR CODE HERE ***\\\"\\n length_legalActions = len(legalActions) #Find length of allowed actions\\n\\n if length_legalActions == 0: #To check if no legal action is possible, that is incase of terminal state\\n action = None #set action as none and return from here\\n return action\\n\\n epsilon = self.epsilon #to get the epsilon value\\n\\n if util.flipCoin(epsilon): #util.flipcoin returns binary variable with probability p of success by using util.flipCoin(p), which returns True with probability p and False with probability 1-p.\\n action = random.choice(legalActions) #Choosing randomly from list of allowed actions\\n return action\\n\\n action = self.getPolicy(state) #Without probability epsilon we should take best policy action. getPolicy function calls the computeActionFromQValues function which gives us the best action to take in a state\\n\\n #util.raiseNotDefined()\\n\\n return action\",\n \"def getAction(self):\\n # Module player is always assumed player #0\\n state = [0] * (4+self.game.numPlayers*2)\\n state[0] = (0,1)[self.game.roles[0] == \\\"Werewolf\\\"]\\n state[1] = (0,1)[self.game.roles[0] == \\\"Villager\\\"]\\n state[2] = (0,1)[self.game.turnnum == 0]\\n state[3] = (0,1)[self.game.turnnum == 1]\\n for i in range(len(self.game.claim)):\\n state[4+i*2+0] = (0,1)[self.game.claim[i] == \\\"Werewolf\\\"]\\n state[4+i*2+1] = (0,1)[self.game.claim[i] == \\\"Villager\\\"]\\n #state[4+i*2+0] = (0,1)[self.game.roles[0] == \\\"Werewolf\\\"]\\n #state[4+i*2+1] = (0,1)[self.game.roles[0] == \\\"Villager\\\"]\\n self.module.reset()\\n output = self.module.activate(state)\\n result = None\\n if (self.game.turnnum == 0):\\n if output[0] > output[1]: result = \\\"Werewolf\\\"\\n else : result = \\\"Villager\\\"\\n else:\\n votes = output[2:]\\n result = drawGibbs(votes, self.temperature) + 1\\n #print (\\\"votes, result\\\", votes, result)\\n #print ()\\n #print (\\\"input\\\", state)\\n #print (self.game.stateStr())\\n #print (\\\"output\\\", output, result)\\n #print ()\\n return [self.pnum, result]\",\n \"def choose_action(self, board, possible_actions):\\r\\n self._print_board(board)\\r\\n while True:\\r\\n user_choice = int(input(\\\"Which Field?\\\"))\\r\\n if user_choice in possible_actions:\\r\\n return user_choice\\r\\n else:\\r\\n print('Action not possible!')\",\n \"def chooseAction(self, gameState):\\n probabilities = self.assignProbablities(gameState)\\n #print probabilities\\n prob, bestProbabilityAction = max(probabilities)\\n return bestProbabilityAction\",\n \"def get_action_from_user(self) -> ActionType:\\n if self.wait_for_explicit_human_action:\\n while len(self.renderer.pressed_keys) == 0:\\n self.renderer.get_events()\\n\\n if self.key_to_action == {}:\\n # the keys are the numbers on the keyboard corresponding to the action index\\n if len(self.renderer.pressed_keys) > 0:\\n action_idx = self.renderer.pressed_keys[0] - ord(\\\"1\\\")\\n if 0 <= action_idx < self.action_space.shape[0]:\\n return action_idx\\n else:\\n # the keys are mapped through the environment to more intuitive keyboard keys\\n # key = tuple(self.renderer.pressed_keys)\\n # for key in self.renderer.pressed_keys:\\n for env_keys in self.key_to_action.keys():\\n if set(env_keys) == set(self.renderer.pressed_keys):\\n return self.action_space.actions[self.key_to_action[env_keys]]\\n\\n # return the default action 0 so that the environment will continue running\\n return self.action_space.default_action\",\n \"def getAction(self, gameState):\\n \\\"*** YOUR CODE HERE ***\\\"\\n return self.expectimax(gameState,self.depth * 2,0,True)[1]\\n util.raiseNotDefined()\",\n \"def action_menu(player):\\n\\n\\tclear_screen()\\n\\n\\trun_game_log(player, game_log)\\t# runs the run_game_log function which gets output from game_log class\\n\\n\\tprint('1. Move')\\n\\tprint('2. Show Map')\\n\\tprint('3. Show Player Inventory')\\n\\tprint('4. Show Player Stats')\\n\\tprint('5. Exit to Main Menu')\\n\\n\\tpossible_choices = ['1','2','3','4','5']\\n\\tactive = True\\n\\n\\twhile active:\\n\\t\\tselection = input('\\\\nNow I shall... ')\\n\\t\\tif selection in possible_choices:\\n\\t\\t\\tactive = False\\n\\t\\t\\treturn int(selection)\\t# return always exits a function, right? so active = False is redundant?\\n\\t\\telse:\\n\\t\\t\\tprint('That\\\\'s not one of the menu options!')\",\n \"def chooseAction(self, gameState):\\n\\n actions = gameState.getLegalActions(self.index)\\n obs = gameState.getAgentDistances()\\n for o in self.opponents:\\n self.observe(o, obs[o], gameState)\\n self.displayDistributionsOverPositions(self.distributions)\\n\\n # You can profile your evaluation time by uncommenting these lines\\n start = time.time()\\n values = [self.evaluate(gameState, a) for a in actions]\\n print 'eval time for agent %d: %.4f' % (self.index, time.time() - start)\\n\\n maxValue = max(values)\\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\\n\\n #self.elapseTime(gameState)\\n\\n return random.choice(bestActions)\",\n \"def getAction(self, gameState):\\n \\\"*** YOUR CODE HERE ***\\\"\\n #the return value of \\\"result\\\" function is (action, score) pair\\n a = self.result(gameState,0)[0]\\n return a\\n util.raiseNotDefined()\",\n \"def getAction(self, gameState):\\n \\\"*** YOUR CODE HERE ***\\\"\\n return self.minimax(gameState, 0, self.depth)[1]\",\n \"def select_action(self, state: str) -> Action:\\n rnd_num = self._random.random()\\n p = 1.0 - self.epsilon\\n if rnd_num > p:\\n action = self._random.random_choice() \\n else:\\n action = max(self.Qs[state], key=lambda x: self.Qs[state][x])\\n if self.epsilon_decay == True:\\n self.turns += 1\\n if self.turns < self.end_epsilon_decay:\\n self.epsilon -= self.decay_value \\n return action\",\n \"def getAction(self, gameState):\\n\\t\\t\\\"*** YOUR CODE HERE ***\\\"\\n\\t\\treturn self.minimax_value(gameState, 1, 0)\\n\\t\\tutil.raiseNotDefined()\",\n \"def get_action(obs, player_x, player_y):\\n return Action.Left\",\n \"def perform_action(self, action):\\n \\n assert self.is_valid_action(action)\\n \\n # Save the action.\\n self.action = action\\n \\n #the slight strategy of the opponent\\n if self.reward==rLose :\\n observation = self.observation\\n else:\\n observation = random.choice([oRock,oPaper,oScissor])\\n \\n #determine the result of the game and get the reward\\n if action == aRock:\\n if observation == oRock:\\n reward= rDraw\\n elif observation == oPaper:\\n reward= rLose\\n elif observation == oScissor:\\n reward= rWin\\n elif action == aPaper:\\n if observation == oRock:\\n reward= rWin\\n elif observation == oPaper:\\n reward= rDraw\\n elif observation == oScissor:\\n reward= rLose\\n elif action == aScissor:\\n if observation == oRock:\\n reward= rLose\\n elif observation == oPaper:\\n reward= rWin\\n elif observation == oScissor:\\n reward= rDraw\\n \\n \\n #Store the observation and reward in the environment.\\n self.observation = observation\\n \\n self.reward = reward\\n \\n \\n return (observation, reward)\\n # end def\",\n \"def get_action(obs, player_x, player_y):\\n return Action.HighPass\",\n \"def getAction(self, state):\\n # Pick Action\\n legalActions = self.getLegalActions(state)\\n if len(legalActions) == 0:\\n return None\\n elif util.flipCoin(self.epsilon):\\n return random.choice(legalActions)\\n else:\\n return self.getPolicy(state)\",\n \"def chooseAction(self, gameState):\\r\\n actions = gameState.getLegalActions(self.index)\\r\\n\\r\\n # You can profile your evaluation time by uncommenting these lines\\r\\n # start = time.time()\\r\\n values = [self.evaluate(gameState, a) for a in actions]\\r\\n # print 'eval time for agent %d: %.4f' % (self.index, time.time() - start)\\r\\n\\r\\n maxValue = max(values)\\r\\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\\r\\n\\r\\n foodLeft = len(self.getFood(gameState).asList())\\r\\n\\r\\n if foodLeft <= 2:\\r\\n bestDist = 9999\\r\\n for action in actions:\\r\\n successor = self.essor(gameState, action)\\r\\n pos2 = successor.getAgentPosition(self.index)\\r\\n dist = self.getMazeDistance(self.start,pos2)\\r\\n if dist < bestDist:\\r\\n bestAction = action\\r\\n bestDist = dist\\r\\n return bestAction\\r\\n\\r\\n return random.choice(bestActions)\",\n \"def getAction(self, gameState):\\n \\\"*** YOUR CODE HERE ***\\\"\\n a = self.result(gameState,0)[0]\\n return a\\n util.raiseNotDefined()\",\n \"def getAction(self, gameState):\\n \\\"*** YOUR CODE HERE ***\\\"\\n a = self.result(gameState,0)[0]\\n return a\\n util.raiseNotDefined()\",\n \"def get_attack(self, pykemon):\\n #Show the moves list using pykemon specific move names\\n print(\\\"\\\\nWhat would you like to do...\\\")\\n print(\\\"(1) - \\\" + pykemon.moves[0])\\n print(\\\"(2) - \\\" + pykemon.moves[1])\\n print(\\\"(3) - \\\" + pykemon.moves[2])\\n print(\\\"(4) - \\\" + pykemon.moves[3])\\n choice = int(input(\\\"Please enter your move choice: \\\"))\\n\\n #Formatting\\n print()\\n print(\\\"-----------------------------------------------------------------------------\\\")\\n\\n return choice\",\n \"def chooseAction(self, gameState):\\n\\n actions = gameState.getLegalActions(self.index)\\n\\n values = [self.evaluate(gameState, a) for a in actions]\\n\\n maxValue = max(values)\\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\\n\\n return random.choice(bestActions)\",\n \"def chooseAction(self, gameState):\\n\\n ####print \\\"chooseAction Called\\\"\\n\\n #self.lastEatenFood = None\\n\\n\\n actions = gameState.getLegalActions(self.index)\\n\\n ##print \\\"\\\\nNEW ACTION\\\\n--------\\\"\\n\\n # You can profile your evaluation time by uncommenting these lines\\n # start = time.time()\\n values = [self.evaluate(gameState, a) for a in actions]\\n # ###print 'eval time for agent %d: %.4f' % (self.index, time.time() - start)\\n\\n maxValue = max(values)\\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\\n\\n \\n\\n return random.choice(bestActions)\",\n \"def chooseAction(self, gameState):\\n myState = gameState.getAgentState(self.index)\\n myPos = myState.getPosition()\\n ghosts = self.getGhosts(gameState)\\n\\n if self.lastState:\\n myLastState = self.lastState.getAgentState(self.index)\\n \\n ghosts = self.getGhosts(gameState)\\n if len(ghosts) > 0:\\n minDistToGhost = min([self.getMazeDistance(myPos, a.getPosition()) for a in ghosts])\\n if not myState.isPacman and myLastState.isPacman and minDistToGhost <= 3 and self.specificPath == []:\\n path, target = self.getAlternativePath(gameState, minPathLength=5)\\n self.specificPath = path\\n self.targetPos = target\\n \\n if len(self.specificPath) > 0:\\n return self.specificPath.pop(0)\\n elif self.isStucking(gameState):\\n actions, target = self.getAlternativePath(gameState, minPathLength=5)\\n if len(actions) > 0:\\n self.specificPath = actions\\n self.targetPos = target\\n return self.specificPath.pop(0)\\n else:\\n actions = gameState.getLegalActions(self.index)\\n return random.choice(actions)\\n\\n actions = gameState.getLegalActions(self.index)\\n actions.remove('Stop')\\n\\n if len(ghosts) > 0:\\n distToGhost = min([self.getMazeDistance(myPos, a.getPosition()) for a in ghosts])\\n if not self.isOppoentsScared(gameState) and myState.isPacman and distToGhost <= 6:\\n safeActions = self.getSafeActions(gameState)\\n if len(safeActions) > 0:\\n actions = safeActions\\n\\n values = [self.getQValue(gameState, a) for a in actions]\\n maxValue = max(values)\\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\\n bestAction = random.choice(bestActions)\\n \\n self.doAction(gameState, bestAction)\\n\\n return bestAction\",\n \"def random_play(state, player):\\n import random\\n actions = YoteRules.get_player_actions(state, player, reward_move=state.rewarding_move)\\n choice = random.choice(actions)\\n return choice\",\n \"def choose_action(self, board, possible_actions):\\r\\n pass\",\n \"def action(self):\\n obs = self.observation\\n\\n action = None\\n try:\\n if SETTINGS_DEAD_CANT_THINK and obs.respawn_in > -1:\\n self.debugMsg(\\\"Sleeping\\\")\\n return (0,0,False)\\n\\n # Check if agent reached goal.\\n if self.goal and point_dist(self.goal, obs.loc) < self.settings.tilesize:\\n self.goal = None\\n\\n # If agent already has a goal\\n # check if the motivation is still accurate\\n if self.goal:\\n self.validateMotivation()\\n\\n # Drive to where the user clicked\\n if self.selected and self.observation.clicked:\\n self.motivation = MOTIVATION_USER_CLICK\\n self.goal = obs.clicked\\n\\n if self.goal is None:\\n if self.strategy == STRATEGY_DEFENCE:\\n action = self.action_defend()\\n elif self.strategy == STRATEGY_OFFENCE:\\n action = self.action_offence()\\n else:\\n action = self.action_normal()\\n else:\\n self.debugMsg(\\\"Goal already found: (%d,%d)\\\" % self.goal)\\n except Exception:\\n self.goal = None\\n# self.debugMsg(\\\"Goal: %s, exception: %s\\\" % (self.goal, exp), True)\\n \\n if self.goal is None:\\n self.goal = obs.loc\\n\\n self.updateTrendingSpot()\\n if action is None:\\n if self.goal == obs.loc:\\n return (0,0,False)\\n else:\\n return self.getActionTriple()\\n else:\\n return action\",\n \"def get_action(obs, player_x, player_y):\\n if (random.random() < 0.5 and\\n Action.TopRight not in obs[\\\"sticky_actions\\\"] and\\n Action.BottomRight not in obs[\\\"sticky_actions\\\"]):\\n return Action.TopRight\\n else:\\n if Action.BottomRight not in obs[\\\"sticky_actions\\\"]:\\n return Action.BottomRight\\n return Action.ShortPass\",\n \"def choose_action(self, agent_data):\\r\\n action_value_estimates = agent_data[\\\"action_value_estimates\\\"]\\r\\n roll = random.uniform(0,1)\\r\\n if roll <= self.epsilon:\\r\\n action = random.choice( list( range(0,len(action_value_estimates))))\\r\\n else:\\r\\n action = self.argmax_with_random_tiebreaker(action_value_estimates)\\r\\n return action\",\n \"def chooseAction(self, gameState):\\n actions = gameState.getLegalActions(self.index)\\n\\n # You can profile your evaluation time by uncommenting these lines\\n # start = time.time()\\n values = [self.evaluate(gameState, a) for a in actions]\\n # print 'eval time for agent %d: %.4f' % (self.index, time.time() - start)\\n\\n maxValue = max(values)\\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\\n\\n foodLeft = len(self.getFood(gameState).asList())\\n\\n if foodLeft <= 2:\\n bestDist = 9999\\n for action in actions:\\n successor = self.getSuccessor(gameState, action)\\n pos2 = successor.getAgentPosition(self.index)\\n dist = self.getMazeDistance(self.start, pos2)\\n if dist < bestDist:\\n bestAction = action\\n bestDist = dist\\n return bestAction\\n\\n return random.choice(bestActions)\",\n \"def get_random_action(self) -> ActionType:\\n return self.action_space.sample()\",\n \"def chooseAction(self,state):\\r\\n #generate float btwn 0-1\\r\\n choice = random.random()\\r\\n \\r\\n #choose according to that number\\r\\n if choice > self.epsilon:\\r\\n return(self.maxQ(state)[1])\\r\\n else:\\r\\n #choose randomly\\r\\n return(self.actions[random.randrange(0,len(self.actions))])\",\n \"def chooseAction(self,state):\\r\\n #generate float btwn 0-1\\r\\n choice = random.random()\\r\\n \\r\\n #choose according to that number\\r\\n if choice > self.epsilon:\\r\\n return(self.maxQ(state)[1])\\r\\n else:\\r\\n #choose randomly\\r\\n return(self.actions[random.randrange(0,len(self.actions))])\",\n \"def chooseAction(self, gameState):\\n\\n actions = gameState.getLegalActions(self.index)\\n # actions.remove(Directions.STOP)\\n # You can profile your evaluation time by uncommenting these lines\\n # start = time.time()\\n values = [self.evaluate(gameState, a) for a in actions]\\n # print 'eval time for agent %d: %.4f' % (self.index, time.time() - start)\\n maxValue = max(values)\\n bestActions = [a for a, v in zip(actions, values) if v == maxValue]\\n\\n foodLeft = len(self.getFood(gameState).asList())\\n if foodLeft <= 2:\\n bestDist = 9999\\n for action in actions:\\n successor = self.getSuccessor(gameState, action)\\n pos2 = successor.getAgentPosition(self.index)\\n dist = self.getMazeDistance(self.start,pos2)\\n if dist < bestDist:\\n bestAction = action\\n bestDist = dist\\n return bestAction\\n\\n return random.choice(bestActions)\",\n \"def best_action(self, state):\\n return random.choice(self.possible_actions)\",\n \"def getAction(self, gameState):\\n \\\"*** YOUR CODE HERE ***\\\"\\n best_result = self.getexpectimax(gameState, 0, 0, gameState.getNumAgents())\\n return best_result[0] # return the result\",\n \"def action(self, gstate, actions):\\n self.log.debug(\\\"Picking among actions %s\\\" % actions)\\n return actions[0]\",\n \"def choose_action(self, board):\\n options = board.empty_cells\\n # to allow exploration, have a small probability of a random move\\n p_random = random.random()\\n # if the state is not in the table add it\\n if (self.sign, board.state) not in self.Q_table.keys() or p_random < self.epsilon:\\n values = {}\\n for option in options:\\n values[option] = random.random()\\n self.Q_table[(self.sign, board.state)] = values\\n self.action = random.choice(options)\\n else:\\n values = self.Q_table[(self.sign, board.state)]\\n action = max(values, key=values.get)\\n self.action = action\\n\\n # decrease exploration after each action\\n if self.epsilon > 0:\\n self.epsilon -= 0.0001\\n\\n return self.action\",\n \"def user_action():\\n\\t### This is the function that takes and executes the users choices\\n\\twhile battle_on:\\n\\t\\tchoosing = True\\n\\t\\twhile choosing:\\n\\t\\t\\tmenu(\\\"general\\\")\\n\\t\\t\\tanswer()\\n\\t\\t\\tif ans == \\\"attack\\\":\\n\\t\\t\\t\\tattack(my_pokemon, enemy)\\n\\t\\t\\t\\tcalc_hp(enemy, \\\"attack\\\")\\n\\t\\t\\t\\tshow_hp(enemy)\\n\\t\\t\\t\\tprint \\\" \\\"\\n\\t\\t\\t\\treturn\\n\\t\\t\\telif ans == \\\"flee\\\":\\n\\t\\t\\t\\tchance = uniform(0, 100)\\n\\t\\t\\t\\tif chance > 90:\\n\\t\\t\\t\\t\\twin(\\\"flee\\\")\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\tprint \\\"You failed to escape!\\\"\\n\\t\\t\\t\\t\\treturn\\n\\t\\t\\telif ans == \\\"potion\\\":\\n\\t\\t\\t\\tuse_potion(my_pokemon)\\n\\t\\t\\t\\treturn\\n\\t\\t\\telse:\\n\\t\\t\\t\\tprint \\\"i dont know what you mean :)\\\"\\n\\t\\t\\t\\tprint \\\"lets try again!\\\"\\n\\t\\t\\t\\tchoosing = True\",\n \"def getAction(self, gameState):\\n return self.expectimax(gameState, self.depth, 0)\",\n \"def get_action(obs, player_x, player_y):\\n if player_y <= -0.03 or (player_y > 0 and player_y < 0.03):\\n if Action.BottomRight not in obs[\\\"sticky_actions\\\"]:\\n return Action.BottomRight\\n else:\\n if Action.TopRight not in obs[\\\"sticky_actions\\\"]:\\n return Action.TopRight\\n if Action.Sprint in obs[\\\"sticky_actions\\\"]:\\n return Action.ReleaseSprint\\n return Action.Shot\",\n \"def get_action():\\n print(\\\"What do you do next?\\\")\\n print(\\\" m) move\\\")\\n print(\\\" a) fire an arrow\\\")\\n action = input(\\\"> \\\")\\n if action == \\\"m\\\" or action == \\\"a\\\":\\n return action\\n else:\\n print(action + \\\"?\\\")\\n print(\\\"That's not an action that I know about\\\")\\n return False\",\n \"def obtain_action(self, timestep):\\r\\n\\t\\treturn random.randint(0, self.num_actions-1)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7664304","0.76305485","0.7418116","0.7145675","0.71054864","0.7077956","0.70766556","0.70766556","0.70401573","0.6945828","0.69291","0.68862695","0.682164","0.68153846","0.6801916","0.6727821","0.67192125","0.6679106","0.66654944","0.66654944","0.66616535","0.66437554","0.6643395","0.6617352","0.6616787","0.66082335","0.65675956","0.65650064","0.65569377","0.6549011","0.65351826","0.6534965","0.6527093","0.6526833","0.6521981","0.6489602","0.64846325","0.6482397","0.6481578","0.64794326","0.6473889","0.64712155","0.6469555","0.6463533","0.64543974","0.6449622","0.64446056","0.644191","0.6435903","0.6433504","0.6431971","0.6426034","0.6425924","0.6423068","0.6419585","0.6418438","0.6416485","0.6412011","0.6410306","0.640871","0.6402429","0.63991493","0.63951445","0.6385319","0.6382725","0.6371943","0.6370669","0.6359676","0.6357427","0.6354577","0.63496","0.63490933","0.63480544","0.63428396","0.6342424","0.63281345","0.63281345","0.63215554","0.6315267","0.6315167","0.63005954","0.6296598","0.62960416","0.6293423","0.62796885","0.6277061","0.6275085","0.62704265","0.6269481","0.6269481","0.6246425","0.6239495","0.6234619","0.62330025","0.62310815","0.62254035","0.62247556","0.6222658","0.6222222","0.6212645"],"string":"[\n \"0.7664304\",\n \"0.76305485\",\n \"0.7418116\",\n \"0.7145675\",\n \"0.71054864\",\n \"0.7077956\",\n \"0.70766556\",\n \"0.70766556\",\n \"0.70401573\",\n \"0.6945828\",\n \"0.69291\",\n \"0.68862695\",\n \"0.682164\",\n \"0.68153846\",\n \"0.6801916\",\n \"0.6727821\",\n \"0.67192125\",\n \"0.6679106\",\n \"0.66654944\",\n \"0.66654944\",\n \"0.66616535\",\n \"0.66437554\",\n \"0.6643395\",\n \"0.6617352\",\n \"0.6616787\",\n \"0.66082335\",\n \"0.65675956\",\n \"0.65650064\",\n \"0.65569377\",\n \"0.6549011\",\n \"0.65351826\",\n \"0.6534965\",\n \"0.6527093\",\n \"0.6526833\",\n \"0.6521981\",\n \"0.6489602\",\n \"0.64846325\",\n \"0.6482397\",\n \"0.6481578\",\n \"0.64794326\",\n \"0.6473889\",\n \"0.64712155\",\n \"0.6469555\",\n \"0.6463533\",\n \"0.64543974\",\n \"0.6449622\",\n \"0.64446056\",\n \"0.644191\",\n \"0.6435903\",\n \"0.6433504\",\n \"0.6431971\",\n \"0.6426034\",\n \"0.6425924\",\n \"0.6423068\",\n \"0.6419585\",\n \"0.6418438\",\n \"0.6416485\",\n \"0.6412011\",\n \"0.6410306\",\n \"0.640871\",\n \"0.6402429\",\n \"0.63991493\",\n \"0.63951445\",\n \"0.6385319\",\n \"0.6382725\",\n \"0.6371943\",\n \"0.6370669\",\n \"0.6359676\",\n \"0.6357427\",\n \"0.6354577\",\n \"0.63496\",\n \"0.63490933\",\n \"0.63480544\",\n \"0.63428396\",\n \"0.6342424\",\n \"0.63281345\",\n \"0.63281345\",\n \"0.63215554\",\n \"0.6315267\",\n \"0.6315167\",\n \"0.63005954\",\n \"0.6296598\",\n \"0.62960416\",\n \"0.6293423\",\n \"0.62796885\",\n \"0.6277061\",\n \"0.6275085\",\n \"0.62704265\",\n \"0.6269481\",\n \"0.6269481\",\n \"0.6246425\",\n \"0.6239495\",\n \"0.6234619\",\n \"0.62330025\",\n \"0.62310815\",\n \"0.62254035\",\n \"0.62247556\",\n \"0.6222658\",\n \"0.6222222\",\n \"0.6212645\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6747504"},"document_rank":{"kind":"string","value":"15"}}},{"rowIdx":81468,"cells":{"query":{"kind":"string","value":"Retuns the wager the player chooses for this round. It cannot exceed the maximum available."},"document":{"kind":"string","value":"def get_wager_input(max_chips, min_chips=1):\n chips = 0\n while chips < min_chips or chips > max_chips:\n chips = input('How many chips do you wager? (min %d, max %d): ' % (min_chips, max_chips))\n try:\n chips = int(chips)\n except:\n chips = 0\n return chips"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def round_based_alien_limitation(self):\n if self.num_round < 5:\n return 1\n elif self.num_round < 10:\n return 2\n else:\n return 3","def take(self, desired_amount):\n if self.amount >= desired_amount:\n grab = desired_amount\n else:\n grab = min(desired_amount, self.amount)\n self.amount -= grab\n print(f\"{self} {self.amount} of supplies left\")\n return grab","def determine_win(self):\n if self.match.radiant_win is True and self.player_slot < 5:\n return True\n if self.match.radiant_win is False and self.player_slot > 5:\n return True\n return False","def who_won(self):\n if self.dealer.hand.value > 21:\n dealer_busts(self.pot)\n self.player.get_money(self.pot)\n elif self.dealer.hand.value > self.player.hand.value:\n dealer_win(self.dealer.hand, self.player.hand, self.pot)\n self.player.pay_out(self.pot)\n elif self.dealer.hand.value == self.player.hand.value:\n push(self.dealer.hand.value, self.player.hand.value)\n else:\n player_win_text(self.pot)\n self.player.get_money(self.pot)","def STAND_LIMIT() -> int:\n return 15","def round(self):\n #player turn\n if self.started:\n self.started = False #registers the game as started then immediately turns that value false\n if self.initial_action:\n card = self.deck.deal()\n self.player.value += card.value\n if card.is_ace:\n self.player.usable_ace = True\n else:\n self.player.playing = False\n else: \n if self.apply_policy():\n card = self.deck.deal()\n self.player.value += card.value\n if card.is_ace:\n self.player.usable_ace = True\n else:\n self.player.playing = False\n\n #dealer turn\n if self.dealer.value < 17:\n card = self.deck.deal()\n self.dealer.value += card.value\n self.dealer.visible_value += card.value\n #allow people to reduce their scores by applying aces\n self.apply_ace()\n #check to see if anyone has bust by making bust people not _playing\n if self.player.value > 21:\n self.player.broke = True\n self.player.playing = False\n if self.dealer.value > 21:\n self.dealer.broke = True","def get_max_win_strength(self):\n if self.maxWinStrength is None:\n self.calculate_max_win_strength()\n return self.maxWinStrength","def reward(self, winner):\n if winner == self.side:\n return self.win\n elif winner == VALUES.NOT_FINISHED:\n return self.not_finished\n elif winner == VALUES.DRAW:\n return self.draw\n else:\n return self.lose","def get_winner(self) -> None:\n if not self.get_game_ending_hands():\n if max(self.user.hand.value) > max(self.house.hand.value): # Values above 21 are omitted\n self.event_player_wins()\n elif max(self.user.hand.value) == max(self.house.hand.value):\n self.event_player_push()\n else:\n self.event_house_wins()","def calc_winner(self):\n pass","def WIN_BONUS() -> int:\n return 2","def evaluateWinner(self):\n\t\tif self.pots[-1] == 0:\n\t\t\tself.pots.pop()\n\t\tlivePlayers = self.getLivePlayers()\t\n\t\tfor i in range(len(self.pots)):\n\t\t\tplayers = self.getPlayersInPot(i, livePlayers)\n\t\t\tevaluations = []\n\t\t\tfor x in players:\n\t\t\t\tcombined = x.hand + self.communityCards\n\t\t\t\tevaluations.append((x, self.evaluator.getRankOfSeven(\tcombined[0], \\\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tcombined[1], \\\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tcombined[2], \\\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tcombined[3], \\\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tcombined[4], \\\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tcombined[5], \\\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tcombined[6] )))\n\t\t\twinners = self.getWinners(evaluations, i)\n\t\t\tself.handOutMoney(winners, i)\n\t\t\tself.potwinQ.append(winners[0].name)","def next_choice(self, opponent: 'Player') -> str:\n\n if self.adaptive_ai:\n # this is an adaptive_ai player, so see if it has collected\n # enough stats about the current opponent yet:\n if sum(self.opponent_choices[opponent.name].values()) > 5:\n # has enough samples to start adapting to the opponent\n print(' {} is trying to guess the opponent\\'s choice...'.format(self.name))\n\n # AI algorithm 1:\n # simply find the most-frequent selection by the opponent and\n # choose its killer.\n\n guess = self.opponent_choices[opponent.name].most_common(1)[0][0]\n ai_choice = weapon_to_beat(guess)\n print(' ', opponent.name, 'most often chose', guess, 'so he/she chose', ai_choice)\n return ai_choice\n\n # use the standard tendency distribution to choose a weapon:\n n = randint(1, self.randmax)\n if n <= self.tendency[0]:\n return 'rock'\n elif n <= self.tendency[0] + self.tendency[1]:\n return 'paper'\n else:\n return 'scissors'","def select_win_game(self):\r\n win_game_anims =['anim_speedtap_winround_intensity01_01',\r\n 'anim_speedtap_winround_intensity02_02',\r\n 'anim_speedtap_winround_intensity02_01',\r\n 'anim_speedtap_wingame_intensity02_01',\r\n 'anim_speedtap_wingame_intensity02_02',\r\n 'anim_speedtap_wingame_intensity03_01']\r\n cozmo.logger.info(\"Cozmo win game reacion\")\r\n return win_game_anims[randint(0,5)]","def who_won(self):\n if self.scoreB >= WP: return Stone.BLACK\n if self.scoreW >= WP: return Stone.WHITE\n return self.last","def most_powerful_weapon(self):\n # sets inital damge to 0\n max_damage = 0\n # sets the best weapon to nothing\n best_weapon = None\n # Loop for each item in inventory\n for item in self.inventory:\n # Code adapted from Make Your own Python Text Based Adventure\n # tries to see if the item damage is greator than the current max\n # damage and then replaces the best weapon in inventory\n try:\n if item.damage > max_damage:\n best_weapon = item\n max_damage = item.damage\n except AttributeError:\n pass\n # sends the best weapon to function\n return best_weapon","def play_war_round(player):\n for i in xrange(4):\n play_normal_round(player)\n\n return player","def get_winner(self):\n winner: Player = Player('none')\n points_winner = 0\n for player in self.players:\n for key, value in player.get_stats().items():\n print('{}: {}'.format(key, value))\n if key == 'points':\n if value >= points_winner:\n winner = player\n print()\n\n print('The winner is: ' + winner.get_name())\n return winner","def determineWinner(self):\n if self.game_state.numActive() == 1:\n for player in self.game_state.player_list:\n if self.game_state.active_dict[player.name]:\n print \"\"\n print player.name + \" wins with\"\n for card in self.player_hand_dict[player.name]:\n print card\n print \"and takes \" + str(self.game_state.pot) + \" chips!\"\n self.game_state.player_chips[player.name] += self.game_state.pot\n return\n\n for player in self.game_state.player_list:\n for card in self.game_state.board:\n self.player_hand_dict[player.name].append(Card(card.suit, card.rank))\n hand_ranking = HandRanking(self.game_state.player_list, self.player_hand_dict)\n hand_ranking.rankHands()\n winning_rank = -1\n winner = None\n tie_list = []\n \"\"\" Get winning rank, only consider active players for the pot \"\"\"\n for player in self.game_state.player_list:\n if self.game_state.active_dict[player.name] == True:\n if DEBUG:\n print \"Considering \" + str(player.name) + \"'s hand for the pot.\"\n if hand_ranking.player_ranks_dict[player.name] > winning_rank:\n winning_rank = hand_ranking.player_ranks_dict[player.name]\n winner = player \n tie_list = []\n tie_list.append(player)\n elif hand_ranking.player_ranks_dict[player.name] == winning_rank:\n tie_list.append(player)\n \"\"\" winner should never be equal to None \"\"\"\n\n \"\"\" Check for tie and resolve if needed \"\"\"\n if len(tie_list) > 1:\n if DEBUG:\n print \"found potential tie...\"\n for player in tie_list:\n print player.name + \"'s hand:\"\n for card in hand_ranking.player_best_hand_dict[player.name]:\n print card\n print \"resolving tie...\"\n result_tie_list = self.resolveTie(hand_ranking, tie_list)\n print \"\"\n self.printPlayersHands()\n for player in result_tie_list:\n print player.name + \",\",\n print \" wins with\",\n hand_ranking.printRanking(winning_rank)\n print \"and takes \" + str(self.game_state.pot / len(tie_list)) + \" chips!\"\n for player in result_tie_list:\n self.game_state.player_chips[player.name] += self.game_state.pot / len(tie_list)\n else:\n print \"\"\n self.printPlayersHands()\n print winner.name + \" wins with\",\n hand_ranking.printRanking(winning_rank)\n print \"and takes \" + str(self.game_state.pot) + \" chips!\"\n self.game_state.player_chips[winner.name] += self.game_state.pot","def get_winners(self):\n\n if self.optimal is not None:\n return self.optimal\n clean_proposals = self.cleaner.create_scenarios(self.proposals)\n self.optimal = self.optimizer.optimize(clean_proposals)\n return self.optimal","def min_players(self):\n return 2","def winner(self):\n\n if self.game_ended():\n return self.winning()\n else:\n return 0","def get_winner(self):\n return self.winner","def get_weapon_holding():\n return unrealsdk.GetEngine().GamePlayers[0].Actor.Pawn.Weapon","def winner(self) -> Player:\n return max(self.players, key=lambda player: player.score)","def pull(self):\n chance = np.random.uniform()\n return chance < self.winning_prob","def play_for_dealer(self):\n while self.dealer.sum_cards() < 17:\n self.dealer.hit(self.deck)\n else:\n self.round_winner = True\n self.print_hands()\n self.determine_winner()","def take_wager(self, _amount: int) -> None:\n self._take_wager(self.msg.sender, _amount)","def steer_max(self):\n return self._steer_max","def get_winStrength(self):\n if self.winStrength is None:\n self.calculate_my_win_strength()\n return self.winStrength","def getGrowthrate(self):\n if (self.__owner == 0):\n return 0\n if (self.__mancount == self.getMaxMancount()):\n return 0\n if (self.__mancount > self.getMaxMancount()):\n return -1\n return 1 + self.__mancount/20","def get_max_turn(self):\n return self.__max_turn","def radiant_win(self):\n return self._get(\"radiant_win\")","def choose_winner(): \r\n max_health = Titan.max_health()\r\n winners = tuple((titan.name for titan in Titan.titans if titan.health == max_health))\r\n return winners","def winner(self):\n\n if self.home_score > self.away_score:\n return HOME\n elif self.home_score < self.away_score:\n return VISITOR\n else:\n return TIE","def determine_round_winner(self):\n\n if self.getX() + self.SIZE[0] < 0:\n # point for player two\n return 2\n elif self.getX() > Configuration.windowWidth:\n # point for player one\n return 1","def calculateWinRate():\n times = 10\n winRate = 0.0\n for i in range(times):\n game = Game('user', 6, 6)\n winRate += game.play(5, False, True, False, False)\n winRate = winRate/times\n print \"Winrate:\", winRate","def get_winner(game):\n return game['winner']","def get_winners_of_game(self):\n return self.game_winners","def start_next_round(self) -> 'Round':\n freewin = Player.FREEWIN()\n last_round = self.current_round\n all_players = set(self.players.all())\n all_possible_matchings = set(map(frozenset, itertools.combinations(all_players, r=2)))\n previous_duels = self.duels()\n previous_matchings = set(\n frozenset((duel.player_1, duel.player_2))\n for duel in previous_duels\n )\n\n possible_matchings = all_possible_matchings - previous_matchings\n assert possible_matchings\n\n next_round = Round.objects.create(tournament=self, number=last_round.number + 1)\n\n current_standing = sorted(self.standing, key=lambda p: (p, last_round.get_duel_for_player(p.player).wins_of(p.player)), reverse=True)\n players_to_match = [p.player for p in current_standing] + [freewin] if freewin in all_players else []\n matched_players = set()\n\n while len(players_to_match) > 1:\n player = players_to_match.pop(0)\n for opponent in players_to_match:\n match = frozenset((player, opponent))\n if match in possible_matchings:\n matched_players.add(match)\n players_to_match.remove(opponent)\n break\n else:\n raise AssertionError(f\"No opponent found for {player}\")\n\n assert not players_to_match, f'{players_to_match} have not been matched'\n\n for player_1, player_2 in matched_players:\n assert player_2 not in self.opponents(player_1)\n assert player_1 not in self.opponents(player_2)\n if freewin == player_1:\n player_1, player_2 = player_2, player_1\n player_1_wins = settings.MATCH_WINS_NEEDED\n elif freewin == player_2:\n player_1_wins = settings.MATCH_WINS_NEEDED\n else:\n player_1_wins = 0\n Duel.objects.create(player_1=player_1, player_2=player_2, player_1_wins=player_1_wins, round=next_round)\n\n return next_round","def calculate_my_win_strength(self):\n self.winStrength = self.strategy(deepcopy(self.currentBoardState))","def miner_pick(self):\n return build_weapon(PICK, self)","def play_blackjack(wager, max_wager):\n game = BlackJack(wager=wager, max_wager=max_wager, allow_split=True, allow_dd=True)\n player = game.players[0]\n print('\\nYour Hand %s has %s points. Your wager is: %d' % (player['hand'], game.player_hand_value(), player['wager']))\n print(\"Dealer's upcard is: \", game.get_dealer_upcard())\n if not game.verify_blackjack():\n req_split = input('\\nWould you like to Split (Y/N)? ').upper()\n if req_split == 'Y':\n if game.split(): # Split\n print('Your hand has been split. You will play one Hand at a time.', end='\\n\\n')\n else:\n print(\"Looks like you don't have enough credits to split. Playing the round without the split\")\n for hand_idx in range(len(game.players)):\n if hand_idx == 1:\n print('\\nNow, Play your Second (Split) Hand. Results will be shown at the end')\n player = game.players[hand_idx]\n while True and player['active']:\n print('Your hand %s has %s points.' % (player['hand'], game.player_hand_value(hand_idx)))\n action = get_player_input(player['allow_dd'])\n if action == 1: # Hit\n game.hit(hand_idx)\n elif action == 2: # Stand. Round Ends when Player Chooses to Stand\n game.stand(hand_idx)\n elif action == 3: # Double down\n game.double_down(hand_idx)\n results = []\n print('\\nRound Results:')\n print('-' * 13)\n for hand_idx in range(len(game.players)):\n print('Your Hand %s with %s points. Your wager was %d' % (player['hand'], game.player_hand_value(hand_idx), player['wager']))\n print(\"Dealer's Final Hand %s is of value %d\" % (game.dealer_hand, game.dealer_hand_value()))\n print('Result: ', game.players[hand_idx]['result'])\n results.append(game.players[hand_idx]['result'])\n return results, game.wager_earned","def get_winner(self):\n return self._winner","def get_winner(self):\n return self._winner","def max(self) -> int:\n return self._status['party_size'][1]","def adaptive_limit(self) -> int:\n return pulumi.get(self, \"adaptive_limit\")","def __init__(self, wager=1, max_wager=1, dealer_min=17, allow_soft_limit=True, allow_split=True, allow_dd=True, allow_dd_after_split=True):\n self.max_wager = max_wager\n self.dealer_min = dealer_min\n self.allow_soft_limit = allow_soft_limit\n self.allow_split = allow_split\n self.allow_dd_after_split = allow_dd_after_split # Allow Double Down after Split\n self.card_suits = ['Spade', 'Heart', 'Diamond', 'Club']\n self.card_faces = {str(numb): numb for numb in range(2, 11)}\n for face in ('jack', 'king', 'queen'):\n self.card_faces[face] = 10\n self.card_faces['ace'] = 11\n # Set the player hand, Dealer hand\n self.players = [] # Assume One Player Hand (No Split)\n self.players.append(self._init_player(wager, allow_dd))\n self.dealer_hand = []\n self.wager_earned = 0\n self.card_deck = [(face, suit) for suit in self.card_suits for face in self.card_faces.keys()]\n random.shuffle(self.card_deck) # Shuffle the card deck\n # Draw two cards for Player and Dealer\n self.players[0]['hand'].append(self._pick_card())\n self.players[0]['hand'].append(self._pick_card())\n self.dealer_hand.append(self._pick_card())\n self.dealer_hand.append(self._pick_card())\n self.verify_blackjack() # Verify if hand has hit a blackjack\n return None","def winner(self):\n raise NotImplementedError","def winner(self):\n raise NotImplementedError","def round_next(cls):\n if cls.is_finished():\n logging.error('Grand challenge finished.')\n return None\n\n round = cls.get_current_round()\n cls.force_round_close(round)\n\n challenges = []\n if cls.is_final():\n # Only two players left in the game\n arb_win = cls.eligible(0)\n arb_lose = cls.eligible(1)\n challenges.append(GrandChallenge.create(arb_win[0], arb_lose[0], round.round_number + 1))\n else:\n # More than two players, create new challenges\n if round.round_number % 2 == 1:\n challenges += cls.play_round(1, round.round_number + 1)\n challenges += cls.play_round(0, round.round_number + 1)\n else:\n challenges += cls.play_round(1, round.round_number + 1)\n\n if challenges:\n # Update round number\n round.round_number += 1\n cls.set_current_round(round.round_number)\n logging.debug('Played round %s' % round.round_number)\n return round","def get_excess(self) -> int:\n excess_to_min_treasury = self._treasury_balance.get() - self._treasury_min.get()\n auth_score = self.create_interface_score(self._game_auth_score.get(), AuthInterface)\n if not self._excess_smoothing_live.get():\n return excess_to_min_treasury - auth_score.get_excess()\n else:\n third_party_games_excess: int = 0\n games_excess = auth_score.get_todays_games_excess()\n for game in games_excess:\n third_party_games_excess += max(0, int(games_excess[game]))\n reward_pool = excess_to_min_treasury - third_party_games_excess * 20 // 100\n return reward_pool","def get_pile():\n global piles\n global num_piles\n\n while True:\n userInput = int(input(\"Which pile? \"))\n if userInput >= 0 and userInput <= num_piles-1:\n return userInput\n break","def pick_winner(self):\r\n self.convert_face_cards_to_numbers()\r\n main_suit = self.cards_int[0][0] # suit that dominates this round\r\n winner_index = 0 # by default 1st player wins until we find a bigger card in same suit\r\n winner_card_value = self.cards_int[0][1]\r\n for index, card in enumerate(self.cards_int[1:]):\r\n if main_suit == card[0]:\r\n if winner_card_value < card[1]:\r\n winner_index = index+1\r\n winner_card_value = card[1]\r\n\r\n return winner_index","def attack(self):\n # TODO: Use integer division to find half of the max_damage value\n # then return a random integer between\n # half of max_damage and max_damage\n print(\"max damage of \" + self.name + \" is \")\n print(str(self.attack_strength))\n min_damage = self.attack_strength // 2\n weapon_attack_value = random.randint(min_damage, self.attack_strength)\n return weapon_attack_value","def get_next_player(self, player):\r\n return player * -1","def get_next_player(self, player):\r\n return player * -1","def choose_move(self): # pylint: disable=too-many-branches,too-many-return-statements\n if self.current_mana < 10: # Only usable move\n return self.moves.teleport\n\n if self.game.player.current_hp <= 10 and self.current_mana >= self.moves.claw.mana_cost:\n return self.moves.claw\n if self.game.player.current_hp <= 20:\n return self.moves.glide\n if self.game.player.current_hp <= 30:\n if self.current_mana < 50:\n options = {self.moves.teleport: 3, self.moves.glide: 6}\n elif self.current_mana <= 140:\n options = {self.moves.teleport: 1, self.moves.glide: 2, self.moves.claw: 6}\n else:\n options = {self.moves.glide: 2.3333333333, self.moves.claw: 6.6666666667}\n if self.current_hp <= 180:\n options[self.moves.heal] = 1\n return self.random_weighted(options)\n\n if self.current_hp < 25:\n if self.current_mana < 50:\n return self.random_weighted({self.moves.teleport: 0.1, self.moves.glide: 0.1, self.moves.heal: 0.8})\n if self.game.player.current_hp <= 40:\n return random.choice([self.moves.claw, self.moves.heal])\n\n if random.random() < 0.1:\n return random.choice(self.attack_options())\n return self.moves.heal\n\n options = self.attack_options()\n if self.current_hp <= 0.9*self.max_hp:\n options.append(self.moves.heal)\n return random.choice(options)","def get_lift_limit(self) -> float:\n\n return self.send(self.cmd.GET_LIFT_LIMIT)","def pull_arm(self):\n\n if self.t < self.n_arms:\n return self.t\n # Select arm that maximizes the expected reward\n idxs = np.argwhere(self.expected_rewards == self.expected_rewards.max()).reshape(-1)\n # As we could have multiple indexes, we randomly select one of the index that maximizes the expected reward\n chosen_pulled_arm = np.random.choice(idxs)\n return chosen_pulled_arm","def get_additional_ball_capacity(cls):\n return 999","def stand(self, hand_idx=0):\n dealer_value = self.dealer_hand_value()\n # Dealer has to hit until it's atleast Dealer Min (Default 17)\n while dealer_value < self.dealer_min:\n self.dealer_hand.append(self._pick_card())\n dealer_value = self.dealer_hand_value()\n #Compute Player Hand value\n player = self.players[hand_idx]\n player_value = self.player_hand_value(hand_idx)\n if player['active']:\n # When Player has Blackjack in 2 cards and dealer doesn't\n if player_value == 21 and len(player['hand']) == 2 and \\\n (dealer_value != 21 or (dealer_value == 21 and len(self.dealer_hand) > 2)):\n player['result'] = 'blackjack'\n self.wager_earned += 1.5 * player['wager']\n # When Both Player and Dealer values are equal or both are Bust, then \"Push\".\n elif player_value == dealer_value or (player_value > 21 and dealer_value > 21):\n player['result'] = 'push'\n # When Only Player is Bust, then \"Bust\". You lost the wager\n elif player_value > 21:\n player['result'] = 'bust'\n self.wager_earned -= player['wager']\n # When Only Dealer is Bust, then \"Won\". You won the wager\n elif dealer_value > 21:\n player['result'] = 'won'\n self.wager_earned += player['wager']\n # When both Player and delaer are not bust and Player has higher number than Dealer\n elif player_value > dealer_value:\n player['result'] = 'won'\n self.wager_earned += player['wager']\n # When both Player and delaer are not bust and Player has lower number than Dealer\n elif dealer_value > player_value:\n player['result'] = 'lost'\n self.wager_earned -= player['wager']\n player['active'] = False # Set Player Hand Active to False after a Stand\n return None","def calculate_max_win_strength(self):\n if not len(self.children):\n self.maxWinStrength = self.get_winStrength()\n else:\n maxStrength = max([child.get_max_win_strength() for child in self.children])\n self.maxWinStrength = maxStrength","def get_winner(self) -> int:\n return self._win_state","def get_min_takeover(cell: Cell) -> int:\n if cell.creature == 'humans':\n return math.ceil(cell.number * parameters.HUMANS_TAKEOVER_FACTOR)\n return math.ceil(cell.number * parameters.OPPONENT_TAKEOVER_FACTOR)","def get_additional_ball_capacity(self):\n return 999","def predict_winner(self):\n\t\tif len(self.players) > 1:\n\t\t\t# TODO: convert to using of max() function\n\t\t\twinner = self.players[0]\n\t\t\tfor player in self.players:\n\t\t\t\tif player.wr > winner.wr:\n\t\t\t\t\twinner = player\n\t\t\treturn winner\n\t\telse:\n\t\t\treturn None","def default_gamepoint_transfer_unit(declarer_won: bool, multiplier: int, bid: int, declarer_cards_won: int,\n minimum_bid) -> int:\n if declarer_won:\n return multiplier * ((declarer_cards_won - bid) + (bid - minimum_bid) * 2)\n else:\n return multiplier * (bid - declarer_cards_won)","def utility(self, state):\n \n if state.cachedWin and state.cachedWinner:\n return 10000\n elif state.cachedWin and not state.cachedWinner:\n return -10000\n else:\n return 0","def get_w():\r\n \r\n w = int(input(\"Enter the value of w (1-4): \"))\r\n while w < 1 or w > 4:\r\n print(\"Invalid input! Try again\")\r\n w = int(input(\"Enter the value of w (1-4): \"))\r\n \r\n return w","def assign_upLimit():\r\n player.rect.y = 25","def _game_winner(self):\n return self._env.get_winner()","def max_players(self):\n return self._max_players","def playerForfeit(self):\n self.handleWin(self.currentplayer*-1)","def enough_players():\n return True","def decide_winner(user, dealer):\n print(f\"\\n=============== END OF ROUND ===============\\n\\n\"\n f\"This round, your total hand is {user.total} and the dealer's total hand is {dealer.total}\")\n if bust(dealer):\n return \"user\"\n if bust(user):\n return \"dealer\"\n if user.total > dealer.total:\n return \"user\"\n if user.total < dealer.total:\n return \"dealer\"\n else: # tie\n return \"draw\"","def punch(self):\n # you are not working, futher investagtion needed...\n if self.weight < 5:\n return \"That tickles.\"\n elif self.weight < 15:\n return \"Hey that hurt!\"\n else:\n return \"OUCH!\"","def get_best_time():\n\n # Always remember about db.session.rollback() when debugging\n\n max_timing = db.session.query(func.min(Game.timing)).filter(Game.status == \"won\").first()\n time_user = db.session.query(Game.timing, User.username).join(User).filter(Game.timing == max_timing, Game.status == \"won\").first()\n\n return time_user","def winning_game_player(players):\n\n # in order for there to be a winner, the game must\n # be over\n if not game_over(players):\n return None\n\n # if the game is over, it could be that there is no\n # winner\n active_players = players_with_decks(players)\n if not active_players:\n return False\n\n # if the game is over than find the winner\n return players_with_decks(players)[0]","def getWinner (self):\r\n\t\tlines = (\r\n\t\t\tself.board, # columns\r\n\t\t\tzip(*self.board), # rows\r\n\t\t\tBoard.diagonalsPos(self.board, self.cols, self.rows),\r\n\t\t\tBoard.diagonalsNeg(self.board, self.cols, self.rows) \r\n\t\t)\r\n\r\n\t\tfor line in chain(*lines):\r\n\t\t\tfor figure, group in groupby(line):\r\n\t\t\t\tif figure != NONE and len(list(group)) >= self.win:\r\n\t\t\t\t\treturn figure","def _adv_counter(winrate_together, winrate_hero1, winrate_hero2):\n return winrate_together","def get_next_match_prefer_unfair_matches(population):\n win_player = None\n loss_player = None\n for player in population:\n if len(player.record) == 1:\n if player.record[0] == \"W\":\n win_player = player\n elif player.record[0] == \"L\":\n loss_player = player\n if win_player and loss_player:\n return win_player, loss_player\n # if we can't find an unfair match, just pick the first available\n return get_next_match_pick_first_available(population)","def play(self):\n while True:\n self.round()\n if not(self.player.playing) and (self.dealer.value >= 17):\n break\n self.update_state()\n return self.end_game()","def player_stand(self):\r\n if self.in_progress:\r\n while self.dealer_hand.total < 17:\r\n self.dealer_hand.add(self.deck.deal())\r\n if self.dealer_hand.total > 21 or self.dealer_hand.total < self.player_hand.total:\r\n self.status_color = 'red'\r\n self.game_status = \"Player WINS... Press 'r' to start game\"\r\n self.player_wins += 1\r\n elif self.player_hand.total == self.dealer_hand.total:\r\n self.status_color = 'red'\r\n self.game_status = \"TIE Game... Press 'r' to start game\"\r\n else:\r\n self.status_color = 'red'\r\n self.game_status = \"Dealer WINS... Press 'r' to start game\"\r\n self.dealer_wins += 1\r\n self.in_progress = False\r\n self.refresh_canvas()","def won(self):\n return self.roster.won","def Pwin(state):\n # Assumes opponent also plays with optimal strategy\n p, me, you, pending = state\n if me + pending >= goal:\n return 1\n elif you >= goal:\n return 0\n else:\n return max(Q_pig(state, action, Pwin) for action in pig_actions(state))","def player_win(self):\n global chips\n global placed_bet\n\n chips = (self.final_bet*2 + chips)\n self.victory = True\n placed_bet = False","def pick_steal_target(self, callback=None):\n players_copy = copy.copy(self.game.players)\n players_copy.remove(self) # don't pick yourself!\n wealthy_player = max(self.game.players, key=lambda x: x.coins)\n callback(wealthy_player)","def user_pick(self):\n player_taking = True\n while player_taking:\n play_take = int(input(\"How many dots would you like to remove?(1-4)\"))\n if not 1 <= play_take <= 4:\n print(\"You may only take between 1 and 4 balls\")\n else:\n player_taking = False\n return play_take","def winner(self):\n state = self._state['visible']\n if state['reserve'][0] < 1:\n return 1\n elif state['reserve'][1] < 1:\n return 0\n return -1","def get_max_readings( self ):\n return 2500","def _get_next_limit(self):\n return self.__quota","async def evaluate(self):\n if self.players[1].id == bot.user.id:\n self.p2_move = random.choice((\"Rock\", \"Paper\", \"Scissors\"))\n\n if None in self.moves:\n return\n\n if len(self.moves) == 1:\n tie_embed = discord.Embed(title=\"It's a Draw\")\n await self.channel.send(embed=tie_embed)\n return await self.end()\n\n if self.moves == {\"Rock\", \"Paper\"}:\n winner = \"Paper\"\n elif self.moves == {\"Scissors\", \"Paper\"}:\n winner = \"Scissors\"\n elif self.moves == {\"Rock\", \"Scissors\"}:\n winner = \"Rock\"\n\n # P1 Wins\n if self.p1_move == winner:\n embed = discord.Embed(\n title=f\"{self.players[0].name}'s **{winner}** beats {self.players[1].name}'s **{self.p2_move}**\")\n await self.channel.send(embed=embed)\n await self.end(winner=self.players[0])\n\n # P2 Wins\n elif self.p2_move == winner:\n embed = discord.Embed(\n title=f\"{self.players[1].name}'s **{winner}** beats {self.players[0].name}'s **{self.p1_move}**\")\n await self.channel.send(embed=embed)\n await self.end(winner=self.players[1])","def winFor(self,player):\n if(self.cachedWin == False):\n won = False;\n if(player==WHITE):\n for x in range(0,WIDTH):\n if(self.gameState[x,0]==WHITE):\n won = True\n \n elif(player==BLACK):\n for x in range(0,WIDTH):\n if(self.gameState[x,HEIGHT-1]==BLACK):\n won = True\n \n if(len(self.successors()) == 0):#IF there are no available moves for both players\n bCount = self.count(BLACK) #check who has the most pawns\n wCount = self.count(BLACK)\n if(bCount>wCount):\n self.cachedWin = True\n self.cachedWinner = player\n return True\n if(wCount>bCount):\n self.cachedWin = True\n self.cachedWinner = player\n return True\n \n if(won):\n self.cachedWin = True\n self.cachedWinner = player\n return True\n else:\n return False\n else:\n return player == self.cachedWinner","def _take_wager(self, _game_address: Address, _amount: int) -> None:\n if _amount <= 0:\n revert(f\"Invalid bet amount {_amount}\")\n auth_score = self.create_interface_score(self._game_auth_score.get(), AuthInterface)\n if auth_score.get_game_status(_game_address) != \"gameApproved\":\n revert(f'Bet only accepted through approved games.')\n if self.__day_advanced():\n self.__check_for_dividends()\n self._daily_bet_count.set(self._daily_bet_count.get() + 1)\n auth_score.accumulate_daily_wagers(_game_address, _amount)\n Logger.debug(f'Sending wager data to rewards score.', TAG)\n rewards_score = self.create_interface_score(self._rewards_score.get(), RewardsInterface)\n rewards_score.accumulate_wagers(str(self.tx.origin), _amount, (self._day.get() - self._skipped_days.get()) % 2)\n self._treasury_balance.set(self.icx.get_balance(self.address))","def round_advance(self):\n\n\t\t# takes current round and advances it by one.\n\t\tif self.model.status <= 9:\n\t\t\t\n\t\t\tself.model.status += 1","def get_winners():\r\n\r\n numbers = []\r\n\r\n # Randomly get 5 winning numbers\r\n for i in range(0, 5):\r\n if not numbers:\r\n number = random.randrange(1, 71)\r\n while number > 25:\r\n number = random.randrange(1, 71)\r\n else:\r\n numbers.append(number)\r\n else:\r\n numbers.append(random.randrange(numbers[i - 1], 71))\r\n\r\n # Randomly get multiplying ball\r\n numbers.append(random.randrange(1, 25))\r\n\r\n return numbers","def heavy_rollout(self, game):\n game = game.copy()\n while True:\n moves = game.get_legal_moves()\n if not moves:\n break\n scores = [(self.score(game.forecast_move(m), game.active_player), m) for m in moves]\n _, best = max(scores, key=lambda x: x[0])\n game.apply_move(best)\n return game","def _adv_synergy(winrate_together, winrate_hero1, winrate_hero2):\n return winrate_together","def get_wins_overall(self, uuid):\n\n return self.template(uuid, \"wins\")"],"string":"[\n \"def round_based_alien_limitation(self):\\n if self.num_round < 5:\\n return 1\\n elif self.num_round < 10:\\n return 2\\n else:\\n return 3\",\n \"def take(self, desired_amount):\\n if self.amount >= desired_amount:\\n grab = desired_amount\\n else:\\n grab = min(desired_amount, self.amount)\\n self.amount -= grab\\n print(f\\\"{self} {self.amount} of supplies left\\\")\\n return grab\",\n \"def determine_win(self):\\n if self.match.radiant_win is True and self.player_slot < 5:\\n return True\\n if self.match.radiant_win is False and self.player_slot > 5:\\n return True\\n return False\",\n \"def who_won(self):\\n if self.dealer.hand.value > 21:\\n dealer_busts(self.pot)\\n self.player.get_money(self.pot)\\n elif self.dealer.hand.value > self.player.hand.value:\\n dealer_win(self.dealer.hand, self.player.hand, self.pot)\\n self.player.pay_out(self.pot)\\n elif self.dealer.hand.value == self.player.hand.value:\\n push(self.dealer.hand.value, self.player.hand.value)\\n else:\\n player_win_text(self.pot)\\n self.player.get_money(self.pot)\",\n \"def STAND_LIMIT() -> int:\\n return 15\",\n \"def round(self):\\n #player turn\\n if self.started:\\n self.started = False #registers the game as started then immediately turns that value false\\n if self.initial_action:\\n card = self.deck.deal()\\n self.player.value += card.value\\n if card.is_ace:\\n self.player.usable_ace = True\\n else:\\n self.player.playing = False\\n else: \\n if self.apply_policy():\\n card = self.deck.deal()\\n self.player.value += card.value\\n if card.is_ace:\\n self.player.usable_ace = True\\n else:\\n self.player.playing = False\\n\\n #dealer turn\\n if self.dealer.value < 17:\\n card = self.deck.deal()\\n self.dealer.value += card.value\\n self.dealer.visible_value += card.value\\n #allow people to reduce their scores by applying aces\\n self.apply_ace()\\n #check to see if anyone has bust by making bust people not _playing\\n if self.player.value > 21:\\n self.player.broke = True\\n self.player.playing = False\\n if self.dealer.value > 21:\\n self.dealer.broke = True\",\n \"def get_max_win_strength(self):\\n if self.maxWinStrength is None:\\n self.calculate_max_win_strength()\\n return self.maxWinStrength\",\n \"def reward(self, winner):\\n if winner == self.side:\\n return self.win\\n elif winner == VALUES.NOT_FINISHED:\\n return self.not_finished\\n elif winner == VALUES.DRAW:\\n return self.draw\\n else:\\n return self.lose\",\n \"def get_winner(self) -> None:\\n if not self.get_game_ending_hands():\\n if max(self.user.hand.value) > max(self.house.hand.value): # Values above 21 are omitted\\n self.event_player_wins()\\n elif max(self.user.hand.value) == max(self.house.hand.value):\\n self.event_player_push()\\n else:\\n self.event_house_wins()\",\n \"def calc_winner(self):\\n pass\",\n \"def WIN_BONUS() -> int:\\n return 2\",\n \"def evaluateWinner(self):\\n\\t\\tif self.pots[-1] == 0:\\n\\t\\t\\tself.pots.pop()\\n\\t\\tlivePlayers = self.getLivePlayers()\\t\\n\\t\\tfor i in range(len(self.pots)):\\n\\t\\t\\tplayers = self.getPlayersInPot(i, livePlayers)\\n\\t\\t\\tevaluations = []\\n\\t\\t\\tfor x in players:\\n\\t\\t\\t\\tcombined = x.hand + self.communityCards\\n\\t\\t\\t\\tevaluations.append((x, self.evaluator.getRankOfSeven(\\tcombined[0], \\\\\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tcombined[1], \\\\\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tcombined[2], \\\\\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tcombined[3], \\\\\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tcombined[4], \\\\\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tcombined[5], \\\\\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tcombined[6] )))\\n\\t\\t\\twinners = self.getWinners(evaluations, i)\\n\\t\\t\\tself.handOutMoney(winners, i)\\n\\t\\t\\tself.potwinQ.append(winners[0].name)\",\n \"def next_choice(self, opponent: 'Player') -> str:\\n\\n if self.adaptive_ai:\\n # this is an adaptive_ai player, so see if it has collected\\n # enough stats about the current opponent yet:\\n if sum(self.opponent_choices[opponent.name].values()) > 5:\\n # has enough samples to start adapting to the opponent\\n print(' {} is trying to guess the opponent\\\\'s choice...'.format(self.name))\\n\\n # AI algorithm 1:\\n # simply find the most-frequent selection by the opponent and\\n # choose its killer.\\n\\n guess = self.opponent_choices[opponent.name].most_common(1)[0][0]\\n ai_choice = weapon_to_beat(guess)\\n print(' ', opponent.name, 'most often chose', guess, 'so he/she chose', ai_choice)\\n return ai_choice\\n\\n # use the standard tendency distribution to choose a weapon:\\n n = randint(1, self.randmax)\\n if n <= self.tendency[0]:\\n return 'rock'\\n elif n <= self.tendency[0] + self.tendency[1]:\\n return 'paper'\\n else:\\n return 'scissors'\",\n \"def select_win_game(self):\\r\\n win_game_anims =['anim_speedtap_winround_intensity01_01',\\r\\n 'anim_speedtap_winround_intensity02_02',\\r\\n 'anim_speedtap_winround_intensity02_01',\\r\\n 'anim_speedtap_wingame_intensity02_01',\\r\\n 'anim_speedtap_wingame_intensity02_02',\\r\\n 'anim_speedtap_wingame_intensity03_01']\\r\\n cozmo.logger.info(\\\"Cozmo win game reacion\\\")\\r\\n return win_game_anims[randint(0,5)]\",\n \"def who_won(self):\\n if self.scoreB >= WP: return Stone.BLACK\\n if self.scoreW >= WP: return Stone.WHITE\\n return self.last\",\n \"def most_powerful_weapon(self):\\n # sets inital damge to 0\\n max_damage = 0\\n # sets the best weapon to nothing\\n best_weapon = None\\n # Loop for each item in inventory\\n for item in self.inventory:\\n # Code adapted from Make Your own Python Text Based Adventure\\n # tries to see if the item damage is greator than the current max\\n # damage and then replaces the best weapon in inventory\\n try:\\n if item.damage > max_damage:\\n best_weapon = item\\n max_damage = item.damage\\n except AttributeError:\\n pass\\n # sends the best weapon to function\\n return best_weapon\",\n \"def play_war_round(player):\\n for i in xrange(4):\\n play_normal_round(player)\\n\\n return player\",\n \"def get_winner(self):\\n winner: Player = Player('none')\\n points_winner = 0\\n for player in self.players:\\n for key, value in player.get_stats().items():\\n print('{}: {}'.format(key, value))\\n if key == 'points':\\n if value >= points_winner:\\n winner = player\\n print()\\n\\n print('The winner is: ' + winner.get_name())\\n return winner\",\n \"def determineWinner(self):\\n if self.game_state.numActive() == 1:\\n for player in self.game_state.player_list:\\n if self.game_state.active_dict[player.name]:\\n print \\\"\\\"\\n print player.name + \\\" wins with\\\"\\n for card in self.player_hand_dict[player.name]:\\n print card\\n print \\\"and takes \\\" + str(self.game_state.pot) + \\\" chips!\\\"\\n self.game_state.player_chips[player.name] += self.game_state.pot\\n return\\n\\n for player in self.game_state.player_list:\\n for card in self.game_state.board:\\n self.player_hand_dict[player.name].append(Card(card.suit, card.rank))\\n hand_ranking = HandRanking(self.game_state.player_list, self.player_hand_dict)\\n hand_ranking.rankHands()\\n winning_rank = -1\\n winner = None\\n tie_list = []\\n \\\"\\\"\\\" Get winning rank, only consider active players for the pot \\\"\\\"\\\"\\n for player in self.game_state.player_list:\\n if self.game_state.active_dict[player.name] == True:\\n if DEBUG:\\n print \\\"Considering \\\" + str(player.name) + \\\"'s hand for the pot.\\\"\\n if hand_ranking.player_ranks_dict[player.name] > winning_rank:\\n winning_rank = hand_ranking.player_ranks_dict[player.name]\\n winner = player \\n tie_list = []\\n tie_list.append(player)\\n elif hand_ranking.player_ranks_dict[player.name] == winning_rank:\\n tie_list.append(player)\\n \\\"\\\"\\\" winner should never be equal to None \\\"\\\"\\\"\\n\\n \\\"\\\"\\\" Check for tie and resolve if needed \\\"\\\"\\\"\\n if len(tie_list) > 1:\\n if DEBUG:\\n print \\\"found potential tie...\\\"\\n for player in tie_list:\\n print player.name + \\\"'s hand:\\\"\\n for card in hand_ranking.player_best_hand_dict[player.name]:\\n print card\\n print \\\"resolving tie...\\\"\\n result_tie_list = self.resolveTie(hand_ranking, tie_list)\\n print \\\"\\\"\\n self.printPlayersHands()\\n for player in result_tie_list:\\n print player.name + \\\",\\\",\\n print \\\" wins with\\\",\\n hand_ranking.printRanking(winning_rank)\\n print \\\"and takes \\\" + str(self.game_state.pot / len(tie_list)) + \\\" chips!\\\"\\n for player in result_tie_list:\\n self.game_state.player_chips[player.name] += self.game_state.pot / len(tie_list)\\n else:\\n print \\\"\\\"\\n self.printPlayersHands()\\n print winner.name + \\\" wins with\\\",\\n hand_ranking.printRanking(winning_rank)\\n print \\\"and takes \\\" + str(self.game_state.pot) + \\\" chips!\\\"\\n self.game_state.player_chips[winner.name] += self.game_state.pot\",\n \"def get_winners(self):\\n\\n if self.optimal is not None:\\n return self.optimal\\n clean_proposals = self.cleaner.create_scenarios(self.proposals)\\n self.optimal = self.optimizer.optimize(clean_proposals)\\n return self.optimal\",\n \"def min_players(self):\\n return 2\",\n \"def winner(self):\\n\\n if self.game_ended():\\n return self.winning()\\n else:\\n return 0\",\n \"def get_winner(self):\\n return self.winner\",\n \"def get_weapon_holding():\\n return unrealsdk.GetEngine().GamePlayers[0].Actor.Pawn.Weapon\",\n \"def winner(self) -> Player:\\n return max(self.players, key=lambda player: player.score)\",\n \"def pull(self):\\n chance = np.random.uniform()\\n return chance < self.winning_prob\",\n \"def play_for_dealer(self):\\n while self.dealer.sum_cards() < 17:\\n self.dealer.hit(self.deck)\\n else:\\n self.round_winner = True\\n self.print_hands()\\n self.determine_winner()\",\n \"def take_wager(self, _amount: int) -> None:\\n self._take_wager(self.msg.sender, _amount)\",\n \"def steer_max(self):\\n return self._steer_max\",\n \"def get_winStrength(self):\\n if self.winStrength is None:\\n self.calculate_my_win_strength()\\n return self.winStrength\",\n \"def getGrowthrate(self):\\n if (self.__owner == 0):\\n return 0\\n if (self.__mancount == self.getMaxMancount()):\\n return 0\\n if (self.__mancount > self.getMaxMancount()):\\n return -1\\n return 1 + self.__mancount/20\",\n \"def get_max_turn(self):\\n return self.__max_turn\",\n \"def radiant_win(self):\\n return self._get(\\\"radiant_win\\\")\",\n \"def choose_winner(): \\r\\n max_health = Titan.max_health()\\r\\n winners = tuple((titan.name for titan in Titan.titans if titan.health == max_health))\\r\\n return winners\",\n \"def winner(self):\\n\\n if self.home_score > self.away_score:\\n return HOME\\n elif self.home_score < self.away_score:\\n return VISITOR\\n else:\\n return TIE\",\n \"def determine_round_winner(self):\\n\\n if self.getX() + self.SIZE[0] < 0:\\n # point for player two\\n return 2\\n elif self.getX() > Configuration.windowWidth:\\n # point for player one\\n return 1\",\n \"def calculateWinRate():\\n times = 10\\n winRate = 0.0\\n for i in range(times):\\n game = Game('user', 6, 6)\\n winRate += game.play(5, False, True, False, False)\\n winRate = winRate/times\\n print \\\"Winrate:\\\", winRate\",\n \"def get_winner(game):\\n return game['winner']\",\n \"def get_winners_of_game(self):\\n return self.game_winners\",\n \"def start_next_round(self) -> 'Round':\\n freewin = Player.FREEWIN()\\n last_round = self.current_round\\n all_players = set(self.players.all())\\n all_possible_matchings = set(map(frozenset, itertools.combinations(all_players, r=2)))\\n previous_duels = self.duels()\\n previous_matchings = set(\\n frozenset((duel.player_1, duel.player_2))\\n for duel in previous_duels\\n )\\n\\n possible_matchings = all_possible_matchings - previous_matchings\\n assert possible_matchings\\n\\n next_round = Round.objects.create(tournament=self, number=last_round.number + 1)\\n\\n current_standing = sorted(self.standing, key=lambda p: (p, last_round.get_duel_for_player(p.player).wins_of(p.player)), reverse=True)\\n players_to_match = [p.player for p in current_standing] + [freewin] if freewin in all_players else []\\n matched_players = set()\\n\\n while len(players_to_match) > 1:\\n player = players_to_match.pop(0)\\n for opponent in players_to_match:\\n match = frozenset((player, opponent))\\n if match in possible_matchings:\\n matched_players.add(match)\\n players_to_match.remove(opponent)\\n break\\n else:\\n raise AssertionError(f\\\"No opponent found for {player}\\\")\\n\\n assert not players_to_match, f'{players_to_match} have not been matched'\\n\\n for player_1, player_2 in matched_players:\\n assert player_2 not in self.opponents(player_1)\\n assert player_1 not in self.opponents(player_2)\\n if freewin == player_1:\\n player_1, player_2 = player_2, player_1\\n player_1_wins = settings.MATCH_WINS_NEEDED\\n elif freewin == player_2:\\n player_1_wins = settings.MATCH_WINS_NEEDED\\n else:\\n player_1_wins = 0\\n Duel.objects.create(player_1=player_1, player_2=player_2, player_1_wins=player_1_wins, round=next_round)\\n\\n return next_round\",\n \"def calculate_my_win_strength(self):\\n self.winStrength = self.strategy(deepcopy(self.currentBoardState))\",\n \"def miner_pick(self):\\n return build_weapon(PICK, self)\",\n \"def play_blackjack(wager, max_wager):\\n game = BlackJack(wager=wager, max_wager=max_wager, allow_split=True, allow_dd=True)\\n player = game.players[0]\\n print('\\\\nYour Hand %s has %s points. Your wager is: %d' % (player['hand'], game.player_hand_value(), player['wager']))\\n print(\\\"Dealer's upcard is: \\\", game.get_dealer_upcard())\\n if not game.verify_blackjack():\\n req_split = input('\\\\nWould you like to Split (Y/N)? ').upper()\\n if req_split == 'Y':\\n if game.split(): # Split\\n print('Your hand has been split. You will play one Hand at a time.', end='\\\\n\\\\n')\\n else:\\n print(\\\"Looks like you don't have enough credits to split. Playing the round without the split\\\")\\n for hand_idx in range(len(game.players)):\\n if hand_idx == 1:\\n print('\\\\nNow, Play your Second (Split) Hand. Results will be shown at the end')\\n player = game.players[hand_idx]\\n while True and player['active']:\\n print('Your hand %s has %s points.' % (player['hand'], game.player_hand_value(hand_idx)))\\n action = get_player_input(player['allow_dd'])\\n if action == 1: # Hit\\n game.hit(hand_idx)\\n elif action == 2: # Stand. Round Ends when Player Chooses to Stand\\n game.stand(hand_idx)\\n elif action == 3: # Double down\\n game.double_down(hand_idx)\\n results = []\\n print('\\\\nRound Results:')\\n print('-' * 13)\\n for hand_idx in range(len(game.players)):\\n print('Your Hand %s with %s points. Your wager was %d' % (player['hand'], game.player_hand_value(hand_idx), player['wager']))\\n print(\\\"Dealer's Final Hand %s is of value %d\\\" % (game.dealer_hand, game.dealer_hand_value()))\\n print('Result: ', game.players[hand_idx]['result'])\\n results.append(game.players[hand_idx]['result'])\\n return results, game.wager_earned\",\n \"def get_winner(self):\\n return self._winner\",\n \"def get_winner(self):\\n return self._winner\",\n \"def max(self) -> int:\\n return self._status['party_size'][1]\",\n \"def adaptive_limit(self) -> int:\\n return pulumi.get(self, \\\"adaptive_limit\\\")\",\n \"def __init__(self, wager=1, max_wager=1, dealer_min=17, allow_soft_limit=True, allow_split=True, allow_dd=True, allow_dd_after_split=True):\\n self.max_wager = max_wager\\n self.dealer_min = dealer_min\\n self.allow_soft_limit = allow_soft_limit\\n self.allow_split = allow_split\\n self.allow_dd_after_split = allow_dd_after_split # Allow Double Down after Split\\n self.card_suits = ['Spade', 'Heart', 'Diamond', 'Club']\\n self.card_faces = {str(numb): numb for numb in range(2, 11)}\\n for face in ('jack', 'king', 'queen'):\\n self.card_faces[face] = 10\\n self.card_faces['ace'] = 11\\n # Set the player hand, Dealer hand\\n self.players = [] # Assume One Player Hand (No Split)\\n self.players.append(self._init_player(wager, allow_dd))\\n self.dealer_hand = []\\n self.wager_earned = 0\\n self.card_deck = [(face, suit) for suit in self.card_suits for face in self.card_faces.keys()]\\n random.shuffle(self.card_deck) # Shuffle the card deck\\n # Draw two cards for Player and Dealer\\n self.players[0]['hand'].append(self._pick_card())\\n self.players[0]['hand'].append(self._pick_card())\\n self.dealer_hand.append(self._pick_card())\\n self.dealer_hand.append(self._pick_card())\\n self.verify_blackjack() # Verify if hand has hit a blackjack\\n return None\",\n \"def winner(self):\\n raise NotImplementedError\",\n \"def winner(self):\\n raise NotImplementedError\",\n \"def round_next(cls):\\n if cls.is_finished():\\n logging.error('Grand challenge finished.')\\n return None\\n\\n round = cls.get_current_round()\\n cls.force_round_close(round)\\n\\n challenges = []\\n if cls.is_final():\\n # Only two players left in the game\\n arb_win = cls.eligible(0)\\n arb_lose = cls.eligible(1)\\n challenges.append(GrandChallenge.create(arb_win[0], arb_lose[0], round.round_number + 1))\\n else:\\n # More than two players, create new challenges\\n if round.round_number % 2 == 1:\\n challenges += cls.play_round(1, round.round_number + 1)\\n challenges += cls.play_round(0, round.round_number + 1)\\n else:\\n challenges += cls.play_round(1, round.round_number + 1)\\n\\n if challenges:\\n # Update round number\\n round.round_number += 1\\n cls.set_current_round(round.round_number)\\n logging.debug('Played round %s' % round.round_number)\\n return round\",\n \"def get_excess(self) -> int:\\n excess_to_min_treasury = self._treasury_balance.get() - self._treasury_min.get()\\n auth_score = self.create_interface_score(self._game_auth_score.get(), AuthInterface)\\n if not self._excess_smoothing_live.get():\\n return excess_to_min_treasury - auth_score.get_excess()\\n else:\\n third_party_games_excess: int = 0\\n games_excess = auth_score.get_todays_games_excess()\\n for game in games_excess:\\n third_party_games_excess += max(0, int(games_excess[game]))\\n reward_pool = excess_to_min_treasury - third_party_games_excess * 20 // 100\\n return reward_pool\",\n \"def get_pile():\\n global piles\\n global num_piles\\n\\n while True:\\n userInput = int(input(\\\"Which pile? \\\"))\\n if userInput >= 0 and userInput <= num_piles-1:\\n return userInput\\n break\",\n \"def pick_winner(self):\\r\\n self.convert_face_cards_to_numbers()\\r\\n main_suit = self.cards_int[0][0] # suit that dominates this round\\r\\n winner_index = 0 # by default 1st player wins until we find a bigger card in same suit\\r\\n winner_card_value = self.cards_int[0][1]\\r\\n for index, card in enumerate(self.cards_int[1:]):\\r\\n if main_suit == card[0]:\\r\\n if winner_card_value < card[1]:\\r\\n winner_index = index+1\\r\\n winner_card_value = card[1]\\r\\n\\r\\n return winner_index\",\n \"def attack(self):\\n # TODO: Use integer division to find half of the max_damage value\\n # then return a random integer between\\n # half of max_damage and max_damage\\n print(\\\"max damage of \\\" + self.name + \\\" is \\\")\\n print(str(self.attack_strength))\\n min_damage = self.attack_strength // 2\\n weapon_attack_value = random.randint(min_damage, self.attack_strength)\\n return weapon_attack_value\",\n \"def get_next_player(self, player):\\r\\n return player * -1\",\n \"def get_next_player(self, player):\\r\\n return player * -1\",\n \"def choose_move(self): # pylint: disable=too-many-branches,too-many-return-statements\\n if self.current_mana < 10: # Only usable move\\n return self.moves.teleport\\n\\n if self.game.player.current_hp <= 10 and self.current_mana >= self.moves.claw.mana_cost:\\n return self.moves.claw\\n if self.game.player.current_hp <= 20:\\n return self.moves.glide\\n if self.game.player.current_hp <= 30:\\n if self.current_mana < 50:\\n options = {self.moves.teleport: 3, self.moves.glide: 6}\\n elif self.current_mana <= 140:\\n options = {self.moves.teleport: 1, self.moves.glide: 2, self.moves.claw: 6}\\n else:\\n options = {self.moves.glide: 2.3333333333, self.moves.claw: 6.6666666667}\\n if self.current_hp <= 180:\\n options[self.moves.heal] = 1\\n return self.random_weighted(options)\\n\\n if self.current_hp < 25:\\n if self.current_mana < 50:\\n return self.random_weighted({self.moves.teleport: 0.1, self.moves.glide: 0.1, self.moves.heal: 0.8})\\n if self.game.player.current_hp <= 40:\\n return random.choice([self.moves.claw, self.moves.heal])\\n\\n if random.random() < 0.1:\\n return random.choice(self.attack_options())\\n return self.moves.heal\\n\\n options = self.attack_options()\\n if self.current_hp <= 0.9*self.max_hp:\\n options.append(self.moves.heal)\\n return random.choice(options)\",\n \"def get_lift_limit(self) -> float:\\n\\n return self.send(self.cmd.GET_LIFT_LIMIT)\",\n \"def pull_arm(self):\\n\\n if self.t < self.n_arms:\\n return self.t\\n # Select arm that maximizes the expected reward\\n idxs = np.argwhere(self.expected_rewards == self.expected_rewards.max()).reshape(-1)\\n # As we could have multiple indexes, we randomly select one of the index that maximizes the expected reward\\n chosen_pulled_arm = np.random.choice(idxs)\\n return chosen_pulled_arm\",\n \"def get_additional_ball_capacity(cls):\\n return 999\",\n \"def stand(self, hand_idx=0):\\n dealer_value = self.dealer_hand_value()\\n # Dealer has to hit until it's atleast Dealer Min (Default 17)\\n while dealer_value < self.dealer_min:\\n self.dealer_hand.append(self._pick_card())\\n dealer_value = self.dealer_hand_value()\\n #Compute Player Hand value\\n player = self.players[hand_idx]\\n player_value = self.player_hand_value(hand_idx)\\n if player['active']:\\n # When Player has Blackjack in 2 cards and dealer doesn't\\n if player_value == 21 and len(player['hand']) == 2 and \\\\\\n (dealer_value != 21 or (dealer_value == 21 and len(self.dealer_hand) > 2)):\\n player['result'] = 'blackjack'\\n self.wager_earned += 1.5 * player['wager']\\n # When Both Player and Dealer values are equal or both are Bust, then \\\"Push\\\".\\n elif player_value == dealer_value or (player_value > 21 and dealer_value > 21):\\n player['result'] = 'push'\\n # When Only Player is Bust, then \\\"Bust\\\". You lost the wager\\n elif player_value > 21:\\n player['result'] = 'bust'\\n self.wager_earned -= player['wager']\\n # When Only Dealer is Bust, then \\\"Won\\\". You won the wager\\n elif dealer_value > 21:\\n player['result'] = 'won'\\n self.wager_earned += player['wager']\\n # When both Player and delaer are not bust and Player has higher number than Dealer\\n elif player_value > dealer_value:\\n player['result'] = 'won'\\n self.wager_earned += player['wager']\\n # When both Player and delaer are not bust and Player has lower number than Dealer\\n elif dealer_value > player_value:\\n player['result'] = 'lost'\\n self.wager_earned -= player['wager']\\n player['active'] = False # Set Player Hand Active to False after a Stand\\n return None\",\n \"def calculate_max_win_strength(self):\\n if not len(self.children):\\n self.maxWinStrength = self.get_winStrength()\\n else:\\n maxStrength = max([child.get_max_win_strength() for child in self.children])\\n self.maxWinStrength = maxStrength\",\n \"def get_winner(self) -> int:\\n return self._win_state\",\n \"def get_min_takeover(cell: Cell) -> int:\\n if cell.creature == 'humans':\\n return math.ceil(cell.number * parameters.HUMANS_TAKEOVER_FACTOR)\\n return math.ceil(cell.number * parameters.OPPONENT_TAKEOVER_FACTOR)\",\n \"def get_additional_ball_capacity(self):\\n return 999\",\n \"def predict_winner(self):\\n\\t\\tif len(self.players) > 1:\\n\\t\\t\\t# TODO: convert to using of max() function\\n\\t\\t\\twinner = self.players[0]\\n\\t\\t\\tfor player in self.players:\\n\\t\\t\\t\\tif player.wr > winner.wr:\\n\\t\\t\\t\\t\\twinner = player\\n\\t\\t\\treturn winner\\n\\t\\telse:\\n\\t\\t\\treturn None\",\n \"def default_gamepoint_transfer_unit(declarer_won: bool, multiplier: int, bid: int, declarer_cards_won: int,\\n minimum_bid) -> int:\\n if declarer_won:\\n return multiplier * ((declarer_cards_won - bid) + (bid - minimum_bid) * 2)\\n else:\\n return multiplier * (bid - declarer_cards_won)\",\n \"def utility(self, state):\\n \\n if state.cachedWin and state.cachedWinner:\\n return 10000\\n elif state.cachedWin and not state.cachedWinner:\\n return -10000\\n else:\\n return 0\",\n \"def get_w():\\r\\n \\r\\n w = int(input(\\\"Enter the value of w (1-4): \\\"))\\r\\n while w < 1 or w > 4:\\r\\n print(\\\"Invalid input! Try again\\\")\\r\\n w = int(input(\\\"Enter the value of w (1-4): \\\"))\\r\\n \\r\\n return w\",\n \"def assign_upLimit():\\r\\n player.rect.y = 25\",\n \"def _game_winner(self):\\n return self._env.get_winner()\",\n \"def max_players(self):\\n return self._max_players\",\n \"def playerForfeit(self):\\n self.handleWin(self.currentplayer*-1)\",\n \"def enough_players():\\n return True\",\n \"def decide_winner(user, dealer):\\n print(f\\\"\\\\n=============== END OF ROUND ===============\\\\n\\\\n\\\"\\n f\\\"This round, your total hand is {user.total} and the dealer's total hand is {dealer.total}\\\")\\n if bust(dealer):\\n return \\\"user\\\"\\n if bust(user):\\n return \\\"dealer\\\"\\n if user.total > dealer.total:\\n return \\\"user\\\"\\n if user.total < dealer.total:\\n return \\\"dealer\\\"\\n else: # tie\\n return \\\"draw\\\"\",\n \"def punch(self):\\n # you are not working, futher investagtion needed...\\n if self.weight < 5:\\n return \\\"That tickles.\\\"\\n elif self.weight < 15:\\n return \\\"Hey that hurt!\\\"\\n else:\\n return \\\"OUCH!\\\"\",\n \"def get_best_time():\\n\\n # Always remember about db.session.rollback() when debugging\\n\\n max_timing = db.session.query(func.min(Game.timing)).filter(Game.status == \\\"won\\\").first()\\n time_user = db.session.query(Game.timing, User.username).join(User).filter(Game.timing == max_timing, Game.status == \\\"won\\\").first()\\n\\n return time_user\",\n \"def winning_game_player(players):\\n\\n # in order for there to be a winner, the game must\\n # be over\\n if not game_over(players):\\n return None\\n\\n # if the game is over, it could be that there is no\\n # winner\\n active_players = players_with_decks(players)\\n if not active_players:\\n return False\\n\\n # if the game is over than find the winner\\n return players_with_decks(players)[0]\",\n \"def getWinner (self):\\r\\n\\t\\tlines = (\\r\\n\\t\\t\\tself.board, # columns\\r\\n\\t\\t\\tzip(*self.board), # rows\\r\\n\\t\\t\\tBoard.diagonalsPos(self.board, self.cols, self.rows),\\r\\n\\t\\t\\tBoard.diagonalsNeg(self.board, self.cols, self.rows) \\r\\n\\t\\t)\\r\\n\\r\\n\\t\\tfor line in chain(*lines):\\r\\n\\t\\t\\tfor figure, group in groupby(line):\\r\\n\\t\\t\\t\\tif figure != NONE and len(list(group)) >= self.win:\\r\\n\\t\\t\\t\\t\\treturn figure\",\n \"def _adv_counter(winrate_together, winrate_hero1, winrate_hero2):\\n return winrate_together\",\n \"def get_next_match_prefer_unfair_matches(population):\\n win_player = None\\n loss_player = None\\n for player in population:\\n if len(player.record) == 1:\\n if player.record[0] == \\\"W\\\":\\n win_player = player\\n elif player.record[0] == \\\"L\\\":\\n loss_player = player\\n if win_player and loss_player:\\n return win_player, loss_player\\n # if we can't find an unfair match, just pick the first available\\n return get_next_match_pick_first_available(population)\",\n \"def play(self):\\n while True:\\n self.round()\\n if not(self.player.playing) and (self.dealer.value >= 17):\\n break\\n self.update_state()\\n return self.end_game()\",\n \"def player_stand(self):\\r\\n if self.in_progress:\\r\\n while self.dealer_hand.total < 17:\\r\\n self.dealer_hand.add(self.deck.deal())\\r\\n if self.dealer_hand.total > 21 or self.dealer_hand.total < self.player_hand.total:\\r\\n self.status_color = 'red'\\r\\n self.game_status = \\\"Player WINS... Press 'r' to start game\\\"\\r\\n self.player_wins += 1\\r\\n elif self.player_hand.total == self.dealer_hand.total:\\r\\n self.status_color = 'red'\\r\\n self.game_status = \\\"TIE Game... Press 'r' to start game\\\"\\r\\n else:\\r\\n self.status_color = 'red'\\r\\n self.game_status = \\\"Dealer WINS... Press 'r' to start game\\\"\\r\\n self.dealer_wins += 1\\r\\n self.in_progress = False\\r\\n self.refresh_canvas()\",\n \"def won(self):\\n return self.roster.won\",\n \"def Pwin(state):\\n # Assumes opponent also plays with optimal strategy\\n p, me, you, pending = state\\n if me + pending >= goal:\\n return 1\\n elif you >= goal:\\n return 0\\n else:\\n return max(Q_pig(state, action, Pwin) for action in pig_actions(state))\",\n \"def player_win(self):\\n global chips\\n global placed_bet\\n\\n chips = (self.final_bet*2 + chips)\\n self.victory = True\\n placed_bet = False\",\n \"def pick_steal_target(self, callback=None):\\n players_copy = copy.copy(self.game.players)\\n players_copy.remove(self) # don't pick yourself!\\n wealthy_player = max(self.game.players, key=lambda x: x.coins)\\n callback(wealthy_player)\",\n \"def user_pick(self):\\n player_taking = True\\n while player_taking:\\n play_take = int(input(\\\"How many dots would you like to remove?(1-4)\\\"))\\n if not 1 <= play_take <= 4:\\n print(\\\"You may only take between 1 and 4 balls\\\")\\n else:\\n player_taking = False\\n return play_take\",\n \"def winner(self):\\n state = self._state['visible']\\n if state['reserve'][0] < 1:\\n return 1\\n elif state['reserve'][1] < 1:\\n return 0\\n return -1\",\n \"def get_max_readings( self ):\\n return 2500\",\n \"def _get_next_limit(self):\\n return self.__quota\",\n \"async def evaluate(self):\\n if self.players[1].id == bot.user.id:\\n self.p2_move = random.choice((\\\"Rock\\\", \\\"Paper\\\", \\\"Scissors\\\"))\\n\\n if None in self.moves:\\n return\\n\\n if len(self.moves) == 1:\\n tie_embed = discord.Embed(title=\\\"It's a Draw\\\")\\n await self.channel.send(embed=tie_embed)\\n return await self.end()\\n\\n if self.moves == {\\\"Rock\\\", \\\"Paper\\\"}:\\n winner = \\\"Paper\\\"\\n elif self.moves == {\\\"Scissors\\\", \\\"Paper\\\"}:\\n winner = \\\"Scissors\\\"\\n elif self.moves == {\\\"Rock\\\", \\\"Scissors\\\"}:\\n winner = \\\"Rock\\\"\\n\\n # P1 Wins\\n if self.p1_move == winner:\\n embed = discord.Embed(\\n title=f\\\"{self.players[0].name}'s **{winner}** beats {self.players[1].name}'s **{self.p2_move}**\\\")\\n await self.channel.send(embed=embed)\\n await self.end(winner=self.players[0])\\n\\n # P2 Wins\\n elif self.p2_move == winner:\\n embed = discord.Embed(\\n title=f\\\"{self.players[1].name}'s **{winner}** beats {self.players[0].name}'s **{self.p1_move}**\\\")\\n await self.channel.send(embed=embed)\\n await self.end(winner=self.players[1])\",\n \"def winFor(self,player):\\n if(self.cachedWin == False):\\n won = False;\\n if(player==WHITE):\\n for x in range(0,WIDTH):\\n if(self.gameState[x,0]==WHITE):\\n won = True\\n \\n elif(player==BLACK):\\n for x in range(0,WIDTH):\\n if(self.gameState[x,HEIGHT-1]==BLACK):\\n won = True\\n \\n if(len(self.successors()) == 0):#IF there are no available moves for both players\\n bCount = self.count(BLACK) #check who has the most pawns\\n wCount = self.count(BLACK)\\n if(bCount>wCount):\\n self.cachedWin = True\\n self.cachedWinner = player\\n return True\\n if(wCount>bCount):\\n self.cachedWin = True\\n self.cachedWinner = player\\n return True\\n \\n if(won):\\n self.cachedWin = True\\n self.cachedWinner = player\\n return True\\n else:\\n return False\\n else:\\n return player == self.cachedWinner\",\n \"def _take_wager(self, _game_address: Address, _amount: int) -> None:\\n if _amount <= 0:\\n revert(f\\\"Invalid bet amount {_amount}\\\")\\n auth_score = self.create_interface_score(self._game_auth_score.get(), AuthInterface)\\n if auth_score.get_game_status(_game_address) != \\\"gameApproved\\\":\\n revert(f'Bet only accepted through approved games.')\\n if self.__day_advanced():\\n self.__check_for_dividends()\\n self._daily_bet_count.set(self._daily_bet_count.get() + 1)\\n auth_score.accumulate_daily_wagers(_game_address, _amount)\\n Logger.debug(f'Sending wager data to rewards score.', TAG)\\n rewards_score = self.create_interface_score(self._rewards_score.get(), RewardsInterface)\\n rewards_score.accumulate_wagers(str(self.tx.origin), _amount, (self._day.get() - self._skipped_days.get()) % 2)\\n self._treasury_balance.set(self.icx.get_balance(self.address))\",\n \"def round_advance(self):\\n\\n\\t\\t# takes current round and advances it by one.\\n\\t\\tif self.model.status <= 9:\\n\\t\\t\\t\\n\\t\\t\\tself.model.status += 1\",\n \"def get_winners():\\r\\n\\r\\n numbers = []\\r\\n\\r\\n # Randomly get 5 winning numbers\\r\\n for i in range(0, 5):\\r\\n if not numbers:\\r\\n number = random.randrange(1, 71)\\r\\n while number > 25:\\r\\n number = random.randrange(1, 71)\\r\\n else:\\r\\n numbers.append(number)\\r\\n else:\\r\\n numbers.append(random.randrange(numbers[i - 1], 71))\\r\\n\\r\\n # Randomly get multiplying ball\\r\\n numbers.append(random.randrange(1, 25))\\r\\n\\r\\n return numbers\",\n \"def heavy_rollout(self, game):\\n game = game.copy()\\n while True:\\n moves = game.get_legal_moves()\\n if not moves:\\n break\\n scores = [(self.score(game.forecast_move(m), game.active_player), m) for m in moves]\\n _, best = max(scores, key=lambda x: x[0])\\n game.apply_move(best)\\n return game\",\n \"def _adv_synergy(winrate_together, winrate_hero1, winrate_hero2):\\n return winrate_together\",\n \"def get_wins_overall(self, uuid):\\n\\n return self.template(uuid, \\\"wins\\\")\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.607354","0.60145956","0.5848289","0.58172387","0.57498705","0.5735455","0.5721542","0.56717646","0.5671178","0.5665499","0.5651265","0.5645929","0.5634616","0.55988336","0.55921286","0.559142","0.55852073","0.55724007","0.55680674","0.5562452","0.55509394","0.5520514","0.5516257","0.54812247","0.54711634","0.546675","0.5431267","0.5426583","0.5406156","0.53945214","0.5387781","0.538657","0.53858936","0.5380849","0.5377137","0.5375408","0.5358078","0.53542536","0.5353617","0.533372","0.53297347","0.53280425","0.531224","0.5306995","0.5306995","0.52966887","0.52869797","0.528517","0.5275849","0.5275849","0.5271692","0.52675146","0.5263308","0.526144","0.5242863","0.52407354","0.52407354","0.5240579","0.52392036","0.52359223","0.5234169","0.52312577","0.5225664","0.52219063","0.52171665","0.5215621","0.52152467","0.5211457","0.52069485","0.5204874","0.519612","0.51908505","0.51841354","0.5181203","0.5180286","0.5177507","0.5175726","0.51748115","0.51696116","0.51648057","0.51599586","0.515589","0.51411575","0.513903","0.5135257","0.5134099","0.51324284","0.51207936","0.5112849","0.5112504","0.5108366","0.51081157","0.5106886","0.5099951","0.5090645","0.5088198","0.5086419","0.50852555","0.5078287","0.50759405"],"string":"[\n \"0.607354\",\n \"0.60145956\",\n \"0.5848289\",\n \"0.58172387\",\n \"0.57498705\",\n \"0.5735455\",\n \"0.5721542\",\n \"0.56717646\",\n \"0.5671178\",\n \"0.5665499\",\n \"0.5651265\",\n \"0.5645929\",\n \"0.5634616\",\n \"0.55988336\",\n \"0.55921286\",\n \"0.559142\",\n \"0.55852073\",\n \"0.55724007\",\n \"0.55680674\",\n \"0.5562452\",\n \"0.55509394\",\n \"0.5520514\",\n \"0.5516257\",\n \"0.54812247\",\n \"0.54711634\",\n \"0.546675\",\n \"0.5431267\",\n \"0.5426583\",\n \"0.5406156\",\n \"0.53945214\",\n \"0.5387781\",\n \"0.538657\",\n \"0.53858936\",\n \"0.5380849\",\n \"0.5377137\",\n \"0.5375408\",\n \"0.5358078\",\n \"0.53542536\",\n \"0.5353617\",\n \"0.533372\",\n \"0.53297347\",\n \"0.53280425\",\n \"0.531224\",\n \"0.5306995\",\n \"0.5306995\",\n \"0.52966887\",\n \"0.52869797\",\n \"0.528517\",\n \"0.5275849\",\n \"0.5275849\",\n \"0.5271692\",\n \"0.52675146\",\n \"0.5263308\",\n \"0.526144\",\n \"0.5242863\",\n \"0.52407354\",\n \"0.52407354\",\n \"0.5240579\",\n \"0.52392036\",\n \"0.52359223\",\n \"0.5234169\",\n \"0.52312577\",\n \"0.5225664\",\n \"0.52219063\",\n \"0.52171665\",\n \"0.5215621\",\n \"0.52152467\",\n \"0.5211457\",\n \"0.52069485\",\n \"0.5204874\",\n \"0.519612\",\n \"0.51908505\",\n \"0.51841354\",\n \"0.5181203\",\n \"0.5180286\",\n \"0.5177507\",\n \"0.5175726\",\n \"0.51748115\",\n \"0.51696116\",\n \"0.51648057\",\n \"0.51599586\",\n \"0.515589\",\n \"0.51411575\",\n \"0.513903\",\n \"0.5135257\",\n \"0.5134099\",\n \"0.51324284\",\n \"0.51207936\",\n \"0.5112849\",\n \"0.5112504\",\n \"0.5108366\",\n \"0.51081157\",\n \"0.5106886\",\n \"0.5099951\",\n \"0.5090645\",\n \"0.5088198\",\n \"0.5086419\",\n \"0.50852555\",\n \"0.5078287\",\n \"0.50759405\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.52707225"},"document_rank":{"kind":"string","value":"51"}}},{"rowIdx":81469,"cells":{"query":{"kind":"string","value":"Returns the initialized player attributes. This function is called just once, but the player dict is updated on each round"},"document":{"kind":"string","value":"def _initialize_game(wager_credits):\n player = {}\n player['chips'] = wager_credits\n player['round'] = 0\n player['blackjack'] = 0\n player['won'] = 0\n player['lost'] = 0\n player['push'] = 0\n player['bust'] = 0\n return player"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_player_attributes(self):\n return Player_Attributes.read_by_player_fifa_api_id(self.player_fifa_api_id)","def __init__(self):\r\n self.players = {}","def player_properties(self):\n return self.properties.GetAll(self.player_interface)","def get_players():\n return {\"X\": play_human, \"O\": play_ai}","def _get_player_info(self):\n return [player._player_info() for player in self.players.values()]","def _initialize_player_stats(self):\r\n self.reset()\r\n for x in range(self.num_players):\r\n self.player_draws[f'{x}']=[]\r\n self.player_points[f'{x}']= 0","def newGameLoad():\n import new_game\n global attributes\n attributes = {\"heroName\": new_game.heroName, \"hp\": new_game.hp, \"exp\": new_game.exp, \"lvl\": new_game.lvl,\n \"strength\": new_game.strength, \"mana\": new_game.mana,\n \"hpPotions\": new_game.hpPotions, \"manaPotions\": new_game.manaPotions,\n \"weapon\": new_game.weapon, \"weaponAtt\": new_game.weaponAtt}\n return(attributes)","def extra_state_attributes(self):\n attributes = {}\n if self._multiroom_group != []:\n attributes[ATTR_LINKPLAY_GROUP] = self._multiroom_group\n attributes[ATTR_GROUP_MEMBERS] = self._multiroom_group\n\n attributes[ATTR_MASTER] = self._is_master\n if self._slave_mode:\n attributes[ATTR_SLAVE] = self._slave_mode\n if self._media_uri_final:\n attributes[ATTR_MEDIA_CONTENT_ID] = self._media_uri_final\n if len(self._trackq) > 0:\n attributes[ATTR_TRCNT] = len(self._trackq) - 1\n if self._trackc:\n attributes[ATTR_TRCRT] = self._trackc\n if self._uuid != '':\n attributes[ATTR_UUID] = self._uuid\n\n attributes[ATTR_TTS] = self._playing_tts\n attributes[ATTR_SNAPSHOT] = self._snapshot_active\n attributes[ATTR_SNAPSPOT] = self._snap_spotify\n \n attributes[ATTR_MASS_POSITION] = self._mass_position\n\n if DEBUGSTR_ATTR:\n atrdbg = \"\"\n if self._playing_localfile:\n atrdbg = atrdbg + \" _playing_localfile\"\n\n if self._playing_spotify:\n atrdbg = atrdbg + \" _playing_spotify\"\n\n if self._playing_webplaylist:\n atrdbg = atrdbg + \" _playing_webplaylist\"\n\n if self._playing_stream:\n atrdbg = atrdbg + \" _playing_stream\"\n\n if self._playing_liveinput:\n atrdbg = atrdbg + \" _playing_liveinput\"\n\n if self._playing_tts:\n atrdbg = atrdbg + \" _playing_tts\"\n \n if self._playing_mediabrowser:\n atrdbg = atrdbg + \" _playing_mediabrowser\"\n \n if self._playing_mass:\n atrdbg = atrdbg + \" _playing_mass\"\n\n attributes[ATTR_DEBUG] = atrdbg\n\n if self._state != STATE_UNAVAILABLE:\n attributes[ATTR_FWVER] = self._fw_ver + \".\" + self._mcu_ver\n\n return attributes","def load(cls):\n playerdata = Data.raw_load(\"savedata.dat\")\n for key in playerdata:\n cls.name = playerdata[\"name\"]\n cls.max_hp = playerdata[\"max_hp\"]\n cls.hp = playerdata[\"hp\"]\n cls.lv = playerdata[\"lv\"]\n cls.exp = playerdata[\"exp\"]\n cls.atk = playerdata[\"atk\"]\n cls._def = playerdata[\"_def\"]\n cls.inventory = playerdata[\"inventory\"]\n cls.pin = playerdata[\"pin\"]","def player_data(self):\n return self._player","def to_json(self):\n player = {\n 'name': self.name,\n 'colour': self.colour,\n 'gender': self.gender,\n 'uid': self.UID,\n 'position': self.position,\n 'money': self.money,\n 'ready': self.is_ready(),\n }\n return player","def SavedGameLoad():\n import saved_game\n global attributes\n attributes = {\"heroName\": saved_game.heroName, \"hp\": saved_game.hp, \"exp\": saved_game.exp, \"lvl\": saved_game.lvl,\n \"strength\": saved_game.strength, \"mana\": saved_game.mana,\n \"hpPotions\": saved_game.hpPotions, \"manaPotions\": saved_game.manaPotions,\n \"weapon\": saved_game.weapon, \"weaponAtt\": saved_game.weaponAtt}\n return(attributes)","def returnPlayerStats(self):\n\t\tplayerStats = [self.name, \n\t\t\t\t\t self.agility, \n\t\t\t\t\t self.personality, \n\t\t\t\t\t self.sanity, \n\t\t\t\t\t self.strength, \n\t\t\t\t\t self.progress]\n\t\treturn playerStats","def initialize_movement_info():\n\n # index of player to blit on screen\n playerIndex = 0\n playerIndexGen = cycle([0, 1, 2, 1])\n # iterator used to change playerIndex after every 5th iteration\n loopIter = 0\n\n playerx = int(SCREENWIDTH * 0.2)\n playery = int((SCREENHEIGHT - IMAGES['player'][0].get_height()) / 2)\n\n messagex = int((SCREENWIDTH - IMAGES['message'].get_width()) / 2)\n messagey = int(SCREENHEIGHT * 0.12)\n\n basex = 0\n # amount by which base can maximum shift to left\n baseShift = IMAGES['base'].get_width() - IMAGES['background'].get_width()\n\n # player shm for up-down motion on welcome screen\n playerShmVals = {'val': 0, 'dir': 1}\n\n # make first flap sound and return values for mainGame\n SOUNDS['wing'].play() if SOUND_ON else None\n return {'playery': playery + playerShmVals['val'],\n 'basex': basex,\n 'playerIndexGen': playerIndexGen,}","def reset_attributes():\n \n print(\"reset_attributes\")\n\n attributes = {\n \"scores\": {},\n \"state\": \"Start\",\n \"current_player\": 0,\n \"current_round\": 0,\n \"current_question\": \"\",\n \"sess_questions\":[],\n \"question_index\": 0,\n \"speech_output\": WELCOME_MESSAGE,\n \"reprompt_text\": HELP_MESSAGE}\n \n return attributes","def __initStats(self):\n players = self.teamparser.getPlayers()\n try:\n stats = players[(self.team, self.position)]\n except KeyError, err:\n stats = (0, 0, 0, 0, 0, 0)\n raise TypeError, \"Invalid Team/Position: \" + self.team\n self.max = int(stats[0]) #maximum\n self.ma = int(stats[1]) #movement\n self.st = int(stats[2]) #strength\n self.ag = int(stats[3]) #agility\n self.av = int(stats[4]) #armor value\n self.costs = int(stats[5]) #costs\n self.injury = 0 #injury\n self.ssp = 0 #starplayerpoints\n self.touchdowns = 0 #touchdown\n self.completions = 0 #completions\n self.interceptions = 0 #interceptions\n self.casualties = 0 #casualties\n self.mvpawards = 0 #most valuable player awards","def initialize_object_attributes(self, ai_game):\r\n self.ship_bullets = ai_game.ship_bullets\r\n self.alien_bullets = ai_game.alien_bullets\r\n self.aliens = ai_game.aliens\r\n self.explosions = ai_game.explosions\r\n self.stats = ai_game.stats\r\n self.sb = ai_game.sb\r\n self.ship = ai_game.ship","def load_players_dict(self):\n player_dict = {}\n for player_file in os.listdir(self.player_path):\n player_name = player_file.split(sep='.')[0]\n player_dict[player_name] = player_file\n return(player_dict)","def __init__(self):\n self.space1 = 0\n self.space2 = 0\n self.space3 = 0\n self.space4 = 0\n self.space5 = 0\n self.space6 = 0\n self.playerList = []","def _player_info(self):\n return \"%r %s seat:%s m:%r c:%s b:%s \" % (self.name, self.serial, self.seat, self.money, self._chips, self._bet)","def get_info(self):\n players = self.player_set\n if self.order_by == 'rank':\n players = players.order_by('rank')\n else:\n players = players.order_by('-rating')\n\n # if players have None scores, move to the bottom\n none_players = []\n players = list(players)\n for player in players:\n if ((self.order_by == 'rank' and player.rank is None)\n or (self.order_by == 'rating' and player.rating is None)):\n none_players.append(player)\n players.remove(player)\n players.extend(none_players)\n\n return dict(\n players = players,\n players_json = json.dumps([\n {\n 'id': player.id,\n 'name': \"%d %s\" % (\n player.rank or len(players), player.name)\n }\n for player in players]),\n num_matches = self.match_set.count(),\n num_rounds = Round.objects.filter(match__company = self).count(),\n recent_matches = (self.match_set\n .order_by('-played_time')[:MATCH_RESULT_LIMIT]),\n api_account_id = self.get_api_account_id(),\n api_access_key = self.get_api_access_key()\n )","def __init__(self, player, gamestate):\n self.player = player\n self.gamestate = gamestate","def build_player_data():\n names = [\"Gunther O'Brian\",\n 'Workman Gloom',\n 'Esme Ramsey',\n 'Cornelius Games',\n 'Kline Greenlemon',\n 'Hotbox Sato',\n 'Famous Owens',\n 'Jenkins Good']\n nums = [77, 31, 37, 6, 14, 53, 7, 64]\n avgs = [0.40666, 0.118451, 0.400093, 0.335117,\n 0.425694, 0.353378, 0.179842, 0.246856]\n\n return names, nums, avgs","def _init_game(self):\n state, player_id = self.game.init_game()\n if self.record_action:\n self.action_recorder = []\n return self._extract_state(state), player_id","def get_players(self):\r\n return self.players.values()","def __init__(self, player_name, player_number, player_position):\n self.name = player_name\n self.number = player_number\n self.position = player_position","def get_player_stats() -> List[BaseStat]:\n return [BoostStat(),\n PositionalTendencies(),\n Averages(),\n BallDistanceStat(),\n ControlsStat(),\n SpeedTendencies(),\n CarryStat(),\n PerPossessionStat(),\n SpeedTendencies(),\n RumbleItemStat(),\n KickoffStat(),\n DropshotStats(),\n DemoStat()\n ]","def __init__(self):\n super().__init__(SCREEN_WIDTH, SCREEN_HEIGHT, SCREEN_TITLE)\n self.player_count: int = None\n self.player_hand_0: arcade.SpriteList = None\n self.player_hand_1: arcade.SpriteList = None\n self.deck: arcade.SpriteList = None\n self.pile: arcade.SpriteList = None","def __init__(self, player):\n self.player = player","def make_player(self, page):\r\n player = Player()\r\n face = page.find(\"div\",id=\"info_content\").find_all(\"td\")\r\n player.name = face[0].get_text().strip()\r\n player.club = face[1].get_text().strip()\r\n player.nation = face[2].get_text().strip()\r\n player.league = face[3].get_text().strip()\r\n player.sf = int(face[4].get_text().strip())\r\n player.wf = int(face[5].get_text().strip())\r\n player.ir = int(face[6].get_text().strip())\r\n player.foot = face[7].get_text().strip()\r\n player.height = float(face[8].get_text().split(\"|\")[0].strip(\"cm \"))\r\n player.weight = float(face[9].get_text().strip(\"\"))\r\n player.version = face[10].get_text().strip()\r\n player.def_wr = face[11].get_text().strip()\r\n player.att_wr = face[12].get_text().strip()\r\n player.added_on = datetime.strptime(face[13].get_text().strip()[2:], \"%y-%m-%d\")\r\n player.real_face = face[15].get_text().strip()==\"icon-checkmark text-success\"\r\n player.body_type = face[16].get_text().strip()\r\n player.age = face[17].get_text().strip(\" years old \\n\\r\")\r\n player.rating = self.make_rating([sub for sub in page.find(\"div\",id=\"stats_box\").find(class_=\"stats-inner col-md-12\").find(class_=\"row\").children])\r\n player.href = \"/\"+page.find(id=\"share_player_link\")[\"value\"].strip(\"https://www.futbin.com/\")\r\n player.pid = int(page.find(id=\"page-info\")[\"data-player-resource\"])\r\n return player","def resetPlayerDefaultAttributes(self):\r\n debug.write(\"[SourceRPG] Resetting player %s default attribute\" % self.name, 2)\r\n self.playerAttributes['baseHealth'] = 100\r\n self.playerAttributes['maxHealth'] = 100\r\n self.playerAttributes['maxSpeed'] = 1.0\r\n self.playerAttributes['maxGravity'] = 1.0\r\n self.playerAttributes['minStealth'] = 255\r\n self.playerAttributes['maxArmor'] = 100\r\n debug.write(\"[SourceRPG] Attributes reset\", 2)","def __init__(self, game, player):\n self.game = game\n self.player = player","def __init__(self, player):\n\t\tself.player = player","def _init_attributes(self):\n self.attr = {\n 'name': None,\n 'tags': [],\n 'openHours': None,\n 'type': None,\n 'parent': None,\n 'locationId': None,\n 'bannerAbbreviation': None,\n 'arcGisAbbreviation': None,\n 'geoLocation': None,\n 'geometry': None,\n 'summary': None,\n 'description': None,\n 'descriptionHtml': None,\n 'address': None,\n 'city': None,\n 'state': None,\n 'zip': None,\n 'county': None,\n 'telephone': None,\n 'fax': None,\n 'thumbnails': [],\n 'images': [],\n 'departments': [],\n 'website': None,\n 'sqft': None,\n 'calendar': None,\n 'campus': None,\n 'girCount': None,\n 'girLimit': False,\n 'girLocations': None,\n 'synonyms': [],\n 'bldgId': None,\n 'parkingZoneGroup': None,\n 'propId': None,\n 'adaParkingSpaceCount': None,\n 'motorcycleParkingSpaceCount': None,\n 'evParkingSpaceCount': None,\n 'weeklyMenu': None,\n 'notes': None,\n 'labels': {},\n 'steward': None,\n 'shape': {}\n }","def __init__(self, players):\n\n self._players = players\n self._game = None","def initialize_players():\n return [Player(name, Hand([]), 0) for name in PLAYER_NAMES]","def __init__(self):\n \n self.player = None\n self.brick_list = None\n self.coin_list = None\n self.physics_engine = None\n self.num_coins = None","def __init__(self):\n self.players = {1: [\"Player_a\", \"\\u25CF\"], 2: [\"Player_b\", \"\\u25CB\"]}\n self.current_player = 1\n self.playing_player = self.players[1]\n self.grid = [[\" \"] * 6 for x in range(7)]","def __init__(self):\n # Mutual attributes (summoner_v1.4 & current_game_v1.0)\n self.id = None\n self.name = None\n self.profile_icon_id = None\n\n # summoner_v1.4 attributes\n self.revision_date = None\n self.level = None","def initAttributes(self):\n Packet.initAttributes(self)\n self.packetType = TM_PACKET_TYPE","def __init__(self, player_id, difficulty_level):\n self.player_id = player_id\n self.difficulty_level = difficulty_level\n global our_player\n our_player = player_id","def initialize_game_params(self):\r\n\r\n self.is_new_game = True\r\n self.is_game_over = False\r\n self.is_game_lost = False\r\n self.is_left_mouse_down = False\r\n self.is_right_mouse_down = False\r\n self.num_of_hidden_non_mines_tiles = self.rows * self.cols - self.num_of_mines","def collectPlayers(self):\n \n playerDict = {}\n self.hardware = {}\n for session in self.sessions:\n player = playerDict.get(session.avId, None)\n if not player:\n player = Player(session.avId)\n playerDict[session.avId] = player\n player.addSession(session)\n\n self.hardware.setdefault((player, session.getHardware()), []).append(session)\n\n self.players = playerDict.values()\n for player in self.players:\n player.calcFrameRate()","def players(self) -> dict[int, Player]:\n return self._players","def get_state(self):\n return {\n \"board\": self.board,\n \"player\": self.player,\n \"winner\": self.winner\n }","def __init__(self):\n\n self.name = 'KuhnPoker'\n self.num_players = 2","def __init__(self):\n self.played_pos = []\n self.grid = [['-', '-', '-'],\n ['-', '-', '-'],\n ['-', '-', '-']]\n self.player_played_pos = {'p1': set(), 'p2': set()}","def __init__(self):\n self.board_dict = dict()\n for i in range(self.BOARD_WIDTH):\n for j in range(self.BOARD_WIDTH):\n self.board_dict[i, j] = 0, None\n\n self.players_locations = dict()\n self.last_moved = None","def __init__(self, player_raw: dict, time_per_player_game: int,\n start_side: int, board_size: int, n_players: int):\n self.is_ai = player_raw[\"is_ai\"]\n self.id_ = player_raw[\"id_\"]\n self.name = player_raw[\"name\"]\n self.executable = player_raw[\"executable\"]\n self.color = player_raw[\"color\"]\n self.time_per_game = time_per_player_game\n self.start_side = start_side\n self.board_size = board_size\n self.n_players = n_players\n self.coordinates = self.get_starting_coordinates(\n board_size, start_side)\n\n self.goals: List[Coordinates] = self.get_goal_states(\n self.coordinates, self.board_size)\n\n if self.is_ai and os.path.isfile(self.executable):\n self.proc: Optional[Popen] = self.start_ai(\n self.executable,\n self.n_players,\n self.board_size,\n self.time_per_game,\n self.start_side,\n )","def __init__(self):\n self.games = {} # Dict from gameIDs to game objects. Initially empty.\n self.players = {} # Dict from playerID to player name\n self._version = __version__ # Used in version check during un-pickling\n\n # Log initialization\n TournamentSystem._logger.debug(\"Initialized\")","def load_attrs(self):\n return loads(self.get_attr().GetObject()) or {}","def getInitialPlayer(self):\n return self.__colordict__[self.__initial_color__]","def __init__(self, playerColors : Dict[str, str]):\n initialGameState = {\n \"counter\" : {\"Team1\" : 0, \"Team2\" : 0},\n \"lastChanged\" : None,\n \"wonRounds\" : {\"Team1\" : 0, \"Team2\" : 0},\n \"wonGames\" : {\"Team1\" : 0, \"Team2\" : 0},\n \"currentMaxPoints\" : self.maxPointsWithoutOvertime,\n \"sidesChanged\" : False,\n \"playerPositions\" : {\"Team1\" : {\"Player1\" : 1, \"Player2\": 2}, \"Team2\" : {\"Player1\" : 3, \"Player2\": 4}},\n \"servePosition\" : 0,\n \"playerColors\" : playerColors,\n \"undoStack\" : [],\n \"redoStack\" : [],\n \"observers\" : []}\n self.setGameState(initialGameState)","def init_attrs(self):\n raise NotImplementedError","def hook_collectgamesetup(self):\n result = ui.collectgamesetup()\n # The following unpacking/repacking is just to force the interface:\n return {'nPlayers':result['nPlayers'],'ixDealer':result['ixDealer'],\n 'playerCharCards':result['playerCharCards'],\n 'playerCardHeldCounts':result['playerCardHeldCounts'],\n 'myCards':result['myCards']}","def update(self) -> None:\n try:\n client = self._client\n\n if client.state == \"Playing\":\n self._attr_state = MediaPlayerState.PLAYING\n elif client.state == \"Paused\":\n self._attr_state = MediaPlayerState.PAUSED\n elif client.state == \"Disconnected\":\n self._attr_state = MediaPlayerState.OFF\n else:\n self._attr_state = MediaPlayerState.PAUSED\n\n if client.last_update and (time.time() - client.last_update > 40):\n self._attr_state = MediaPlayerState.OFF\n\n volume = float(client.volume) if client.volume else 0.0\n self._attr_volume_level = volume / 100.0\n if client.active_playlist_id in client.playlists:\n self._attr_source = client.playlists[client.active_playlist_id][\"name\"]\n else:\n self._attr_source = \"Unknown\"\n self._attr_source_list = [s[\"name\"] for s in client.playlists.values()]\n\n if client.current_track:\n self._attr_media_title = client.current_track[\"title\"]\n self._attr_media_artist = client.current_track[\"track_artist\"]\n self._attr_media_album_name = client.current_track[\"track_album\"]\n self._attr_media_image_hash = client.current_track[\"track_id\"]\n else:\n self._attr_media_image_hash = None\n\n except Exception:\n self._attr_state = MediaPlayerState.OFF\n raise","def player_to_raw(player: andesite.Player) -> Dict[str, Any]:\n return convert_to_raw(player)","def __init__(self, players):\n\n self._players = players\n self._current_player = players.get()","def __init__(self, _gameBeingPlayed, _charcter):\n self.name = \"random\"\n random.seed(2)\n self.game = _gameBeingPlayed\n self.character = _charcter\n self.neutralCharacter = self.game.neutralCharacter","def init_players(self):\n complain = \"\"\n players_turn = random.sample(range(self.n_players), self.n_players)\n players_created = {}\n picked_colors = []\n for x in range(self.n_players):\n while True:\n clear_output()\n try:\n color = input(\n f\"{complain}Player {x+1}, please type in one of the following colors: ({', '.join([x.capitalize() for x in self.world.player_colors if x not in picked_colors])}):\\n\").lower()\n if color in self.world.player_colors and color not in picked_colors:\n picked_colors.append(color)\n players_created[players_turn[x]] = Player(\n color.capitalize(), self.start_troops)\n break\n else:\n complain = \"Please enter a valid color\\n\"\n except:\n pass\n\n self.players = [players_created[y] for x in range(\n self.n_players) for y in players_created.keys() if int(y) == x]","def initial_obs(self):\n\n return (PrivateObservation(-1, player=0), PrivateObservation(-1, player=1),\n PublicObservation([1, 1]))","def __init__(self, **kwargs):\n self.paused = self._get('paused', **kwargs)\n self.title = self._get('title', **kwargs)\n self.artist = self._get('artist', **kwargs)\n self.album = self._get('album', **kwargs)\n self.total_time = self._get('total_time', **kwargs)\n self.position = self._get('position', **kwargs)\n self.mediakind = self._get('mediakind', **kwargs)\n self.playstatus = self._get('playstatus', **kwargs)","def init_player():\n global active_track_idx\n global track_last_slided_pos\n global track_last_paused_pos\n global track_total_play_time \n\n # INITIALIZE Player\n active_track_idx = -1\n cancel_update_play_time_loop()\n cancel_track_end_event_loop()\n track_status.set(\"---\")\n track_title.set(\"--- : \")\n play_pause_btn.configure(image=play_img)\n track_last_slided_pos = 0\n track_last_paused_pos = 0\n track_total_play_time = 0\n track_pos_label.configure(text=\"00:00\")\n track_length_label.configure(text=\"00:00\")\n track_pos_slider.configure(state=\"disabled\")\n track_pos.set(0)","def initGame(self):\n self.map = {}\n self.blocks = Group()\n self.Coins =Group()\n self.players = Group()\n self.player1 = Player(1525,75,2)\n self.players.add(self.player1)\n if self.playernum == 2:\n self.player2 = Player(75,825,1)\n self.players.add(self.player2)\n else:\n self.player2 = False","def _load_player_map(self) -> None:\n # Loading people that have had ab appearance in the year specified\n # This might not be general enough as some players get paid even if they don't play\n sql = \"\"\"\\\n select p.playerid, p.namefirst, p.namelast, p.namegiven, a.team_id\n from people p\n INNER JOIN appearances a ON p.playerid = a.playerid and a.yearid = %s\n \"\"\"\n\n self._cursor.execute(sql, (self._yearid,))\n duplicates = 0\n all_players = self._cursor.fetchall()\n for player in all_players:\n r = {'playerid': player[0], 'namefirst': player[1], 'namelast': player[2],\n 'namegiven': player[3], 'team_id': player[4]}\n\n # Build a key from namefirst, namelast and team_id, then remove all spaces\n # Make sure we don't already have the player loaded, count and report duplicates.\n key = \"{}{}{}\".format(player[1], player[2], player[4]).replace(\" \", \"\")\n if self._player_map.get(key) is None:\n self._player_map[key] = r\n else:\n duplicates += 1\n\n # We'll add the player again using his given first name if different from namefirst\n given_first = player[3].split()[0]\n if given_first != player[1]:\n key2 = \"{}{}{}\".format(given_first, player[2], player[4]).replace(\" \", \"\")\n if self._player_map.get(key2) is None:\n self._player_map[key2] = r\n else:\n duplicates += 1\n\n if duplicates > 0:\n raise RuntimeError(\"Duplicates found building player map: \" + str(duplicates))","def __init__(self):\n super(PregamePitcherGameEntry, self).__init__()\n\n self.predicted_draftkings_points = 0\n self.draftkings_salary = 0\n\n # Season stats\n self.season_bf = 0\n self.season_ip = 0\n self.season_so = 0\n self.season_wins = 0\n self.season_losses = 0\n self.season_er = 0\n self.season_h = 0\n self.season_bb = 0\n self.season_hr = 0\n\n # Career stats\n self.career_bf = 0\n self.career_ip = 0\n self.career_so = 0\n self.career_wins = 0\n self.career_losses = 0\n self.career_er = 0\n self.career_h = 0\n self.career_bb = 0\n self.career_hr = 0\n\n # Versus stats\n self.vs_bf = 0\n self.vs_so = 0\n self.vs_er = 0\n self.vs_h = 0\n self.vs_bb = 0\n self.vs_hr = 0\n\n # Month stats\n self.recent_bf = 0\n self.recent_ip = 0\n self.recent_so = 0\n self.recent_er = 0\n self.recent_h = 0\n self.recent_bb = 0\n self.recent_hr = 0","def extra_state_attributes(self):\n return {\n ATTR_ATTRIBUTION: ATTRIBUTION,\n ATTR_STATION: self.probe.get_data(\"station_name\"),\n ATTR_UPDATED: self.probe.last_update.isoformat(),\n }","def set_instance_vars(self, new_vars=None):\n if new_vars is None:\n new_vars = Bird.default_player_values\n\n vars(self).update(new_vars)","def __repr__(self):\n name = self.name\n prefix = \": \"\n gen = (\n value for value in self.init_kwargs.values() if value is not None\n )\n for value in gen:\n try:\n if issubclass(value, Player):\n value = value.name\n except TypeError:\n pass\n name = \"\".join([name, prefix, str(value)])\n prefix = \", \"\n return name","def get_player_states(self, players):\n for player in self.players.values():\n p = players.add()\n p.id = player.id\n p.pos.CopyFrom(player.pos.to_protocol())","def extract_player_data(row):\n player = {\n 'player': row.find('td', {'data-stat': 'player'}).find('a').text,\n 'team': row.find('td', {'data-stat': 'team'}).text,\n 'fantasy_pos': row.find('td', {'data-stat': 'fantasy_pos'}).text,\n 'age': row.find('td', {'data-stat': 'age'}).text,\n 'g': row.find('td', {'data-stat': 'g'}).text,\n 'gs': row.find('td', {'data-stat': 'gs'}).text,\n 'pass_cmp': row.find('td', {'data-stat': 'pass_cmp'}).text,\n 'pass_att': row.find('td', {'data-stat': 'pass_att'}).text,\n 'pass_yds': row.find('td', {'data-stat': 'pass_yds'}).text,\n 'pass_td': row.find('td', {'data-stat': 'pass_td'}).text,\n 'pass_int': row.find('td', {'data-stat': 'pass_int'}).text,\n 'rush_att': row.find('td', {'data-stat': 'rush_att'}).text,\n 'rush_yds': row.find('td', {'data-stat': 'rush_yds'}).text,\n 'rush_yds_per_att': row.find(\n 'td', {'data-stat': 'rush_yds_per_att'}\n ).text,\n 'rush_td': row.find('td', {'data-stat': 'rush_td'}).text,\n 'rec': row.find('td', {'data-stat': 'rec'}).text,\n 'rec_yds': row.find('td', {'data-stat': 'rec_yds'}).text,\n 'rec_yds_per_rec': row.find(\n 'td', {'data-stat': 'rec_yds_per_rec'}\n ).text,\n 'rec_td': row.find('td', {'data-stat': 'rec_td'}).text,\n 'fumbles': row.find('td', {'data-stat': 'fumbles'}).text,\n 'fumbles_lost': row.find('td', {'data-stat': 'fumbles_lost'}).text,\n 'all_td': row.find('td', {'data-stat': 'all_td'}).text,\n 'two_pt_md': row.find('td', {'data-stat': 'two_pt_md'}).text,\n 'two_pt_pass': row.find('td', {'data-stat': 'two_pt_pass'}).text,\n 'fantasy_points': row.find(\n 'td', {'data-stat': 'fantasy_points'}\n ).text,\n 'fantasy_points_ppr': row.find(\n 'td', {'data-stat': 'fantasy_points_ppr'}\n ).text,\n 'draftkings_points': row.find(\n 'td', {'data-stat': 'draftkings_points'}\n ).text,\n 'fanduel_points': row.find(\n 'td', {'data-stat': 'fanduel_points'}\n ).text,\n 'vbd': row.find('td', {'data-stat': 'vbd'}).text,\n 'fantasy_rank_pos': row.find(\n 'td', {'data-stat': 'fantasy_rank_pos'}\n ).text,\n 'fantasy_rank_overall': row.find(\n 'td', {'data-stat': 'fantasy_rank_overall'}\n ).text,\n }\n \n # Need to handle targets column individually, since before 1992 targets were\n # not tracked.\n try:\n player['targets'] = row.find('td', {'data-stat': 'targets'}).text\n except AttributeError:\n player['targets'] = None\n\n return player","def to_raw(self) -> Dict[str, Any]:\n if self._player:\n raw_player = player_to_raw(self._player)\n else:\n raw_player = None\n\n if self._voice_server_update:\n raw_voice_server_update = voice_server_update_to_raw(self._voice_server_update)\n else:\n raw_voice_server_update = None\n\n return {\n \"guild_id\": self.__guild_id,\n \"player\": raw_player,\n \"track\": self._track,\n \"voice_server_update\": raw_voice_server_update,\n }","def __init__(self, player1, player2):\n # # players of the game {player1name: {color: , red_marbles:}}\n # self._players = {player1[0]: {\"name\": player1[0], \"color\": player1[1]},\n # player2[0]: {\"name\": player2[0], \"color\": player2[1]}}\n # # empty board, no marbles yet\n # self._board = self.create_board()\n # # current player's turn\n # self._turn = None\n # # winner state\n # self._winner = None\n # # red marbles captured for each player, needs addition of black and white marbles\n # self._captured = {player1[0]: 0, player2[0]: 0}\n pass","def __init__(self):\n self.name = None\n self.time_stamp = time()\n self.last_win = None\n self.wins = 0","def __init__(self, player_control, players=None):\r\n self.player_control = player_control\r\n self.players = {} # copy for restoration\r\n if players is not None:\r\n for player in players.values():\r\n self.add_player(player)","def __init__(self, player: DuneHDPlayer, name: str, unique_id: str) -> None:\n self._player = player\n self._media_title: str | None = None\n self._state: dict[str, Any] = {}\n self._attr_unique_id = unique_id\n self._attr_device_info = DeviceInfo(\n identifiers={(DOMAIN, unique_id)},\n manufacturer=ATTR_MANUFACTURER,\n name=name,\n )","def __init__(self, player):\r\n other_player = \"lower\" if player == \"upper\" else \"upper\"\r\n \r\n #set our sides \r\n self.player_information[\"us\"][\"player_side\"] = player\r\n self.player_information[\"them\"][\"player_side\"] = other_player\r\n\r\n #create our board edge and board representation\r\n self.board_edge = hex_boundary_getter((0,0), 4, [])\r\n self.board_array = generate_board()","def players(self):\n return self._get(\"players\")","def update(self):\r\n debug.write(\"Querying stats for player %s\" % self.name, 3)\r\n debug.write(\"Is turbo mode on? %s\" % ({True:\"Yes\", False:\"No\"}[currentTurboMode]), 3)\r\n if not currentTurboMode:\r\n database.execute(\"SELECT * FROM Player WHERE UserID=?\", self.dbUserid)\r\n \r\n \"\"\" \r\n ~NOTE: Nasty, explicitly defining may break in future updates if I\r\n alter the DB structure, think of a new way to alter this.\r\n \r\n Thoughts:\r\n \r\n Make a list of the structure, then call the list and update the oldAttributes\r\n and currentAttributes with items from the list.\r\n \"\"\"\r\n result = database.fetchone()\r\n UserID, steamid, level, xp, credits, popup, name, lastconnected = result\r\n\r\n debug.write(\"Steamid: %s\" % steamid, 3)\r\n debug.write(\"DB UserID: %s\" % UserID, 3)\r\n debug.write(\"xp: %s\" % xp, 3)\r\n debug.write(\"Credits %s\" % credits, 3)\r\n debug.write(\"Level: %s\" % level, 3)\r\n \r\n for option in ('steamid', 'level', 'xp', 'credits', 'popup', 'name', 'lastconnected'):\r\n self.oldAttributes[option] = self.currentAttributes[option] = locals()[option]\r\n \r\n \"\"\" Retrieve the skills id and level from the database \"\"\"\r\n database.execute(\"SELECT name,level FROM Skill WHERE UserID=?\", self.dbUserid )\r\n \r\n \"\"\" Iterate through all the skills returned \"\"\"\r\n for skill in database.fetchall():\r\n \"\"\" Each iteration will produce a 2 itemed tuple with skillrow and level \"\"\"\r\n skillName, level = skill\r\n\r\n debug.write(\"Skill %s :: level %s\" % (skillName, level), 3)\r\n \r\n \"\"\" We only want to add the skill if it's currently loaded \"\"\"\r\n self.oldSkills[skillName] = self.currentSkills[skillName] = level\r\n \r\n else:\r\n \"\"\" Turbo mode is on, make the default attributes \"\"\" \r\n defaultValues = {\r\n \"level\" : 1,\r\n \"xp\" : 0,\r\n \"credits\" : int(startCredits),\r\n \"popup\" : int(popupStatus),\r\n \"lastconnected\" : int(time.time())\r\n }\r\n for key, value in defaultValues.iteritems():\r\n self.oldAttributes[key] = self.currentAttributes[key] = value","def set_props(cont):\n\n\t# Basic\n\town = cont.owner\n\t\n\t# Sensors\n\ts_keyboard = cont.sensors['keyboard']\n\t\n\t# Objects\n\to_group = own.groupObject\n\t\t\n\t# Properties\n\tp_player = globalDict['state']['player']\n\tp_controls = globalDict['settings']['controls']\n\tup = p_controls['key_up'] in s_keyboard.inputs.keys()\n\tdown = p_controls['key_down'] in s_keyboard.inputs.keys()\n\tleft = p_controls['key_left'] in s_keyboard.inputs.keys()\n\tright = p_controls['key_right'] in s_keyboard.inputs.keys()\n\trun = p_controls['key_run'] in s_keyboard.inputs.keys()\n\tcrouch = p_controls['key_crouch'] in s_keyboard.inputs.keys()\n\t\n\tif o_group != None:\n\t\t\n\t\t#print(s_keyboard.inputs)\n\t\t\n\t\t# Vertical\n\t\tif not up and not down or up and down:\n\t\t\tp_player['mov_v'] = 0\n\t\t\n\t\tif up and not down:\n\t\t\tp_player['mov_v'] = 1\n\t\t\n\t\tif not up and down:\n\t\t\tp_player['mov_v'] = -1\n\t\t\t\n\t\t# Horizontal\n\t\tif not left and not right or left and right:\n\t\t\tp_player['mov_h'] = 0\n\t\t\n\t\tif right and not left:\n\t\t\tp_player['mov_h'] = 1\n\t\t\n\t\tif not right and left:\n\t\t\tp_player['mov_h'] = -1\n\t\t\t\n\t\t# None\n\t\tif not run and not crouch or run and crouch:\n\t\t\tp_player['mov_run'] = 0\n\t\t\tp_player['mov_crouch'] = 0\n\t\t\t\n\t\t# Run\n\t\tif run and not crouch:\n\t\t\tp_player['mov_run'] = 1\n\t\t\tp_player['mov_crouch'] = 0\n\t\t\t\n\t\t# Crouch\n\t\tif not run and crouch:\n\t\t\tp_player['mov_run'] = 0\n\t\t\tp_player['mov_crouch'] = 1\n\t\t\t\n\t\t\n\tpass","def get_perfect_information(self):\n state = {}\n state[\"chips\"] = [self.game.players[i].in_chips for i in range(self.player_num)]\n state[\"public_card\"] = (\n self.game.public_card.get_index() if self.game.public_card else None\n )\n state[\"hand_cards\"] = [\n self.game.players[i].hand.get_index() for i in range(self.player_num)\n ]\n state[\"current_round\"] = self.game.round_counter\n state[\"current_player\"] = self.game.game_pointer\n state[\"legal_actions\"] = self.game.get_legal_actions()\n return state","def _init_attributes(self):\n if os.name == \"nt\":\n if \"64\" in platform.architecture()[0]:\n platform_arch = \"x86_64\"\n elif \"32\" in platform.architecture()[0]:\n platform_arch = \"i386\"\n else:\n platform_arch = platform.architecture()\n os_ver = f\"Windows-{platform.win32_ver()[1]}\"\n else:\n platform_arch = platform.machine()\n if platform.system() == \"Darwin\":\n os_ver = f\"macOS-{platform.mac_ver()[0]}\"\n else:\n os_ver = \"-\".join(linux_distribution()[0:2])\n\n license_chunks = LICENSE.split(\" \")\n if license_chunks[0] == \"GPLv2\":\n client_license = \"GPL-2.0\"\n else:\n client_license = \"Commercial\"\n\n default_attributes = {\n # Process id\n \"_pid\": str(os.getpid()),\n # Platform architecture\n \"_platform\": platform_arch,\n # OS version\n \"_os\": os_ver,\n # Hostname of the local machine\n \"_source_host\": socket.gethostname(),\n # Client's name\n \"_client_name\": \"mysql-connector-python\",\n # Client's version\n \"_client_version\": \".\".join([str(x) for x in VERSION[0:3]]),\n # Client's License identifier\n \"_client_license\": client_license,\n }\n self._settings[\"attributes\"].update(default_attributes)\n\n if \"connection-attributes\" in self._settings:\n for attr_name in self._settings[\"connection-attributes\"]:\n attr_value = self._settings[\"connection-attributes\"][attr_name]\n # Validate name type\n if not isinstance(attr_name, str):\n raise InterfaceError(\n f\"Attribute name '{attr_name}' must be a string type\"\n )\n # Validate attribute name limit 32 characters\n if len(attr_name) > 32:\n raise InterfaceError(\n f\"Attribute name '{attr_name}' exceeds 32 characters \"\n \"limit size\"\n )\n # Validate names in connection-attributes cannot start with \"_\"\n if attr_name.startswith(\"_\"):\n raise InterfaceError(\n \"Key names in 'session-connect-attributes' cannot \"\n f\"start with '_', found: {attr_name}\"\n )\n # Validate value type\n if not isinstance(attr_value, str):\n raise InterfaceError(\n f\"Attribute name '{attr_name}' value '{attr_value}' \"\n \" must be a string type\"\n )\n\n # Validate attribute value limit 1024 characters\n if len(attr_value) > 1024:\n raise InterfaceError(\n f\"Attribute name '{attr_name}' value: '{attr_value}' \"\n \"exceeds 1024 characters limit size\"\n )\n\n self._settings[\"attributes\"][attr_name] = attr_value","def _player_list(self):\n game = self.ctrl.game\n return game.players[self.i_to_player_id(0)], game.players[self.i_to_player_id(1)]","def __init__(self, data):\n # add play_guid as it sometimes doesn't exist\n if 'play_guid' not in data:\n data['play_guid'] = ''\n # loop through data\n for x in data:\n # set information as correct data type\n mlbgame.object.setobjattr(self, x, data[x])","def player_from_raw(data: Dict[str, Any]) -> andesite.Player:\n return build_from_raw(andesite.Player, data)","async def get_self(self) -> PlayerInfo:\n e = await self.request.request(url=f'https://users.roblox.com/v1/users/authenticated', method='get')\n a = PlayerInfo(player_id=e['id'], request=self.request)\n await a.update()\n return a","def __init__(self, name=\"Player\", resources=[0,0,0,0,0,0,0,0], xor_resources=None,\\\n current_hand=None, structures=None, starting_gold=3, discounted_resources=None):\n if structures != None:\n self.structures = structures # by type? Should we have a structure type? \n else:\n self.structures = []\n \n self.name = name\n self.wonders = None \n player.west_natural= False\n player.west_manufactured = False\n player.east_natural= False\n player.east_manufactured= False\n\n if current_hand == None:\n self.current_hand = None\n else:\n self.current_hand = current_hand #I dont know if we need this\n self.starting_gold = starting_gold","def __init__(self,state,player=WHITE):\n if(state==None):\n self.gameState = dict()\n for x in range(0,WIDTH):\n for y in range(0,HEIGHT):\n self.gameState[x,y] = EMPTY\n for x in range(0,WIDTH):\n self.gameState[x,BSTARTROW] = BLACK#Blacks starting row\n self.gameState[x,WSTARTROW] = WHITE#Whites starting row\n #whites.append(Board.pawn(Board.pos(x,WSTARTROW),WHITE))\n #blacks.append(Board.pawn(Board.pos(x,BSTARTROW),BLACK))\n else:\n self.gameState = state\n \n self.whoseTurn = player\n self.cachedWin = False # set to True in winFor() if\n self.cachedWinner = None","def __init__(self, min_player_count):\n self.min_player_count = min_player_count","def __init__(self):\n self.get_name()\n self.get_difficulty()\n self.get_guesses()\n self.get_answer()\n self.get_wager()\n self.chance = 0","def setup(self):\n header_print(self.data['intro'])\n header_print(self.data['help'])\n random.shuffle(self.data['draw'])\n random.shuffle(self.data['locations'])\n random.shuffle(self.data['events'])\n random.shuffle(self.data['aces'])\n random.shuffle(self.data['personalities'])\n self.stats = {\n 'round': 0,\n 'powers': {\n 'MOONS': 6,\n 'SUNS': 6,\n 'WAVES': 6,\n 'LEAVES': 6,\n 'WYRMS': 6,\n 'KNOTS': 6,\n },\n 'hand': self.data['draw'][:],\n 'discard': [],\n 'active': [],\n 'opponent': {},\n }","def gameState(self):\n gameState = {\"counter\" : {\"Team1\" : self.counter[\"Team1\"], \"Team2\" : self.counter[\"Team2\"]},\\\n \"lastChanged\" : self.lastChanged,\\\n \"wonRounds\" : {\"Team1\" : self.wonRounds[\"Team1\"], \"Team2\" : self.wonRounds[\"Team2\"]},\\\n \"wonGames\" : {\"Team1\" : self.wonGames[\"Team1\"], \"Team2\" : self.wonGames[\"Team2\"]},\\\n \"currentMaxPoints\" : self.currentMaxPoints,\\\n \"sidesChanged\" : self.sidesChanged,\\\n \"playerPositions\" : self.playerPositions,\\\n \"servePosition\" : self.servePosition,\\\n \"playerColors\" : self.playerColors,\\\n \"undoStack\" : self._undoStack,\\\n \"redoStack\" : self._redoStack,\\\n \"observers\" : self.__observers,\\\n \"gameName\" : self._getGameName()}\n return gameState","def __init__(self, *args, **kwargs):\n super(Player, self).__init__(*args, **kwargs)","def NowPlaying(self):\n self.logger.debug(\"Fetching currently playing information\")\n try:\n xbmc = Server(self.url('/jsonrpc', True))\n player = xbmc.Player.GetActivePlayers()[0]\n playerid = player['playerid']\n\n if player['type'] == 'video':\n playerprop = ['speed', 'position', 'time', 'totaltime',\n 'percentage', 'subtitleenabled', 'currentsubtitle',\n 'subtitles', 'currentaudiostream', 'audiostreams']\n itemprop = ['thumbnail', 'showtitle', 'season', 'episode', 'year', 'fanart']\n\n elif player['type'] == 'audio':\n playerprop = ['speed', 'position', 'time', 'totaltime', 'percentage']\n itemprop = ['thumbnail', 'title', 'artist', 'album', 'year', 'fanart']\n\n app = xbmc.Application.GetProperties(properties=['muted', 'volume'])\n player = xbmc.Player.GetProperties(playerid=playerid, properties=playerprop)\n item = xbmc.Player.GetItem(playerid=playerid, properties=itemprop)\n\n return {'playerInfo': player, 'itemInfo': item, 'app': app}\n except:\n self.logger.debug(\"Unable to fetch currently playing information!\")\n return","def init_meta(self):\n self.meta = {}\n # Required (core)\n self.meta['ra'] = dict(ext=0, card='RA')\n self.meta['dec'] = dict(ext=0, card='DEC')\n self.meta['target'] = dict(ext=0, card='OBJECT')\n self.meta['decker'] = dict(ext=0, card=None, default='default')\n self.meta['dichroic'] = dict(ext=0, card=None, default='default')\n self.meta['binning'] = dict(ext=0, card=None, default='1,1')\n\n self.meta['mjd'] = dict(ext=0, card='ACQTIME')\n self.meta['exptime'] = dict(ext=0, card='EXPTIME')\n self.meta['airmass'] = dict(ext=0, card='AIRMASS')\n # Extras for config and frametyping\n self.meta['dispname'] = dict(ext=0, card='GRISM')\n self.meta['idname'] = dict(ext=0, card='OBSTYPE')\n self.meta['instrument'] = dict(ext=0, card='INSTRUME')","def update(self, player_info):\n self.seat = player_info.get(\"seat\", -1)\n self.name = player_info.get(\"name\", \"unknown\")\n self.sit_out = player_info.get(\"sit_out\", True)","def attributes_to_save(self):\r\n return ['initial_pos', 'height', 'width']","def display_make_a_player():\n display_head_menu(\"Création du joueur\")\n player_dict = {}\n player_dict.update({\"lastname\": display(\"Nom: \")})\n player_dict.update({\"firstname\": display(\"Prénom: \")})\n player_dict.update({\"gender\": display(\"Genre : (homme/femme)\", \"gender\")})\n player_dict.update({\"date_of_birth\": display(\"Date de naissance: \", \"date\")})\n player_dict.update({\"ranking\": display(\"Classement : \", \"natural\")})\n return player_dict","def get_attributes(self):\n\n _attributes = (self.survival_id, self.record_id, self.name,\n self.source_id, self.failure_date, self.left_interval,\n self.right_interval, self.status_id, self.quantity,\n self.tbf, self.mode_type_id, self.nevada_chart,\n self.ship_date, self.number_shipped, self.return_date,\n self.number_returned, self.user_float_1,\n self.user_float_2, self.user_float_3,\n self.user_integer_1, self.user_integer_2,\n self.user_integer_3, self.user_string_1,\n self.user_string_2, self.user_string_3)\n\n return _attributes","def get_player_items(self):\n return self.player.items"],"string":"[\n \"def get_player_attributes(self):\\n return Player_Attributes.read_by_player_fifa_api_id(self.player_fifa_api_id)\",\n \"def __init__(self):\\r\\n self.players = {}\",\n \"def player_properties(self):\\n return self.properties.GetAll(self.player_interface)\",\n \"def get_players():\\n return {\\\"X\\\": play_human, \\\"O\\\": play_ai}\",\n \"def _get_player_info(self):\\n return [player._player_info() for player in self.players.values()]\",\n \"def _initialize_player_stats(self):\\r\\n self.reset()\\r\\n for x in range(self.num_players):\\r\\n self.player_draws[f'{x}']=[]\\r\\n self.player_points[f'{x}']= 0\",\n \"def newGameLoad():\\n import new_game\\n global attributes\\n attributes = {\\\"heroName\\\": new_game.heroName, \\\"hp\\\": new_game.hp, \\\"exp\\\": new_game.exp, \\\"lvl\\\": new_game.lvl,\\n \\\"strength\\\": new_game.strength, \\\"mana\\\": new_game.mana,\\n \\\"hpPotions\\\": new_game.hpPotions, \\\"manaPotions\\\": new_game.manaPotions,\\n \\\"weapon\\\": new_game.weapon, \\\"weaponAtt\\\": new_game.weaponAtt}\\n return(attributes)\",\n \"def extra_state_attributes(self):\\n attributes = {}\\n if self._multiroom_group != []:\\n attributes[ATTR_LINKPLAY_GROUP] = self._multiroom_group\\n attributes[ATTR_GROUP_MEMBERS] = self._multiroom_group\\n\\n attributes[ATTR_MASTER] = self._is_master\\n if self._slave_mode:\\n attributes[ATTR_SLAVE] = self._slave_mode\\n if self._media_uri_final:\\n attributes[ATTR_MEDIA_CONTENT_ID] = self._media_uri_final\\n if len(self._trackq) > 0:\\n attributes[ATTR_TRCNT] = len(self._trackq) - 1\\n if self._trackc:\\n attributes[ATTR_TRCRT] = self._trackc\\n if self._uuid != '':\\n attributes[ATTR_UUID] = self._uuid\\n\\n attributes[ATTR_TTS] = self._playing_tts\\n attributes[ATTR_SNAPSHOT] = self._snapshot_active\\n attributes[ATTR_SNAPSPOT] = self._snap_spotify\\n \\n attributes[ATTR_MASS_POSITION] = self._mass_position\\n\\n if DEBUGSTR_ATTR:\\n atrdbg = \\\"\\\"\\n if self._playing_localfile:\\n atrdbg = atrdbg + \\\" _playing_localfile\\\"\\n\\n if self._playing_spotify:\\n atrdbg = atrdbg + \\\" _playing_spotify\\\"\\n\\n if self._playing_webplaylist:\\n atrdbg = atrdbg + \\\" _playing_webplaylist\\\"\\n\\n if self._playing_stream:\\n atrdbg = atrdbg + \\\" _playing_stream\\\"\\n\\n if self._playing_liveinput:\\n atrdbg = atrdbg + \\\" _playing_liveinput\\\"\\n\\n if self._playing_tts:\\n atrdbg = atrdbg + \\\" _playing_tts\\\"\\n \\n if self._playing_mediabrowser:\\n atrdbg = atrdbg + \\\" _playing_mediabrowser\\\"\\n \\n if self._playing_mass:\\n atrdbg = atrdbg + \\\" _playing_mass\\\"\\n\\n attributes[ATTR_DEBUG] = atrdbg\\n\\n if self._state != STATE_UNAVAILABLE:\\n attributes[ATTR_FWVER] = self._fw_ver + \\\".\\\" + self._mcu_ver\\n\\n return attributes\",\n \"def load(cls):\\n playerdata = Data.raw_load(\\\"savedata.dat\\\")\\n for key in playerdata:\\n cls.name = playerdata[\\\"name\\\"]\\n cls.max_hp = playerdata[\\\"max_hp\\\"]\\n cls.hp = playerdata[\\\"hp\\\"]\\n cls.lv = playerdata[\\\"lv\\\"]\\n cls.exp = playerdata[\\\"exp\\\"]\\n cls.atk = playerdata[\\\"atk\\\"]\\n cls._def = playerdata[\\\"_def\\\"]\\n cls.inventory = playerdata[\\\"inventory\\\"]\\n cls.pin = playerdata[\\\"pin\\\"]\",\n \"def player_data(self):\\n return self._player\",\n \"def to_json(self):\\n player = {\\n 'name': self.name,\\n 'colour': self.colour,\\n 'gender': self.gender,\\n 'uid': self.UID,\\n 'position': self.position,\\n 'money': self.money,\\n 'ready': self.is_ready(),\\n }\\n return player\",\n \"def SavedGameLoad():\\n import saved_game\\n global attributes\\n attributes = {\\\"heroName\\\": saved_game.heroName, \\\"hp\\\": saved_game.hp, \\\"exp\\\": saved_game.exp, \\\"lvl\\\": saved_game.lvl,\\n \\\"strength\\\": saved_game.strength, \\\"mana\\\": saved_game.mana,\\n \\\"hpPotions\\\": saved_game.hpPotions, \\\"manaPotions\\\": saved_game.manaPotions,\\n \\\"weapon\\\": saved_game.weapon, \\\"weaponAtt\\\": saved_game.weaponAtt}\\n return(attributes)\",\n \"def returnPlayerStats(self):\\n\\t\\tplayerStats = [self.name, \\n\\t\\t\\t\\t\\t self.agility, \\n\\t\\t\\t\\t\\t self.personality, \\n\\t\\t\\t\\t\\t self.sanity, \\n\\t\\t\\t\\t\\t self.strength, \\n\\t\\t\\t\\t\\t self.progress]\\n\\t\\treturn playerStats\",\n \"def initialize_movement_info():\\n\\n # index of player to blit on screen\\n playerIndex = 0\\n playerIndexGen = cycle([0, 1, 2, 1])\\n # iterator used to change playerIndex after every 5th iteration\\n loopIter = 0\\n\\n playerx = int(SCREENWIDTH * 0.2)\\n playery = int((SCREENHEIGHT - IMAGES['player'][0].get_height()) / 2)\\n\\n messagex = int((SCREENWIDTH - IMAGES['message'].get_width()) / 2)\\n messagey = int(SCREENHEIGHT * 0.12)\\n\\n basex = 0\\n # amount by which base can maximum shift to left\\n baseShift = IMAGES['base'].get_width() - IMAGES['background'].get_width()\\n\\n # player shm for up-down motion on welcome screen\\n playerShmVals = {'val': 0, 'dir': 1}\\n\\n # make first flap sound and return values for mainGame\\n SOUNDS['wing'].play() if SOUND_ON else None\\n return {'playery': playery + playerShmVals['val'],\\n 'basex': basex,\\n 'playerIndexGen': playerIndexGen,}\",\n \"def reset_attributes():\\n \\n print(\\\"reset_attributes\\\")\\n\\n attributes = {\\n \\\"scores\\\": {},\\n \\\"state\\\": \\\"Start\\\",\\n \\\"current_player\\\": 0,\\n \\\"current_round\\\": 0,\\n \\\"current_question\\\": \\\"\\\",\\n \\\"sess_questions\\\":[],\\n \\\"question_index\\\": 0,\\n \\\"speech_output\\\": WELCOME_MESSAGE,\\n \\\"reprompt_text\\\": HELP_MESSAGE}\\n \\n return attributes\",\n \"def __initStats(self):\\n players = self.teamparser.getPlayers()\\n try:\\n stats = players[(self.team, self.position)]\\n except KeyError, err:\\n stats = (0, 0, 0, 0, 0, 0)\\n raise TypeError, \\\"Invalid Team/Position: \\\" + self.team\\n self.max = int(stats[0]) #maximum\\n self.ma = int(stats[1]) #movement\\n self.st = int(stats[2]) #strength\\n self.ag = int(stats[3]) #agility\\n self.av = int(stats[4]) #armor value\\n self.costs = int(stats[5]) #costs\\n self.injury = 0 #injury\\n self.ssp = 0 #starplayerpoints\\n self.touchdowns = 0 #touchdown\\n self.completions = 0 #completions\\n self.interceptions = 0 #interceptions\\n self.casualties = 0 #casualties\\n self.mvpawards = 0 #most valuable player awards\",\n \"def initialize_object_attributes(self, ai_game):\\r\\n self.ship_bullets = ai_game.ship_bullets\\r\\n self.alien_bullets = ai_game.alien_bullets\\r\\n self.aliens = ai_game.aliens\\r\\n self.explosions = ai_game.explosions\\r\\n self.stats = ai_game.stats\\r\\n self.sb = ai_game.sb\\r\\n self.ship = ai_game.ship\",\n \"def load_players_dict(self):\\n player_dict = {}\\n for player_file in os.listdir(self.player_path):\\n player_name = player_file.split(sep='.')[0]\\n player_dict[player_name] = player_file\\n return(player_dict)\",\n \"def __init__(self):\\n self.space1 = 0\\n self.space2 = 0\\n self.space3 = 0\\n self.space4 = 0\\n self.space5 = 0\\n self.space6 = 0\\n self.playerList = []\",\n \"def _player_info(self):\\n return \\\"%r %s seat:%s m:%r c:%s b:%s \\\" % (self.name, self.serial, self.seat, self.money, self._chips, self._bet)\",\n \"def get_info(self):\\n players = self.player_set\\n if self.order_by == 'rank':\\n players = players.order_by('rank')\\n else:\\n players = players.order_by('-rating')\\n\\n # if players have None scores, move to the bottom\\n none_players = []\\n players = list(players)\\n for player in players:\\n if ((self.order_by == 'rank' and player.rank is None)\\n or (self.order_by == 'rating' and player.rating is None)):\\n none_players.append(player)\\n players.remove(player)\\n players.extend(none_players)\\n\\n return dict(\\n players = players,\\n players_json = json.dumps([\\n {\\n 'id': player.id,\\n 'name': \\\"%d %s\\\" % (\\n player.rank or len(players), player.name)\\n }\\n for player in players]),\\n num_matches = self.match_set.count(),\\n num_rounds = Round.objects.filter(match__company = self).count(),\\n recent_matches = (self.match_set\\n .order_by('-played_time')[:MATCH_RESULT_LIMIT]),\\n api_account_id = self.get_api_account_id(),\\n api_access_key = self.get_api_access_key()\\n )\",\n \"def __init__(self, player, gamestate):\\n self.player = player\\n self.gamestate = gamestate\",\n \"def build_player_data():\\n names = [\\\"Gunther O'Brian\\\",\\n 'Workman Gloom',\\n 'Esme Ramsey',\\n 'Cornelius Games',\\n 'Kline Greenlemon',\\n 'Hotbox Sato',\\n 'Famous Owens',\\n 'Jenkins Good']\\n nums = [77, 31, 37, 6, 14, 53, 7, 64]\\n avgs = [0.40666, 0.118451, 0.400093, 0.335117,\\n 0.425694, 0.353378, 0.179842, 0.246856]\\n\\n return names, nums, avgs\",\n \"def _init_game(self):\\n state, player_id = self.game.init_game()\\n if self.record_action:\\n self.action_recorder = []\\n return self._extract_state(state), player_id\",\n \"def get_players(self):\\r\\n return self.players.values()\",\n \"def __init__(self, player_name, player_number, player_position):\\n self.name = player_name\\n self.number = player_number\\n self.position = player_position\",\n \"def get_player_stats() -> List[BaseStat]:\\n return [BoostStat(),\\n PositionalTendencies(),\\n Averages(),\\n BallDistanceStat(),\\n ControlsStat(),\\n SpeedTendencies(),\\n CarryStat(),\\n PerPossessionStat(),\\n SpeedTendencies(),\\n RumbleItemStat(),\\n KickoffStat(),\\n DropshotStats(),\\n DemoStat()\\n ]\",\n \"def __init__(self):\\n super().__init__(SCREEN_WIDTH, SCREEN_HEIGHT, SCREEN_TITLE)\\n self.player_count: int = None\\n self.player_hand_0: arcade.SpriteList = None\\n self.player_hand_1: arcade.SpriteList = None\\n self.deck: arcade.SpriteList = None\\n self.pile: arcade.SpriteList = None\",\n \"def __init__(self, player):\\n self.player = player\",\n \"def make_player(self, page):\\r\\n player = Player()\\r\\n face = page.find(\\\"div\\\",id=\\\"info_content\\\").find_all(\\\"td\\\")\\r\\n player.name = face[0].get_text().strip()\\r\\n player.club = face[1].get_text().strip()\\r\\n player.nation = face[2].get_text().strip()\\r\\n player.league = face[3].get_text().strip()\\r\\n player.sf = int(face[4].get_text().strip())\\r\\n player.wf = int(face[5].get_text().strip())\\r\\n player.ir = int(face[6].get_text().strip())\\r\\n player.foot = face[7].get_text().strip()\\r\\n player.height = float(face[8].get_text().split(\\\"|\\\")[0].strip(\\\"cm \\\"))\\r\\n player.weight = float(face[9].get_text().strip(\\\"\\\"))\\r\\n player.version = face[10].get_text().strip()\\r\\n player.def_wr = face[11].get_text().strip()\\r\\n player.att_wr = face[12].get_text().strip()\\r\\n player.added_on = datetime.strptime(face[13].get_text().strip()[2:], \\\"%y-%m-%d\\\")\\r\\n player.real_face = face[15].get_text().strip()==\\\"icon-checkmark text-success\\\"\\r\\n player.body_type = face[16].get_text().strip()\\r\\n player.age = face[17].get_text().strip(\\\" years old \\\\n\\\\r\\\")\\r\\n player.rating = self.make_rating([sub for sub in page.find(\\\"div\\\",id=\\\"stats_box\\\").find(class_=\\\"stats-inner col-md-12\\\").find(class_=\\\"row\\\").children])\\r\\n player.href = \\\"/\\\"+page.find(id=\\\"share_player_link\\\")[\\\"value\\\"].strip(\\\"https://www.futbin.com/\\\")\\r\\n player.pid = int(page.find(id=\\\"page-info\\\")[\\\"data-player-resource\\\"])\\r\\n return player\",\n \"def resetPlayerDefaultAttributes(self):\\r\\n debug.write(\\\"[SourceRPG] Resetting player %s default attribute\\\" % self.name, 2)\\r\\n self.playerAttributes['baseHealth'] = 100\\r\\n self.playerAttributes['maxHealth'] = 100\\r\\n self.playerAttributes['maxSpeed'] = 1.0\\r\\n self.playerAttributes['maxGravity'] = 1.0\\r\\n self.playerAttributes['minStealth'] = 255\\r\\n self.playerAttributes['maxArmor'] = 100\\r\\n debug.write(\\\"[SourceRPG] Attributes reset\\\", 2)\",\n \"def __init__(self, game, player):\\n self.game = game\\n self.player = player\",\n \"def __init__(self, player):\\n\\t\\tself.player = player\",\n \"def _init_attributes(self):\\n self.attr = {\\n 'name': None,\\n 'tags': [],\\n 'openHours': None,\\n 'type': None,\\n 'parent': None,\\n 'locationId': None,\\n 'bannerAbbreviation': None,\\n 'arcGisAbbreviation': None,\\n 'geoLocation': None,\\n 'geometry': None,\\n 'summary': None,\\n 'description': None,\\n 'descriptionHtml': None,\\n 'address': None,\\n 'city': None,\\n 'state': None,\\n 'zip': None,\\n 'county': None,\\n 'telephone': None,\\n 'fax': None,\\n 'thumbnails': [],\\n 'images': [],\\n 'departments': [],\\n 'website': None,\\n 'sqft': None,\\n 'calendar': None,\\n 'campus': None,\\n 'girCount': None,\\n 'girLimit': False,\\n 'girLocations': None,\\n 'synonyms': [],\\n 'bldgId': None,\\n 'parkingZoneGroup': None,\\n 'propId': None,\\n 'adaParkingSpaceCount': None,\\n 'motorcycleParkingSpaceCount': None,\\n 'evParkingSpaceCount': None,\\n 'weeklyMenu': None,\\n 'notes': None,\\n 'labels': {},\\n 'steward': None,\\n 'shape': {}\\n }\",\n \"def __init__(self, players):\\n\\n self._players = players\\n self._game = None\",\n \"def initialize_players():\\n return [Player(name, Hand([]), 0) for name in PLAYER_NAMES]\",\n \"def __init__(self):\\n \\n self.player = None\\n self.brick_list = None\\n self.coin_list = None\\n self.physics_engine = None\\n self.num_coins = None\",\n \"def __init__(self):\\n self.players = {1: [\\\"Player_a\\\", \\\"\\\\u25CF\\\"], 2: [\\\"Player_b\\\", \\\"\\\\u25CB\\\"]}\\n self.current_player = 1\\n self.playing_player = self.players[1]\\n self.grid = [[\\\" \\\"] * 6 for x in range(7)]\",\n \"def __init__(self):\\n # Mutual attributes (summoner_v1.4 & current_game_v1.0)\\n self.id = None\\n self.name = None\\n self.profile_icon_id = None\\n\\n # summoner_v1.4 attributes\\n self.revision_date = None\\n self.level = None\",\n \"def initAttributes(self):\\n Packet.initAttributes(self)\\n self.packetType = TM_PACKET_TYPE\",\n \"def __init__(self, player_id, difficulty_level):\\n self.player_id = player_id\\n self.difficulty_level = difficulty_level\\n global our_player\\n our_player = player_id\",\n \"def initialize_game_params(self):\\r\\n\\r\\n self.is_new_game = True\\r\\n self.is_game_over = False\\r\\n self.is_game_lost = False\\r\\n self.is_left_mouse_down = False\\r\\n self.is_right_mouse_down = False\\r\\n self.num_of_hidden_non_mines_tiles = self.rows * self.cols - self.num_of_mines\",\n \"def collectPlayers(self):\\n \\n playerDict = {}\\n self.hardware = {}\\n for session in self.sessions:\\n player = playerDict.get(session.avId, None)\\n if not player:\\n player = Player(session.avId)\\n playerDict[session.avId] = player\\n player.addSession(session)\\n\\n self.hardware.setdefault((player, session.getHardware()), []).append(session)\\n\\n self.players = playerDict.values()\\n for player in self.players:\\n player.calcFrameRate()\",\n \"def players(self) -> dict[int, Player]:\\n return self._players\",\n \"def get_state(self):\\n return {\\n \\\"board\\\": self.board,\\n \\\"player\\\": self.player,\\n \\\"winner\\\": self.winner\\n }\",\n \"def __init__(self):\\n\\n self.name = 'KuhnPoker'\\n self.num_players = 2\",\n \"def __init__(self):\\n self.played_pos = []\\n self.grid = [['-', '-', '-'],\\n ['-', '-', '-'],\\n ['-', '-', '-']]\\n self.player_played_pos = {'p1': set(), 'p2': set()}\",\n \"def __init__(self):\\n self.board_dict = dict()\\n for i in range(self.BOARD_WIDTH):\\n for j in range(self.BOARD_WIDTH):\\n self.board_dict[i, j] = 0, None\\n\\n self.players_locations = dict()\\n self.last_moved = None\",\n \"def __init__(self, player_raw: dict, time_per_player_game: int,\\n start_side: int, board_size: int, n_players: int):\\n self.is_ai = player_raw[\\\"is_ai\\\"]\\n self.id_ = player_raw[\\\"id_\\\"]\\n self.name = player_raw[\\\"name\\\"]\\n self.executable = player_raw[\\\"executable\\\"]\\n self.color = player_raw[\\\"color\\\"]\\n self.time_per_game = time_per_player_game\\n self.start_side = start_side\\n self.board_size = board_size\\n self.n_players = n_players\\n self.coordinates = self.get_starting_coordinates(\\n board_size, start_side)\\n\\n self.goals: List[Coordinates] = self.get_goal_states(\\n self.coordinates, self.board_size)\\n\\n if self.is_ai and os.path.isfile(self.executable):\\n self.proc: Optional[Popen] = self.start_ai(\\n self.executable,\\n self.n_players,\\n self.board_size,\\n self.time_per_game,\\n self.start_side,\\n )\",\n \"def __init__(self):\\n self.games = {} # Dict from gameIDs to game objects. Initially empty.\\n self.players = {} # Dict from playerID to player name\\n self._version = __version__ # Used in version check during un-pickling\\n\\n # Log initialization\\n TournamentSystem._logger.debug(\\\"Initialized\\\")\",\n \"def load_attrs(self):\\n return loads(self.get_attr().GetObject()) or {}\",\n \"def getInitialPlayer(self):\\n return self.__colordict__[self.__initial_color__]\",\n \"def __init__(self, playerColors : Dict[str, str]):\\n initialGameState = {\\n \\\"counter\\\" : {\\\"Team1\\\" : 0, \\\"Team2\\\" : 0},\\n \\\"lastChanged\\\" : None,\\n \\\"wonRounds\\\" : {\\\"Team1\\\" : 0, \\\"Team2\\\" : 0},\\n \\\"wonGames\\\" : {\\\"Team1\\\" : 0, \\\"Team2\\\" : 0},\\n \\\"currentMaxPoints\\\" : self.maxPointsWithoutOvertime,\\n \\\"sidesChanged\\\" : False,\\n \\\"playerPositions\\\" : {\\\"Team1\\\" : {\\\"Player1\\\" : 1, \\\"Player2\\\": 2}, \\\"Team2\\\" : {\\\"Player1\\\" : 3, \\\"Player2\\\": 4}},\\n \\\"servePosition\\\" : 0,\\n \\\"playerColors\\\" : playerColors,\\n \\\"undoStack\\\" : [],\\n \\\"redoStack\\\" : [],\\n \\\"observers\\\" : []}\\n self.setGameState(initialGameState)\",\n \"def init_attrs(self):\\n raise NotImplementedError\",\n \"def hook_collectgamesetup(self):\\n result = ui.collectgamesetup()\\n # The following unpacking/repacking is just to force the interface:\\n return {'nPlayers':result['nPlayers'],'ixDealer':result['ixDealer'],\\n 'playerCharCards':result['playerCharCards'],\\n 'playerCardHeldCounts':result['playerCardHeldCounts'],\\n 'myCards':result['myCards']}\",\n \"def update(self) -> None:\\n try:\\n client = self._client\\n\\n if client.state == \\\"Playing\\\":\\n self._attr_state = MediaPlayerState.PLAYING\\n elif client.state == \\\"Paused\\\":\\n self._attr_state = MediaPlayerState.PAUSED\\n elif client.state == \\\"Disconnected\\\":\\n self._attr_state = MediaPlayerState.OFF\\n else:\\n self._attr_state = MediaPlayerState.PAUSED\\n\\n if client.last_update and (time.time() - client.last_update > 40):\\n self._attr_state = MediaPlayerState.OFF\\n\\n volume = float(client.volume) if client.volume else 0.0\\n self._attr_volume_level = volume / 100.0\\n if client.active_playlist_id in client.playlists:\\n self._attr_source = client.playlists[client.active_playlist_id][\\\"name\\\"]\\n else:\\n self._attr_source = \\\"Unknown\\\"\\n self._attr_source_list = [s[\\\"name\\\"] for s in client.playlists.values()]\\n\\n if client.current_track:\\n self._attr_media_title = client.current_track[\\\"title\\\"]\\n self._attr_media_artist = client.current_track[\\\"track_artist\\\"]\\n self._attr_media_album_name = client.current_track[\\\"track_album\\\"]\\n self._attr_media_image_hash = client.current_track[\\\"track_id\\\"]\\n else:\\n self._attr_media_image_hash = None\\n\\n except Exception:\\n self._attr_state = MediaPlayerState.OFF\\n raise\",\n \"def player_to_raw(player: andesite.Player) -> Dict[str, Any]:\\n return convert_to_raw(player)\",\n \"def __init__(self, players):\\n\\n self._players = players\\n self._current_player = players.get()\",\n \"def __init__(self, _gameBeingPlayed, _charcter):\\n self.name = \\\"random\\\"\\n random.seed(2)\\n self.game = _gameBeingPlayed\\n self.character = _charcter\\n self.neutralCharacter = self.game.neutralCharacter\",\n \"def init_players(self):\\n complain = \\\"\\\"\\n players_turn = random.sample(range(self.n_players), self.n_players)\\n players_created = {}\\n picked_colors = []\\n for x in range(self.n_players):\\n while True:\\n clear_output()\\n try:\\n color = input(\\n f\\\"{complain}Player {x+1}, please type in one of the following colors: ({', '.join([x.capitalize() for x in self.world.player_colors if x not in picked_colors])}):\\\\n\\\").lower()\\n if color in self.world.player_colors and color not in picked_colors:\\n picked_colors.append(color)\\n players_created[players_turn[x]] = Player(\\n color.capitalize(), self.start_troops)\\n break\\n else:\\n complain = \\\"Please enter a valid color\\\\n\\\"\\n except:\\n pass\\n\\n self.players = [players_created[y] for x in range(\\n self.n_players) for y in players_created.keys() if int(y) == x]\",\n \"def initial_obs(self):\\n\\n return (PrivateObservation(-1, player=0), PrivateObservation(-1, player=1),\\n PublicObservation([1, 1]))\",\n \"def __init__(self, **kwargs):\\n self.paused = self._get('paused', **kwargs)\\n self.title = self._get('title', **kwargs)\\n self.artist = self._get('artist', **kwargs)\\n self.album = self._get('album', **kwargs)\\n self.total_time = self._get('total_time', **kwargs)\\n self.position = self._get('position', **kwargs)\\n self.mediakind = self._get('mediakind', **kwargs)\\n self.playstatus = self._get('playstatus', **kwargs)\",\n \"def init_player():\\n global active_track_idx\\n global track_last_slided_pos\\n global track_last_paused_pos\\n global track_total_play_time \\n\\n # INITIALIZE Player\\n active_track_idx = -1\\n cancel_update_play_time_loop()\\n cancel_track_end_event_loop()\\n track_status.set(\\\"---\\\")\\n track_title.set(\\\"--- : \\\")\\n play_pause_btn.configure(image=play_img)\\n track_last_slided_pos = 0\\n track_last_paused_pos = 0\\n track_total_play_time = 0\\n track_pos_label.configure(text=\\\"00:00\\\")\\n track_length_label.configure(text=\\\"00:00\\\")\\n track_pos_slider.configure(state=\\\"disabled\\\")\\n track_pos.set(0)\",\n \"def initGame(self):\\n self.map = {}\\n self.blocks = Group()\\n self.Coins =Group()\\n self.players = Group()\\n self.player1 = Player(1525,75,2)\\n self.players.add(self.player1)\\n if self.playernum == 2:\\n self.player2 = Player(75,825,1)\\n self.players.add(self.player2)\\n else:\\n self.player2 = False\",\n \"def _load_player_map(self) -> None:\\n # Loading people that have had ab appearance in the year specified\\n # This might not be general enough as some players get paid even if they don't play\\n sql = \\\"\\\"\\\"\\\\\\n select p.playerid, p.namefirst, p.namelast, p.namegiven, a.team_id\\n from people p\\n INNER JOIN appearances a ON p.playerid = a.playerid and a.yearid = %s\\n \\\"\\\"\\\"\\n\\n self._cursor.execute(sql, (self._yearid,))\\n duplicates = 0\\n all_players = self._cursor.fetchall()\\n for player in all_players:\\n r = {'playerid': player[0], 'namefirst': player[1], 'namelast': player[2],\\n 'namegiven': player[3], 'team_id': player[4]}\\n\\n # Build a key from namefirst, namelast and team_id, then remove all spaces\\n # Make sure we don't already have the player loaded, count and report duplicates.\\n key = \\\"{}{}{}\\\".format(player[1], player[2], player[4]).replace(\\\" \\\", \\\"\\\")\\n if self._player_map.get(key) is None:\\n self._player_map[key] = r\\n else:\\n duplicates += 1\\n\\n # We'll add the player again using his given first name if different from namefirst\\n given_first = player[3].split()[0]\\n if given_first != player[1]:\\n key2 = \\\"{}{}{}\\\".format(given_first, player[2], player[4]).replace(\\\" \\\", \\\"\\\")\\n if self._player_map.get(key2) is None:\\n self._player_map[key2] = r\\n else:\\n duplicates += 1\\n\\n if duplicates > 0:\\n raise RuntimeError(\\\"Duplicates found building player map: \\\" + str(duplicates))\",\n \"def __init__(self):\\n super(PregamePitcherGameEntry, self).__init__()\\n\\n self.predicted_draftkings_points = 0\\n self.draftkings_salary = 0\\n\\n # Season stats\\n self.season_bf = 0\\n self.season_ip = 0\\n self.season_so = 0\\n self.season_wins = 0\\n self.season_losses = 0\\n self.season_er = 0\\n self.season_h = 0\\n self.season_bb = 0\\n self.season_hr = 0\\n\\n # Career stats\\n self.career_bf = 0\\n self.career_ip = 0\\n self.career_so = 0\\n self.career_wins = 0\\n self.career_losses = 0\\n self.career_er = 0\\n self.career_h = 0\\n self.career_bb = 0\\n self.career_hr = 0\\n\\n # Versus stats\\n self.vs_bf = 0\\n self.vs_so = 0\\n self.vs_er = 0\\n self.vs_h = 0\\n self.vs_bb = 0\\n self.vs_hr = 0\\n\\n # Month stats\\n self.recent_bf = 0\\n self.recent_ip = 0\\n self.recent_so = 0\\n self.recent_er = 0\\n self.recent_h = 0\\n self.recent_bb = 0\\n self.recent_hr = 0\",\n \"def extra_state_attributes(self):\\n return {\\n ATTR_ATTRIBUTION: ATTRIBUTION,\\n ATTR_STATION: self.probe.get_data(\\\"station_name\\\"),\\n ATTR_UPDATED: self.probe.last_update.isoformat(),\\n }\",\n \"def set_instance_vars(self, new_vars=None):\\n if new_vars is None:\\n new_vars = Bird.default_player_values\\n\\n vars(self).update(new_vars)\",\n \"def __repr__(self):\\n name = self.name\\n prefix = \\\": \\\"\\n gen = (\\n value for value in self.init_kwargs.values() if value is not None\\n )\\n for value in gen:\\n try:\\n if issubclass(value, Player):\\n value = value.name\\n except TypeError:\\n pass\\n name = \\\"\\\".join([name, prefix, str(value)])\\n prefix = \\\", \\\"\\n return name\",\n \"def get_player_states(self, players):\\n for player in self.players.values():\\n p = players.add()\\n p.id = player.id\\n p.pos.CopyFrom(player.pos.to_protocol())\",\n \"def extract_player_data(row):\\n player = {\\n 'player': row.find('td', {'data-stat': 'player'}).find('a').text,\\n 'team': row.find('td', {'data-stat': 'team'}).text,\\n 'fantasy_pos': row.find('td', {'data-stat': 'fantasy_pos'}).text,\\n 'age': row.find('td', {'data-stat': 'age'}).text,\\n 'g': row.find('td', {'data-stat': 'g'}).text,\\n 'gs': row.find('td', {'data-stat': 'gs'}).text,\\n 'pass_cmp': row.find('td', {'data-stat': 'pass_cmp'}).text,\\n 'pass_att': row.find('td', {'data-stat': 'pass_att'}).text,\\n 'pass_yds': row.find('td', {'data-stat': 'pass_yds'}).text,\\n 'pass_td': row.find('td', {'data-stat': 'pass_td'}).text,\\n 'pass_int': row.find('td', {'data-stat': 'pass_int'}).text,\\n 'rush_att': row.find('td', {'data-stat': 'rush_att'}).text,\\n 'rush_yds': row.find('td', {'data-stat': 'rush_yds'}).text,\\n 'rush_yds_per_att': row.find(\\n 'td', {'data-stat': 'rush_yds_per_att'}\\n ).text,\\n 'rush_td': row.find('td', {'data-stat': 'rush_td'}).text,\\n 'rec': row.find('td', {'data-stat': 'rec'}).text,\\n 'rec_yds': row.find('td', {'data-stat': 'rec_yds'}).text,\\n 'rec_yds_per_rec': row.find(\\n 'td', {'data-stat': 'rec_yds_per_rec'}\\n ).text,\\n 'rec_td': row.find('td', {'data-stat': 'rec_td'}).text,\\n 'fumbles': row.find('td', {'data-stat': 'fumbles'}).text,\\n 'fumbles_lost': row.find('td', {'data-stat': 'fumbles_lost'}).text,\\n 'all_td': row.find('td', {'data-stat': 'all_td'}).text,\\n 'two_pt_md': row.find('td', {'data-stat': 'two_pt_md'}).text,\\n 'two_pt_pass': row.find('td', {'data-stat': 'two_pt_pass'}).text,\\n 'fantasy_points': row.find(\\n 'td', {'data-stat': 'fantasy_points'}\\n ).text,\\n 'fantasy_points_ppr': row.find(\\n 'td', {'data-stat': 'fantasy_points_ppr'}\\n ).text,\\n 'draftkings_points': row.find(\\n 'td', {'data-stat': 'draftkings_points'}\\n ).text,\\n 'fanduel_points': row.find(\\n 'td', {'data-stat': 'fanduel_points'}\\n ).text,\\n 'vbd': row.find('td', {'data-stat': 'vbd'}).text,\\n 'fantasy_rank_pos': row.find(\\n 'td', {'data-stat': 'fantasy_rank_pos'}\\n ).text,\\n 'fantasy_rank_overall': row.find(\\n 'td', {'data-stat': 'fantasy_rank_overall'}\\n ).text,\\n }\\n \\n # Need to handle targets column individually, since before 1992 targets were\\n # not tracked.\\n try:\\n player['targets'] = row.find('td', {'data-stat': 'targets'}).text\\n except AttributeError:\\n player['targets'] = None\\n\\n return player\",\n \"def to_raw(self) -> Dict[str, Any]:\\n if self._player:\\n raw_player = player_to_raw(self._player)\\n else:\\n raw_player = None\\n\\n if self._voice_server_update:\\n raw_voice_server_update = voice_server_update_to_raw(self._voice_server_update)\\n else:\\n raw_voice_server_update = None\\n\\n return {\\n \\\"guild_id\\\": self.__guild_id,\\n \\\"player\\\": raw_player,\\n \\\"track\\\": self._track,\\n \\\"voice_server_update\\\": raw_voice_server_update,\\n }\",\n \"def __init__(self, player1, player2):\\n # # players of the game {player1name: {color: , red_marbles:}}\\n # self._players = {player1[0]: {\\\"name\\\": player1[0], \\\"color\\\": player1[1]},\\n # player2[0]: {\\\"name\\\": player2[0], \\\"color\\\": player2[1]}}\\n # # empty board, no marbles yet\\n # self._board = self.create_board()\\n # # current player's turn\\n # self._turn = None\\n # # winner state\\n # self._winner = None\\n # # red marbles captured for each player, needs addition of black and white marbles\\n # self._captured = {player1[0]: 0, player2[0]: 0}\\n pass\",\n \"def __init__(self):\\n self.name = None\\n self.time_stamp = time()\\n self.last_win = None\\n self.wins = 0\",\n \"def __init__(self, player_control, players=None):\\r\\n self.player_control = player_control\\r\\n self.players = {} # copy for restoration\\r\\n if players is not None:\\r\\n for player in players.values():\\r\\n self.add_player(player)\",\n \"def __init__(self, player: DuneHDPlayer, name: str, unique_id: str) -> None:\\n self._player = player\\n self._media_title: str | None = None\\n self._state: dict[str, Any] = {}\\n self._attr_unique_id = unique_id\\n self._attr_device_info = DeviceInfo(\\n identifiers={(DOMAIN, unique_id)},\\n manufacturer=ATTR_MANUFACTURER,\\n name=name,\\n )\",\n \"def __init__(self, player):\\r\\n other_player = \\\"lower\\\" if player == \\\"upper\\\" else \\\"upper\\\"\\r\\n \\r\\n #set our sides \\r\\n self.player_information[\\\"us\\\"][\\\"player_side\\\"] = player\\r\\n self.player_information[\\\"them\\\"][\\\"player_side\\\"] = other_player\\r\\n\\r\\n #create our board edge and board representation\\r\\n self.board_edge = hex_boundary_getter((0,0), 4, [])\\r\\n self.board_array = generate_board()\",\n \"def players(self):\\n return self._get(\\\"players\\\")\",\n \"def update(self):\\r\\n debug.write(\\\"Querying stats for player %s\\\" % self.name, 3)\\r\\n debug.write(\\\"Is turbo mode on? %s\\\" % ({True:\\\"Yes\\\", False:\\\"No\\\"}[currentTurboMode]), 3)\\r\\n if not currentTurboMode:\\r\\n database.execute(\\\"SELECT * FROM Player WHERE UserID=?\\\", self.dbUserid)\\r\\n \\r\\n \\\"\\\"\\\" \\r\\n ~NOTE: Nasty, explicitly defining may break in future updates if I\\r\\n alter the DB structure, think of a new way to alter this.\\r\\n \\r\\n Thoughts:\\r\\n \\r\\n Make a list of the structure, then call the list and update the oldAttributes\\r\\n and currentAttributes with items from the list.\\r\\n \\\"\\\"\\\"\\r\\n result = database.fetchone()\\r\\n UserID, steamid, level, xp, credits, popup, name, lastconnected = result\\r\\n\\r\\n debug.write(\\\"Steamid: %s\\\" % steamid, 3)\\r\\n debug.write(\\\"DB UserID: %s\\\" % UserID, 3)\\r\\n debug.write(\\\"xp: %s\\\" % xp, 3)\\r\\n debug.write(\\\"Credits %s\\\" % credits, 3)\\r\\n debug.write(\\\"Level: %s\\\" % level, 3)\\r\\n \\r\\n for option in ('steamid', 'level', 'xp', 'credits', 'popup', 'name', 'lastconnected'):\\r\\n self.oldAttributes[option] = self.currentAttributes[option] = locals()[option]\\r\\n \\r\\n \\\"\\\"\\\" Retrieve the skills id and level from the database \\\"\\\"\\\"\\r\\n database.execute(\\\"SELECT name,level FROM Skill WHERE UserID=?\\\", self.dbUserid )\\r\\n \\r\\n \\\"\\\"\\\" Iterate through all the skills returned \\\"\\\"\\\"\\r\\n for skill in database.fetchall():\\r\\n \\\"\\\"\\\" Each iteration will produce a 2 itemed tuple with skillrow and level \\\"\\\"\\\"\\r\\n skillName, level = skill\\r\\n\\r\\n debug.write(\\\"Skill %s :: level %s\\\" % (skillName, level), 3)\\r\\n \\r\\n \\\"\\\"\\\" We only want to add the skill if it's currently loaded \\\"\\\"\\\"\\r\\n self.oldSkills[skillName] = self.currentSkills[skillName] = level\\r\\n \\r\\n else:\\r\\n \\\"\\\"\\\" Turbo mode is on, make the default attributes \\\"\\\"\\\" \\r\\n defaultValues = {\\r\\n \\\"level\\\" : 1,\\r\\n \\\"xp\\\" : 0,\\r\\n \\\"credits\\\" : int(startCredits),\\r\\n \\\"popup\\\" : int(popupStatus),\\r\\n \\\"lastconnected\\\" : int(time.time())\\r\\n }\\r\\n for key, value in defaultValues.iteritems():\\r\\n self.oldAttributes[key] = self.currentAttributes[key] = value\",\n \"def set_props(cont):\\n\\n\\t# Basic\\n\\town = cont.owner\\n\\t\\n\\t# Sensors\\n\\ts_keyboard = cont.sensors['keyboard']\\n\\t\\n\\t# Objects\\n\\to_group = own.groupObject\\n\\t\\t\\n\\t# Properties\\n\\tp_player = globalDict['state']['player']\\n\\tp_controls = globalDict['settings']['controls']\\n\\tup = p_controls['key_up'] in s_keyboard.inputs.keys()\\n\\tdown = p_controls['key_down'] in s_keyboard.inputs.keys()\\n\\tleft = p_controls['key_left'] in s_keyboard.inputs.keys()\\n\\tright = p_controls['key_right'] in s_keyboard.inputs.keys()\\n\\trun = p_controls['key_run'] in s_keyboard.inputs.keys()\\n\\tcrouch = p_controls['key_crouch'] in s_keyboard.inputs.keys()\\n\\t\\n\\tif o_group != None:\\n\\t\\t\\n\\t\\t#print(s_keyboard.inputs)\\n\\t\\t\\n\\t\\t# Vertical\\n\\t\\tif not up and not down or up and down:\\n\\t\\t\\tp_player['mov_v'] = 0\\n\\t\\t\\n\\t\\tif up and not down:\\n\\t\\t\\tp_player['mov_v'] = 1\\n\\t\\t\\n\\t\\tif not up and down:\\n\\t\\t\\tp_player['mov_v'] = -1\\n\\t\\t\\t\\n\\t\\t# Horizontal\\n\\t\\tif not left and not right or left and right:\\n\\t\\t\\tp_player['mov_h'] = 0\\n\\t\\t\\n\\t\\tif right and not left:\\n\\t\\t\\tp_player['mov_h'] = 1\\n\\t\\t\\n\\t\\tif not right and left:\\n\\t\\t\\tp_player['mov_h'] = -1\\n\\t\\t\\t\\n\\t\\t# None\\n\\t\\tif not run and not crouch or run and crouch:\\n\\t\\t\\tp_player['mov_run'] = 0\\n\\t\\t\\tp_player['mov_crouch'] = 0\\n\\t\\t\\t\\n\\t\\t# Run\\n\\t\\tif run and not crouch:\\n\\t\\t\\tp_player['mov_run'] = 1\\n\\t\\t\\tp_player['mov_crouch'] = 0\\n\\t\\t\\t\\n\\t\\t# Crouch\\n\\t\\tif not run and crouch:\\n\\t\\t\\tp_player['mov_run'] = 0\\n\\t\\t\\tp_player['mov_crouch'] = 1\\n\\t\\t\\t\\n\\t\\t\\n\\tpass\",\n \"def get_perfect_information(self):\\n state = {}\\n state[\\\"chips\\\"] = [self.game.players[i].in_chips for i in range(self.player_num)]\\n state[\\\"public_card\\\"] = (\\n self.game.public_card.get_index() if self.game.public_card else None\\n )\\n state[\\\"hand_cards\\\"] = [\\n self.game.players[i].hand.get_index() for i in range(self.player_num)\\n ]\\n state[\\\"current_round\\\"] = self.game.round_counter\\n state[\\\"current_player\\\"] = self.game.game_pointer\\n state[\\\"legal_actions\\\"] = self.game.get_legal_actions()\\n return state\",\n \"def _init_attributes(self):\\n if os.name == \\\"nt\\\":\\n if \\\"64\\\" in platform.architecture()[0]:\\n platform_arch = \\\"x86_64\\\"\\n elif \\\"32\\\" in platform.architecture()[0]:\\n platform_arch = \\\"i386\\\"\\n else:\\n platform_arch = platform.architecture()\\n os_ver = f\\\"Windows-{platform.win32_ver()[1]}\\\"\\n else:\\n platform_arch = platform.machine()\\n if platform.system() == \\\"Darwin\\\":\\n os_ver = f\\\"macOS-{platform.mac_ver()[0]}\\\"\\n else:\\n os_ver = \\\"-\\\".join(linux_distribution()[0:2])\\n\\n license_chunks = LICENSE.split(\\\" \\\")\\n if license_chunks[0] == \\\"GPLv2\\\":\\n client_license = \\\"GPL-2.0\\\"\\n else:\\n client_license = \\\"Commercial\\\"\\n\\n default_attributes = {\\n # Process id\\n \\\"_pid\\\": str(os.getpid()),\\n # Platform architecture\\n \\\"_platform\\\": platform_arch,\\n # OS version\\n \\\"_os\\\": os_ver,\\n # Hostname of the local machine\\n \\\"_source_host\\\": socket.gethostname(),\\n # Client's name\\n \\\"_client_name\\\": \\\"mysql-connector-python\\\",\\n # Client's version\\n \\\"_client_version\\\": \\\".\\\".join([str(x) for x in VERSION[0:3]]),\\n # Client's License identifier\\n \\\"_client_license\\\": client_license,\\n }\\n self._settings[\\\"attributes\\\"].update(default_attributes)\\n\\n if \\\"connection-attributes\\\" in self._settings:\\n for attr_name in self._settings[\\\"connection-attributes\\\"]:\\n attr_value = self._settings[\\\"connection-attributes\\\"][attr_name]\\n # Validate name type\\n if not isinstance(attr_name, str):\\n raise InterfaceError(\\n f\\\"Attribute name '{attr_name}' must be a string type\\\"\\n )\\n # Validate attribute name limit 32 characters\\n if len(attr_name) > 32:\\n raise InterfaceError(\\n f\\\"Attribute name '{attr_name}' exceeds 32 characters \\\"\\n \\\"limit size\\\"\\n )\\n # Validate names in connection-attributes cannot start with \\\"_\\\"\\n if attr_name.startswith(\\\"_\\\"):\\n raise InterfaceError(\\n \\\"Key names in 'session-connect-attributes' cannot \\\"\\n f\\\"start with '_', found: {attr_name}\\\"\\n )\\n # Validate value type\\n if not isinstance(attr_value, str):\\n raise InterfaceError(\\n f\\\"Attribute name '{attr_name}' value '{attr_value}' \\\"\\n \\\" must be a string type\\\"\\n )\\n\\n # Validate attribute value limit 1024 characters\\n if len(attr_value) > 1024:\\n raise InterfaceError(\\n f\\\"Attribute name '{attr_name}' value: '{attr_value}' \\\"\\n \\\"exceeds 1024 characters limit size\\\"\\n )\\n\\n self._settings[\\\"attributes\\\"][attr_name] = attr_value\",\n \"def _player_list(self):\\n game = self.ctrl.game\\n return game.players[self.i_to_player_id(0)], game.players[self.i_to_player_id(1)]\",\n \"def __init__(self, data):\\n # add play_guid as it sometimes doesn't exist\\n if 'play_guid' not in data:\\n data['play_guid'] = ''\\n # loop through data\\n for x in data:\\n # set information as correct data type\\n mlbgame.object.setobjattr(self, x, data[x])\",\n \"def player_from_raw(data: Dict[str, Any]) -> andesite.Player:\\n return build_from_raw(andesite.Player, data)\",\n \"async def get_self(self) -> PlayerInfo:\\n e = await self.request.request(url=f'https://users.roblox.com/v1/users/authenticated', method='get')\\n a = PlayerInfo(player_id=e['id'], request=self.request)\\n await a.update()\\n return a\",\n \"def __init__(self, name=\\\"Player\\\", resources=[0,0,0,0,0,0,0,0], xor_resources=None,\\\\\\n current_hand=None, structures=None, starting_gold=3, discounted_resources=None):\\n if structures != None:\\n self.structures = structures # by type? Should we have a structure type? \\n else:\\n self.structures = []\\n \\n self.name = name\\n self.wonders = None \\n player.west_natural= False\\n player.west_manufactured = False\\n player.east_natural= False\\n player.east_manufactured= False\\n\\n if current_hand == None:\\n self.current_hand = None\\n else:\\n self.current_hand = current_hand #I dont know if we need this\\n self.starting_gold = starting_gold\",\n \"def __init__(self,state,player=WHITE):\\n if(state==None):\\n self.gameState = dict()\\n for x in range(0,WIDTH):\\n for y in range(0,HEIGHT):\\n self.gameState[x,y] = EMPTY\\n for x in range(0,WIDTH):\\n self.gameState[x,BSTARTROW] = BLACK#Blacks starting row\\n self.gameState[x,WSTARTROW] = WHITE#Whites starting row\\n #whites.append(Board.pawn(Board.pos(x,WSTARTROW),WHITE))\\n #blacks.append(Board.pawn(Board.pos(x,BSTARTROW),BLACK))\\n else:\\n self.gameState = state\\n \\n self.whoseTurn = player\\n self.cachedWin = False # set to True in winFor() if\\n self.cachedWinner = None\",\n \"def __init__(self, min_player_count):\\n self.min_player_count = min_player_count\",\n \"def __init__(self):\\n self.get_name()\\n self.get_difficulty()\\n self.get_guesses()\\n self.get_answer()\\n self.get_wager()\\n self.chance = 0\",\n \"def setup(self):\\n header_print(self.data['intro'])\\n header_print(self.data['help'])\\n random.shuffle(self.data['draw'])\\n random.shuffle(self.data['locations'])\\n random.shuffle(self.data['events'])\\n random.shuffle(self.data['aces'])\\n random.shuffle(self.data['personalities'])\\n self.stats = {\\n 'round': 0,\\n 'powers': {\\n 'MOONS': 6,\\n 'SUNS': 6,\\n 'WAVES': 6,\\n 'LEAVES': 6,\\n 'WYRMS': 6,\\n 'KNOTS': 6,\\n },\\n 'hand': self.data['draw'][:],\\n 'discard': [],\\n 'active': [],\\n 'opponent': {},\\n }\",\n \"def gameState(self):\\n gameState = {\\\"counter\\\" : {\\\"Team1\\\" : self.counter[\\\"Team1\\\"], \\\"Team2\\\" : self.counter[\\\"Team2\\\"]},\\\\\\n \\\"lastChanged\\\" : self.lastChanged,\\\\\\n \\\"wonRounds\\\" : {\\\"Team1\\\" : self.wonRounds[\\\"Team1\\\"], \\\"Team2\\\" : self.wonRounds[\\\"Team2\\\"]},\\\\\\n \\\"wonGames\\\" : {\\\"Team1\\\" : self.wonGames[\\\"Team1\\\"], \\\"Team2\\\" : self.wonGames[\\\"Team2\\\"]},\\\\\\n \\\"currentMaxPoints\\\" : self.currentMaxPoints,\\\\\\n \\\"sidesChanged\\\" : self.sidesChanged,\\\\\\n \\\"playerPositions\\\" : self.playerPositions,\\\\\\n \\\"servePosition\\\" : self.servePosition,\\\\\\n \\\"playerColors\\\" : self.playerColors,\\\\\\n \\\"undoStack\\\" : self._undoStack,\\\\\\n \\\"redoStack\\\" : self._redoStack,\\\\\\n \\\"observers\\\" : self.__observers,\\\\\\n \\\"gameName\\\" : self._getGameName()}\\n return gameState\",\n \"def __init__(self, *args, **kwargs):\\n super(Player, self).__init__(*args, **kwargs)\",\n \"def NowPlaying(self):\\n self.logger.debug(\\\"Fetching currently playing information\\\")\\n try:\\n xbmc = Server(self.url('/jsonrpc', True))\\n player = xbmc.Player.GetActivePlayers()[0]\\n playerid = player['playerid']\\n\\n if player['type'] == 'video':\\n playerprop = ['speed', 'position', 'time', 'totaltime',\\n 'percentage', 'subtitleenabled', 'currentsubtitle',\\n 'subtitles', 'currentaudiostream', 'audiostreams']\\n itemprop = ['thumbnail', 'showtitle', 'season', 'episode', 'year', 'fanart']\\n\\n elif player['type'] == 'audio':\\n playerprop = ['speed', 'position', 'time', 'totaltime', 'percentage']\\n itemprop = ['thumbnail', 'title', 'artist', 'album', 'year', 'fanart']\\n\\n app = xbmc.Application.GetProperties(properties=['muted', 'volume'])\\n player = xbmc.Player.GetProperties(playerid=playerid, properties=playerprop)\\n item = xbmc.Player.GetItem(playerid=playerid, properties=itemprop)\\n\\n return {'playerInfo': player, 'itemInfo': item, 'app': app}\\n except:\\n self.logger.debug(\\\"Unable to fetch currently playing information!\\\")\\n return\",\n \"def init_meta(self):\\n self.meta = {}\\n # Required (core)\\n self.meta['ra'] = dict(ext=0, card='RA')\\n self.meta['dec'] = dict(ext=0, card='DEC')\\n self.meta['target'] = dict(ext=0, card='OBJECT')\\n self.meta['decker'] = dict(ext=0, card=None, default='default')\\n self.meta['dichroic'] = dict(ext=0, card=None, default='default')\\n self.meta['binning'] = dict(ext=0, card=None, default='1,1')\\n\\n self.meta['mjd'] = dict(ext=0, card='ACQTIME')\\n self.meta['exptime'] = dict(ext=0, card='EXPTIME')\\n self.meta['airmass'] = dict(ext=0, card='AIRMASS')\\n # Extras for config and frametyping\\n self.meta['dispname'] = dict(ext=0, card='GRISM')\\n self.meta['idname'] = dict(ext=0, card='OBSTYPE')\\n self.meta['instrument'] = dict(ext=0, card='INSTRUME')\",\n \"def update(self, player_info):\\n self.seat = player_info.get(\\\"seat\\\", -1)\\n self.name = player_info.get(\\\"name\\\", \\\"unknown\\\")\\n self.sit_out = player_info.get(\\\"sit_out\\\", True)\",\n \"def attributes_to_save(self):\\r\\n return ['initial_pos', 'height', 'width']\",\n \"def display_make_a_player():\\n display_head_menu(\\\"Création du joueur\\\")\\n player_dict = {}\\n player_dict.update({\\\"lastname\\\": display(\\\"Nom: \\\")})\\n player_dict.update({\\\"firstname\\\": display(\\\"Prénom: \\\")})\\n player_dict.update({\\\"gender\\\": display(\\\"Genre : (homme/femme)\\\", \\\"gender\\\")})\\n player_dict.update({\\\"date_of_birth\\\": display(\\\"Date de naissance: \\\", \\\"date\\\")})\\n player_dict.update({\\\"ranking\\\": display(\\\"Classement : \\\", \\\"natural\\\")})\\n return player_dict\",\n \"def get_attributes(self):\\n\\n _attributes = (self.survival_id, self.record_id, self.name,\\n self.source_id, self.failure_date, self.left_interval,\\n self.right_interval, self.status_id, self.quantity,\\n self.tbf, self.mode_type_id, self.nevada_chart,\\n self.ship_date, self.number_shipped, self.return_date,\\n self.number_returned, self.user_float_1,\\n self.user_float_2, self.user_float_3,\\n self.user_integer_1, self.user_integer_2,\\n self.user_integer_3, self.user_string_1,\\n self.user_string_2, self.user_string_3)\\n\\n return _attributes\",\n \"def get_player_items(self):\\n return self.player.items\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7445393","0.6738495","0.6638327","0.6635758","0.6523638","0.64918613","0.6424853","0.6402643","0.63063866","0.6300941","0.61768234","0.6132734","0.6125309","0.61147493","0.6112685","0.6096234","0.609568","0.60428095","0.5956577","0.59536284","0.5951785","0.5929823","0.59168756","0.59136456","0.59047043","0.5902413","0.589541","0.5881627","0.58593225","0.585183","0.58278316","0.5807542","0.5806623","0.58019495","0.5796621","0.5785985","0.578543","0.57797796","0.5778681","0.5776771","0.5773339","0.57493913","0.5713972","0.5711771","0.5681825","0.56476194","0.5637532","0.56283134","0.56179863","0.56165045","0.5614505","0.5574869","0.55692476","0.5564743","0.5562631","0.55223125","0.5519948","0.55162835","0.5515262","0.550777","0.55061054","0.5502685","0.5493999","0.5492018","0.5476411","0.54731435","0.5464369","0.546302","0.54591495","0.54574","0.54572725","0.54459834","0.54448605","0.5443488","0.5442769","0.5434162","0.5434126","0.5428155","0.5426766","0.54245144","0.5424513","0.5417914","0.5413568","0.54135245","0.5413204","0.5409745","0.540737","0.5400256","0.53999615","0.5398908","0.5397487","0.53965896","0.53946286","0.53927124","0.53851575","0.5379751","0.5373791","0.5365025","0.5361564","0.53610986"],"string":"[\n \"0.7445393\",\n \"0.6738495\",\n \"0.6638327\",\n \"0.6635758\",\n \"0.6523638\",\n \"0.64918613\",\n \"0.6424853\",\n \"0.6402643\",\n \"0.63063866\",\n \"0.6300941\",\n \"0.61768234\",\n \"0.6132734\",\n \"0.6125309\",\n \"0.61147493\",\n \"0.6112685\",\n \"0.6096234\",\n \"0.609568\",\n \"0.60428095\",\n \"0.5956577\",\n \"0.59536284\",\n \"0.5951785\",\n \"0.5929823\",\n \"0.59168756\",\n \"0.59136456\",\n \"0.59047043\",\n \"0.5902413\",\n \"0.589541\",\n \"0.5881627\",\n \"0.58593225\",\n \"0.585183\",\n \"0.58278316\",\n \"0.5807542\",\n \"0.5806623\",\n \"0.58019495\",\n \"0.5796621\",\n \"0.5785985\",\n \"0.578543\",\n \"0.57797796\",\n \"0.5778681\",\n \"0.5776771\",\n \"0.5773339\",\n \"0.57493913\",\n \"0.5713972\",\n \"0.5711771\",\n \"0.5681825\",\n \"0.56476194\",\n \"0.5637532\",\n \"0.56283134\",\n \"0.56179863\",\n \"0.56165045\",\n \"0.5614505\",\n \"0.5574869\",\n \"0.55692476\",\n \"0.5564743\",\n \"0.5562631\",\n \"0.55223125\",\n \"0.5519948\",\n \"0.55162835\",\n \"0.5515262\",\n \"0.550777\",\n \"0.55061054\",\n \"0.5502685\",\n \"0.5493999\",\n \"0.5492018\",\n \"0.5476411\",\n \"0.54731435\",\n \"0.5464369\",\n \"0.546302\",\n \"0.54591495\",\n \"0.54574\",\n \"0.54572725\",\n \"0.54459834\",\n \"0.54448605\",\n \"0.5443488\",\n \"0.5442769\",\n \"0.5434162\",\n \"0.5434126\",\n \"0.5428155\",\n \"0.5426766\",\n \"0.54245144\",\n \"0.5424513\",\n \"0.5417914\",\n \"0.5413568\",\n \"0.54135245\",\n \"0.5413204\",\n \"0.5409745\",\n \"0.540737\",\n \"0.5400256\",\n \"0.53999615\",\n \"0.5398908\",\n \"0.5397487\",\n \"0.53965896\",\n \"0.53946286\",\n \"0.53927124\",\n \"0.53851575\",\n \"0.5379751\",\n \"0.5373791\",\n \"0.5365025\",\n \"0.5361564\",\n \"0.53610986\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6587913"},"document_rank":{"kind":"string","value":"4"}}},{"rowIdx":81470,"cells":{"query":{"kind":"string","value":"Set up some molecules, residues, and spins for testing."},"document":{"kind":"string","value":"def setUp(self):\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Name the first molecule.\n cdp.mol[0].name = 'Ap4Aase'\n\n # Add a second molecule to the system.\n cdp.mol.add_item(mol_name='RNA')\n\n # Add two more residues to the first molecule (and set the residue number of the first).\n cdp.mol[0].res[0].num = 1\n cdp.mol[0].res.add_item(res_num=2, res_name='Glu')\n cdp.mol[0].res.add_item(res_num=4, res_name='Pro')\n\n # Add some spin info to this molecule.\n cdp.mol[0].res[0].spin[0].name = 'NH'\n cdp.mol[0].res[0].spin[0].num = 60\n cdp.mol[0].res[1].spin[0].name = 'NH'\n cdp.mol[0].res[1].spin[0].num = 63\n\n # Add one more residue to the second molecule (and set the residue number of the first).\n cdp.mol[1].res[0].num = -5\n cdp.mol[1].res.add_item(res_num=-4)\n\n # Add a second set of spins to the second molecule (naming the first set first).\n cdp.mol[1].res[0].spin[0].name = 'C8'\n cdp.mol[1].res[1].spin[0].name = 'C8'\n cdp.mol[1].res[0].spin.add_item(spin_name='N5')\n cdp.mol[1].res[1].spin.add_item(spin_name='N5')\n cdp.mol[1].res[1].spin.add_item(spin_name='2H', spin_num=132)\n\n # Deselect a number of spins.\n cdp.mol[0].res[0].spin[0].select = 0\n cdp.mol[0].res[2].spin[0].select = 0\n cdp.mol[1].res[0].spin[0].select = 0\n cdp.mol[1].res[1].spin[1].select = 0\n\n # Update the metadata.\n mol_res_spin.metadata_update()"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def setup(self):\n insts = []\n for i in range(5):\n insts.append(pysat.Instrument('pysat', 'testing',\n clean_level='clean'))\n self.testC = pysat.Constellation(instruments=insts)\n self.testI = pysat.Instrument('pysat', 'testing', clean_level='clean')\n self.bounds = (dt.datetime(2008, 1, 1), dt.datetime(2008, 1, 3))\n\n # Apply bounds to all Instruments in Constellation, and solo Instrument.\n self.testC.bounds = self.bounds\n self.testI.bounds = self.bounds\n\n # Define variables for 1D testing\n self.one_d_vars = ['dummy1', 'dummy2', 'dummy3']\n self.unequal_one_d_vars = []\n\n return","def setup(self):\n insts = []\n for i in range(2):\n r_date = dt.datetime(2009, 1, i + 1)\n insts.append(pysat.Instrument('pysat', 'testing',\n clean_level='clean',\n root_date=r_date))\n self.testC = pysat.Constellation(instruments=insts)\n self.testI = pysat.Instrument('pysat', 'testing', clean_level='clean')\n self.bounds = (dt.datetime(2008, 1, 1), dt.datetime(2008, 1, 3))\n\n # Apply bounds to all Instruments in Constellation, and solo Instrument.\n self.testC.bounds = self.bounds\n self.testI.bounds = self.bounds\n\n # Define variables for 1D testing. A more limited set that only\n # depends upon 'mlt'. Other variables also include longitude, which\n # can differ between instruments when only binning by 'mlt'.\n self.one_d_vars = ['dummy1']\n self.unequal_one_d_vars = ['dummy2', 'dummy3']\n\n return","def setup(self):\n\n self.insts = []\n self.testInst = pysat.Instrument('pysat', 'testing2D',\n clean_level='clean')\n self.testInst.bounds = (dt.datetime(2008, 1, 1),\n dt.datetime(2008, 1, 3))\n self.insts.append(self.testInst)\n self.insts.append(self.testInst)\n\n self.dname = 'series_profiles'\n self.test_vals = np.arange(50) * 1.2\n\n self.testC = pysat.Constellation(instruments=self.insts)\n\n return","def setup_simulation(self, **kwargs):\n\n self.distance = self.config[\"site\"][\"distance\"]\n self.num_substations = self.config[\"num_substations\"]\n\n self.initialize_substructure_production()\n self.initialize_installation_vessel()","def setup_class(self):\n args = {'pdb_path':'/sdf/home/a/apeck/tomoxtal/examples/input/193l.pdb', 'resolution':6.0, 'size':250}\n\n # generate structure factors and retrieve associated cell information\n sf = cctbx_tools.reference_sf(args['pdb_path'], args['resolution'], expand_to_p1=True)\n sf_data = cctbx_tools.reformat_sf(sf)\n sg_symbol, sg_no, self.cell, cs = cctbx_tools.unit_cell_info(args['pdb_path'])\n \n # add random phase shifts\n hklIp1, hklIp2, hklIp3 = sf_data.copy(), sf_data.copy(), sf_data.copy()\n hklIp2[:,-1], self.shifts2 = phases_utils.add_random_phase_shift(sf_data[:,:3], sf_data[:,-1])\n hklIp3[:,-1], self.shifts3 = phases_utils.add_random_phase_shift(sf_data[:,:3], sf_data[:,-1])\n\n # retain subset of Millers\n for data in [hklIp1,hklIp2,hklIp3]:\n keep_idx = np.unique(np.random.randint(0, high=data.shape[0], size=args['size']))\n data = data[keep_idx]\n \n self.data1, self.data2, self.data3 = hklIp1, hklIp2, hklIp3\n fshifts_list = np.random.uniform(size=(4,3))\n self.fshifts_list = np.vstack((fshifts_list, 1-self.shifts2, 1-self.shifts3))","def setUp(self):\n from ampscan.core import AmpObject\n # Load 2 spheres with radius 1, and 1.2\n stl_path = get_path(\"stl_file_5.stl\") # R=1\n self.amp1 = AmpObject(stl_path)\n stl_path = get_path(\"stl_file_4.stl\") # R=1.2\n self.amp2 = AmpObject(stl_path)\n stl_path = get_path(\"stl_file.stl\")\n self.amp3 = AmpObject(stl_path)\n self.amp4 = AmpObject(stl_path)\n stl_path = get_path(\"cone1.stl\")\n self.cone1 = AmpObject(stl_path)\n stl_path = get_path(\"cone2.stl\")\n self.cone2 = AmpObject(stl_path)","def setUp(self):\r\n self.value_for_seed = 20\r\n\r\n # Single comp.\r\n self.labels1 = ['foo', 'bar']\r\n self.dists1 = [[1, 2, 3], [7, 8]]\r\n\r\n # Multiple comps.\r\n self.labels2 = ['foo', 'bar', 'baz']\r\n self.dists2 = [[1, 2, 3], [7, 8], [9, 10, 11]]\r\n\r\n # Too few obs.\r\n self.labels3 = ['foo', 'bar', 'baz']\r\n self.dists3 = [[1], [7], [9, 10, 11]]","def setUp(self):\n lang = self._sim_lang\n self._simulator = self._find_resource(\n f\"drake/examples/hardware_sim/hardware_sim_{lang}\")\n self._example_scenarios = self._find_resource(\n \"drake/examples/hardware_sim/example_scenarios.yaml\")\n self._test_scenarios = self._find_resource(\n \"drake/examples/hardware_sim/test/test_scenarios.yaml\")\n self._default_extra = {\n # For our smoke test, exit fairly quickly.\n \"simulation_duration\": 0.0625,\n }","def _setup_self(self, model_num =0):\n self.all_residues = self._setup_all_residues(model_num) #vector1 of Bio Residues\n self.pdb_info = self._setup_pdb_info() #PDBInfo to map the vector1\n self.peptide_bond_distances = self._setup_peptide_bond_distances() #map of bond distances to next residue in pose.","def setUp(self):\n self.size = 5\n self.parking_lot = CarSlots(self.size)\n self.controller = Controller(self.parking_lot)","def setUp(self):\n np.random.seed(1234)\n\n _TEST_FILE_NAME = 'AHN3.las'\n _TEST_DATA_SOURCE = 'testdata'\n\n _CYLINDER = InfiniteCylinder(4)\n _PC_260807 = load(os.path.join(_TEST_DATA_SOURCE, _TEST_FILE_NAME))\n _PC_1000 = copy_point_cloud(_PC_260807, array_mask=(\n np.random.choice(range(len(_PC_260807[keys.point]['x']['data'])), size=1000, replace=False)))\n _1000_NEIGHBORHOODS_IN_260807 = list(compute_neighbors.compute_neighborhoods(_PC_260807, _PC_1000, _CYLINDER))\n\n self.point_cloud = _PC_260807\n self.neigh = _1000_NEIGHBORHOODS_IN_260807","def setUp(self):\n self.s = Simulation()\n self.s['Retina']=GeneratorSheet(nominal_density=4.0)\n self.s['V1']= CFSheet(nominal_density=4.0)\n self.s['V2'] = CFSheet(nominal_density=4.0)\n\n self.s.connect('Retina','V1',delay=0.5,connection_type=CFProjection,\n name='RtoV1',learning_fn=CFPLF_Hebbian())\n\n self.s.connect('Retina','V2',delay=0.5,connection_type=CFProjection,\n name='RtoV2',learning_fn=CFPLF_Hebbian())","def test_setup_smiles(self):\n from openeye.oechem import OEMolToSmiles\n\n with mmtools.utils.temporary_directory() as tmp_dir:\n yaml_content = \"\"\"\n ---\n options:\n output_dir: {}\n setup_dir: .\n molecules:\n take-first:\n filepath: {}\n antechamber: {{charge_method: bcc}}\n leap: {{parameters: leaprc.gaff}}\n select-second:\n filepath: {}\n antechamber: {{charge_method: bcc}}\n leap: {{parameters: leaprc.gaff}}\n select: 1\n \"\"\".format(tmp_dir, self.smiles_path, self.smiles_path)\n yaml_content = textwrap.dedent(yaml_content)\n exp_builder = ExperimentBuilder(yaml_content)\n\n for i, mol_id in enumerate(['take-first', 'select-second']):\n # The molecule now is neither set up nor processed\n is_setup, is_processed = exp_builder._db.is_molecule_setup(mol_id)\n assert is_setup is False\n assert is_processed is False\n\n # The single SMILES has been converted to mol2 file\n exp_builder._db._setup_molecules(mol_id)\n mol2_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR, mol_id, mol_id + '.mol2')\n assert os.path.exists(os.path.join(mol2_path))\n assert os.path.getsize(os.path.join(mol2_path)) > 0\n\n # The mol2 represents the right molecule\n csv_smiles_str = pipeline.read_csv_lines(self.smiles_path, lines=i).strip().split(',')[1]\n mol2_smiles_str = OEMolToSmiles(utils.load_oe_molecules(mol2_path, molecule_idx=0))\n assert mol2_smiles_str == csv_smiles_str\n\n # The molecule now both set up and processed\n is_setup, is_processed = exp_builder._db.is_molecule_setup(mol_id)\n assert is_setup is True\n assert is_processed is True\n\n # A new instance of ExperimentBuilder is able to resume with correct molecule\n exp_builder = ExperimentBuilder(yaml_content)\n is_setup, is_processed = exp_builder._db.is_molecule_setup(mol_id)\n assert is_setup is True\n assert is_processed is True","def setup(self):\n self.testInst = pysat.Instrument('pysat', 'testing',\n clean_level='clean')\n self.bounds1 = (dt.datetime(2008, 1, 1), dt.datetime(2008, 1, 3))\n self.bounds2 = (dt.datetime(2009, 1, 1), dt.datetime(2009, 1, 2))\n\n self.long_bins = [0., 360., 24]\n self.mlt_bins = [0., 24., 24]\n self.auto_bin = True\n\n return","def setup(self):\n # define misfit function and adjoint source generator\n self.misfit = getattr(misfit, PAR.MISFIT)\n self.adjoint = getattr(adjoint, PAR.MISFIT)\n\n # define seismic data reader and writer\n self.reader = getattr(readers, PAR.READER)\n self.writer = getattr(writers, PAR.WRITER)\n\n # prepare channels list\n self.channels = []\n for char in PAR.CHANNELS:\n self.channels += [char]","def _setup_simulation(self\n ) -> None:\n pass","def setUpClass(cls):\n np.random.seed(2019)\n # So the 1 st row of the first random number array, random.rand(500, 3)\n # will be [0.90348221, 0.39308051, 0.62396996]\n # Accordingly, the first row of\n # coordinates = (0.5 - np.random.rand(500, 3)) * box_length\n # should be [-3.31690899, 0.87895379, -1.01912071]\n cls.sys_obj = monte_carlo.SystemSetup()\n cls.energy = energy.Energy()\n cls.parser = monte_carlo.initialize()\n cls.sim = monte_carlo.MonteCarlo(\n cls.sys_obj, cls.energy, cls.parser)\n np.random.seed()","def setup(self):\n\n self.testInst = pysat.Instrument('pysat', 'testing',\n clean_level='clean')\n self.testInst.bounds = (dt.datetime(2008, 1, 1),\n dt.datetime(2008, 1, 3))\n\n self.bounds1 = (dt.datetime(2008, 1, 1), dt.datetime(2008, 1, 3))\n self.bounds2 = (dt.datetime(2009, 1, 1), dt.datetime(2009, 1, 2))\n\n self.long_bins = np.linspace(0., 360., 25)\n self.mlt_bins = np.linspace(0., 24., 25)\n\n self.auto_bin = False\n\n return","def setUp(self):\n self.supvisors = DummySupvisors()","def setUp(self):\n\n self.veh = Vehicle(0, 0)\n self.R = Random(seed)","def _set_up():\n repl._setUp = self.setUp","def setUp(self):\n\n self.params = master_phil.extract()\n\n self.params.input.xtal_name = \"FALZA-x0085\"\n self.params.input.in_path = os.path.join(\n os.path.realpath(\"./test/resources\"), self.params.input.xtal_name\n )\n self.params.validate.input.base_mtz = os.path.join(\n self.params.input.in_path, \"FALZA-x0085.free.mtz\"\n )\n self.params.input.mtz = os.path.join(\n self.params.input.in_path, \"FALZA-x0085.free.mtz\"\n )\n self.params.input.pdb = os.path.join(self.params.input.in_path, \"refine.pdb\")\n self.params.output.out_dir = os.path.realpath(\"./test/output\")\n self.params.output.log_dir = os.path.realpath(\n os.path.join(\"./test/output\", \"logs\")\n )\n self.params.exhaustive.options.step = 0.05","def setUp(self):\n\n self.params = master_phil.extract()\n\n self.params.input.xtal_name = \"FALZA-x0085\"\n\n self.params.input.in_path = os.path.join(\n os.path.realpath(\"./test/resources\"), self.params.input.xtal_name\n )\n\n self.params.validate.input.base_mtz = os.path.join(\n self.params.input.in_path, \"FALZA-x0085.free.mtz\"\n )\n\n self.params.input.mtz = os.path.join(\n self.params.input.in_path, \"FALZA-x0085.free.mtz\"\n )\n\n self.params.input.pdb = os.path.join(self.params.input.in_path, \"refine.pdb\")","def setup(self):\n self.testInst = pysat.Instrument('pysat', 'testing_xarray',\n clean_level='clean')\n self.bounds1 = (dt.datetime(2008, 1, 1), dt.datetime(2008, 1, 3))\n self.bounds2 = (dt.datetime(2009, 1, 1), dt.datetime(2009, 1, 2))\n\n self.long_bins = [0., 360., 24]\n self.mlt_bins = [0., 24., 24]\n self.auto_bin = True\n\n return","def setUp(self):\n self.testdatapath = os.path.join(mkdtemp())\n self.testfilenames = [\n os.path.join(self.testdatapath, \"0035.nc\"),\n os.path.join(self.testdatapath, \"0107.nc\")\n ]\n\n self.gpis = [1, 10, 11, 12]\n reg_grid = grids.genreg_grid().to_cell_grid()\n self.grid = reg_grid.subgrid_from_gpis(self.gpis)","def setUp(self):\n self.sc = init_orca_context(cores=4)","def setup( self ):","def setUp(self):\n self.compound = PyFBA.metabolism.Compound(\"t1\", \"test compound\")\n self.compound.abbreviation = \"Cool\"\n self.compound.add_attribute('What', \"Everything\")\n self.compound_with_loc = PyFBA.metabolism.CompoundWithLocation.from_compound(self.compound, \"extracellular\")","def setUp(self):\n # Explicitly empty the list of segment input files,\n # otherwise they hang around from previous tests.\n Segment._input_files = {}\n self.segment = Segment(\n file=self.EXPECTED_INPUT_FILE,\n punch_in=self.EXPECTED_PUNCH_IN,\n punch_out=self.EXPECTED_PUNCH_OUT,\n input_stream=self.EXPECTED_INPUT_STREAM)\n self.expected_input_options = [\n \"-ss\", str(self.EXPECTED_PUNCH_IN.total_seconds()),\n \"-t\", str(self.EXPECTED_DURATION),\n \"-i\", self.EXPECTED_INPUT_FILE\n ]\n self.expected_output_options = []","def setUp(self):\n super(PlayTests, self).setUp(\n \"tests/data/shakespeare/\", \"structure.json\", \"brief_example.xml\")","def setUp(self):\n import protolibs.ics_servers as ics_servers\n from point import Point\n from configobj import ConfigObj\n\n # Get config file\n configfile = '/'.join(['sims', 'rtutank', 'config'])\n config=ConfigObj(infile=configfile, unrepr=True)\n self.config = config\n #Set global variable devconfig here \n devconfig=config['vdevs']['slave'] \n\n ##--Set up points\n points={}\n for p in devconfig['points']:\n points.update( { p['name'] : Point(**p) } ) \n #The ** treats the p dictionary as the arguments to the Point class\n self.server = ics_servers.ModbusRTU(devconfig['icsifaces'][0], points.values())\n self.server.start()","def do_setup_pocs(self, *arg):\n args, kwargs = string_to_params(*arg)\n simulator = kwargs.get('simulator', [])\n print_info(\"Simulator: {}\".format(simulator))\n\n try:\n self.pocs = POCS(simulator=simulator)\n self.pocs.initialize()\n except error.PanError as e:\n\n pass","def setup():\n global RBD_POOL, RBD_STORAGE_CLASS, RBD_SECRET, CEPHFS_OBJ, \\\n CEPHFS_STORAGE_CLASS, CEPHFS_SECRET, RBD_PVC, CEPHFS_PVC\n log.info(\"Creating RBD Pool\")\n RBD_POOL = helpers.create_ceph_block_pool()\n\n log.info(\"Creating RBD Secret\")\n RBD_SECRET = helpers.create_secret(constants.CEPHBLOCKPOOL)\n\n log.info(\"Creating RBD StorageClass\")\n RBD_STORAGE_CLASS = helpers.create_storage_class(\n constants.CEPHBLOCKPOOL, RBD_POOL.name, RBD_SECRET.name\n )\n\n log.info(\"Creating CephFilesystem\")\n CEPHFS_OBJ = helpers.create_cephfilesystem()\n\n log.info(\"Creating FS Secret\")\n CEPHFS_SECRET = helpers.create_secret(constants.CEPHFILESYSTEM)\n\n log.info(\"Creating FS StorageClass\")\n CEPHFS_STORAGE_CLASS = helpers.create_storage_class(\n constants.CEPHFILESYSTEM, helpers.get_cephfs_data_pool_name(),\n CEPHFS_SECRET.name\n )\n\n log.info(\"Creating RBC PVC\")\n RBD_PVC = helpers.create_pvc(sc_name=RBD_STORAGE_CLASS.name)\n\n log.info(\"Creating CephFs PVC\")\n CEPHFS_PVC = helpers.create_pvc(sc_name=CEPHFS_STORAGE_CLASS.name)","def setUp(self):\n\n self.sold = Soldier(0, 0)\n self.R = Random(seed)","def setUp(self):\n\n self.hw = HMMERWrapper\n\n modpath = os.path.abspath(os.path.dirname(__file__))\n self.seqfile = os.path.join(modpath, 'data', 'P00929.fasta')\n self.badfile = os.path.join(modpath, 'data', 'bad.fasta')","def setUp(self):\n self.number_of_tests = 20 # number of pseudo-random seeds\n self.max_nq = 2 # maximal number of qubits to check","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setup(self):\n pass","def setUp(self):\n # obtain separate logs\n self.update_log_file_names()\n # Start the servers and agents\n super(MdtestBase, self).setUp()\n\n # Get the parameters for Mdtest\n self.mdtest_cmd = MdtestCommand()\n self.mdtest_cmd.get_params(self)\n self.processes = self.params.get(\"np\", '/run/mdtest/client_processes/*')\n self.manager = self.params.get(\"manager\", '/run/mdtest/*', \"MPICH\")","def setup_pymol():\n pymol.finish_launching() # Prevent threading errors\n # Configure global settings\n cmd.set('scene_buttons', 1)\n cmd.set('matrix_mode', 1)\n cmd.set('movie_panel', 1)\n # Configure quality settings\n cmd.mset(\"1 x500\")\n cmd.set('ray_trace_frames', 1)\n cmd.viewport(800, 800)","def test_set_molecule(self):\n mol = Molecule.from_smiles(\"CCO\")\n atom = Atom(6, 0, False)\n atom.molecule = mol","def setUp(self):\n # generate lattice\n self.lattice = lattice.Lattice()\n self.lattice.addAtom(\"He\", [0,0,0], 0)\n self.lattice.addAtom(\"He\", [2,0,0], 0)\n self.lattice.addAtom(\"He\", [0,2,0], 0)\n self.lattice.addAtom(\"He\", [0,0,2], 0)\n self.lattice.addAtom(\"He\", [9,9,9], 0)\n self.lattice.addAtom(\"He\", [2,2,0], 0)\n self.lattice.addAtom(\"He\", [2,0,2], 0)\n self.lattice.addAtom(\"He\", [0,2,2], 0)\n self.lattice.addAtom(\"He\", [2,2,2], 0)\n \n # indexes of cluster atoms\n self.bigClusterIndexes = [0,1,2,3,5,6,7,8]\n self.smallClusterIndexes = [4]\n \n # filter\n self.filter = clusterFilter.ClusterFilter(\"Cluster\")","def setUp(self):\n import protolibs.ics_servers as ics_servers\n from point import Point\n from configobj import ConfigObj\n\n # Get config file\n configfile = '/'.join(['sims', 'tcptank', 'config'])\n config=ConfigObj(infile=configfile, unrepr=True)\n self.config = config\n #Set global variable devconfig here \n devconfig=config['vdevs']['slave'] \n\n ##--Set up points\n points={}\n for p in devconfig['points']:\n points.update( { p['name'] : Point(**p) } ) \n #The ** treats the p dictionary as the arguments to the Point class\n self.server = ics_servers.ModbusTCP( devconfig['icsifaces'][0], points.values() )\n self.server.start()","def setUp(self):\n\n self.eps = 0.001 # Accept 0.1 % relative error\n\n self.RSISE = Point(-35.27456, 149.12065)\n self.Home = Point(-35.25629, 149.12494) # 28 Scrivener Street, ACT\n self.Syd = Point(-33.93479, 151.16794) # Sydney Airport\n self.Nadi = Point(-17.75330, 177.45148) # Nadi Airport\n self.Kobenhavn = Point(55.70248, 12.58364) # Kobenhavn, Denmark\n self.Muncar = Point(-8.43, 114.33) # Muncar, Indonesia","def initialise_sim(self):\n pass","def setUp(self):\n self.sampler = {\n \"name\": \"samplername\",\n \"backend_name\": \"\",\n \"backend_header\": \"\",\n \"backend_prefix\": \"\",\n \"backend_suffix\": \"\",\n \"backend_footer\": \"\",\n \"ncores\": 2,\n \"threads_per_core\": 1,\n \"omp_enabled\": True,\n \"papi_enabled\": True,\n \"papi_counters_max\": 2,\n \"papi_counters_avail\": (\"C1\", \"C2\", \"C3\"),\n \"kernels\": {\"dgemm\": (\n 'dgemm', 'char*', 'char*', 'int*', 'int*', 'int*', 'double*',\n 'double*', 'int*', 'double*', 'int*', 'double*', 'float*',\n 'int*'\n )},\n \"nt_max\": random.randint(1, 10),\n \"exe\": \"x\"\n }\n self.i = Symbol(\"i\")\n self.j = Symbol(\"j\")\n self.k = Symbol(\"k\")\n self.ns = [random.randint(1, 100) for _ in range(5)]","def setUp(self):\n self.testdatapath = os.path.join(mkdtemp())\n self.testfilenames = [os.path.join(self.testdatapath, \"0001.nc\")]\n\n self.gpis = [1, 10, 11, 12]\n self.lons = [0, 0, 1, 1]\n self.lats = [1, 1, 0, 0]\n self.cells = [1, 1, 1, 1]\n self.grid = grids.CellGrid(self.lons, self.lats, self.cells, self.gpis)","def setUp(self):\n self.pgrid = ProcessorGrid(MPI.COMM_WORLD)\n\n m = mpisync(randint)(1, 500)\n n = mpisync(randint)(1, 500)\n p = mpisync(randint)(1, 4)\n q = mpisync(randint)(1, 4)\n dtype = mpisync(choice)([np.int_, np.float_, np.complex])\n print(\"m = {}, n = {}, p = {}, q = {}, dtype = {}\".format(\n m, n, p, q, dtype\n ))\n self.m, self.n, self.p, self.q, self.dtype = m, n, p, q, dtype\n self.mat = DistributedMatrix(self.pgrid, [m, n, p, q], dtype)","def setup(self) -> None:","def setup(self):\n\n self.points = [[0.360502, 0.535494],\n [0.476489, 0.560185],\n [0.503125, 0.601218],\n [0.462382, 0.666667],\n [0.504702, 0.5]]\n self.max_neighbors = 4\n self.beta = 1\n self.graph = 'beta skeleton'\n self.edges = [0, 1, 0, 2, 0, 3, 0, 4,\n 1, 3, 1, 4,\n 2, 3, 2, 4,\n 3, 4]","def setUp(self):\n #width, height,obs_list, zombie_list, human_list\n self.apoc_1 = Apocalypse(5,5, [(1,1)], [(2,2)], [(4,4)])\n self.apoc_2 = Apocalypse(3,3, [(0,0)], [(1,1),(2,2)], [(0,1),(1,0),(1,1)])\n self.apoc_3 = Apocalypse(1,1, [], [], [])","def setup(self):\n self.score = 0\n self.lives = 3\n self.state = GameStates.RUNNING\n self.focus_word = None\n \n self.star_list = set()\n self.word_list = set()\n\n for _ in range(5):\n self.create_word()\n for _ in range(25):\n self.create_star()","def setup(self):\n\t\tpass","def setUp(cls):\n cls.directory = os.path.join(os.path.dirname(os.path.dirname(rmgpy.__file__)), 'examples', 'arkane')\n cls.level_of_theory = LevelOfTheory(\"cbs-qb3\")\n cls.frequencyScaleFactor = 0.99\n cls.useHinderedRotors = False\n cls.useBondCorrections = True","def setUp(self):\n # Start the servers and agents\n super().setUp()\n\n self.obj_class = self.params.get(\"dfs_oclass\", '/run/ior/objectclass/*')\n self.ior_chu_trs_blk_size = self.params.get(\n \"chunk_block_transfer_sizes\", '/run/ior/*')\n # Fail IOR test in case of Warnings\n self.fail_on_warning = True\n self.server_count = len(self.hostlist_servers) * 2\n # Create the Pool\n self.create_pool_max_size()\n self.update_ior_cmd_with_pool()","def setup(self):\n self.testInst = pysat.Instrument('pysat', 'testing2D',\n clean_level='clean')\n self.testInst.bounds = (dt.datetime(2008, 1, 1),\n dt.datetime(2008, 1, 3))\n self.dname = 'alt_profiles'\n self.test_vals = np.arange(50) * 1.2\n self.test_fracs = np.arange(50) / 50.0\n\n return","def setup(self, name, chem, conc, Kw, D, x_coord, y_coord, dx, dy, dz): \r\n self.name = name\r\n \r\n self.chem = chem # a list of objectives of the class Chemical\r\n if chem is None:\r\n self.nSpecies = 0\r\n elif type(chem) is not list :\r\n self.nSpecies = 1\r\n else :\r\n self.nSpecies = len(chem) # Number of chemcial species\r\n self.conc = conc # The dependent variable (named 'conc') of interest\r\n self.Kw = Kw\r\n self.D = D\r\n \r\n self.x_coord = x_coord\r\n self.y_coord = y_coord\r\n self.dx = dx\r\n self.dy = dy\r\n self.dz = dz","def setUp(self):\n self.setup_beets()","def _initialize_tests(self):\n # Access the sentries for inspecting service units\n self.compute_sentry = self.d.sentry['nova-compute'][0]\n self.rabbitmq_sentry = self.d.sentry['rabbitmq-server'][0]\n self.neutron_api_sentry = self.d.sentry['neutron-api'][0]\n self.n_ovs_sentry = self.d.sentry['neutron-openvswitch'][0]\n\n # pidof is failing to find neutron-server on stein\n # use pgrep instead.\n if self._get_openstack_release() >= self.bionic_stein:\n self.pgrep_full = True\n else:\n self.pgrep_full = False","def prepare_simulations(self):\n # Parse all recording sites into a tuple containing the variable name,\n # segment name and component names\n for setup in self._simulation_setups:\n for i, rec in enumerate(setup.record_variables):\n if rec is None:\n # Records the voltage in the default segment by default\n var = 'v'\n segname = self.default_seg\n component = None\n else:\n parts = rec.split('.')\n if len(parts) == 1:\n var = parts[0]\n segname = self.default_seg\n component = None\n elif len(parts) == 2:\n segname, var = parts\n component = None\n else:\n segname, component, var = parts\n setup.record_variables[i] = (var, segname, component)\n # Check to see if there are multiple setups, because if there aren't\n # the cell can be initialised (they can't in general if there are\n # multiple as there is only ever one instance of NEURON running)\n if len(self._simulation_setups) == 1:\n self._prepare(self._simulation_setups[0])","def setup(self):\n pass","def setup_class(cls):\n # Creating a temporary directory and generating paths for output files\n cls.tmp_dir = tempfile.mkdtemp()\n cls.pdb_path = os.path.join(cls.tmp_dir, 'multipdb.pdb')\n cls.smiles_path = os.path.join(cls.tmp_dir, 'multismiles.smiles')\n cls.sdf_path = os.path.join(cls.tmp_dir, 'multisdf.sdf')\n cls.mol2_path = os.path.join(cls.tmp_dir, 'multimol2.mol2')\n\n # Rotation matrix to invert z-coordinate, i.e. flip molecule w.r.t. x-y plane\n rot = np.array([[1, 0, 0], [0, 1, 0], [0, 0, -1]])\n\n # Create 2-frame PDB file. First frame is lysozyme, second is lysozyme with inverted z\n lysozyme_path = examples_paths()['lysozyme']\n lysozyme = PDBFile(lysozyme_path)\n\n # Rotate positions to invert z for the second frame\n symmetric_pos = lysozyme.getPositions(asNumpy=True).value_in_unit(unit.angstrom)\n symmetric_pos = symmetric_pos.dot(rot) * unit.angstrom\n\n with open(cls.pdb_path, 'w') as f:\n PDBFile.writeHeader(lysozyme.topology, file=f)\n PDBFile.writeModel(lysozyme.topology, lysozyme.positions, file=f, modelIndex=0)\n PDBFile.writeModel(lysozyme.topology, symmetric_pos, file=f, modelIndex=1)\n\n # Create 2-molecule SMILES file\n with open(cls.smiles_path, 'w') as f:\n f.write('# comment\\n')\n f.write('benzene,c1ccccc1\\n')\n f.write('toluene,Cc1ccccc1\\n')\n\n # Create 2-molecule sdf and mol2 with OpenEye\n if utils.is_openeye_installed():\n from openeye import oechem\n oe_benzene = utils.load_oe_molecules(examples_paths()['benzene'], molecule_idx=0)\n oe_benzene_pos = utils.get_oe_mol_positions(oe_benzene).dot(rot)\n oe_benzene.NewConf(oechem.OEFloatArray(oe_benzene_pos.flatten()))\n\n # Save 2-conformer benzene in sdf and mol2 format\n utils.write_oe_molecule(oe_benzene, cls.sdf_path)\n utils.write_oe_molecule(oe_benzene, cls.mol2_path, mol2_resname='MOL')","def setup(bot):\n bot.add_cog(Miniscape(bot))","def setUp(self):\n TESTFAMILY = 'H_Abstraction'\n\n # set-up RMG object\n self.rmg = RMG()\n\n # load kinetic database and forbidden structures\n self.rmg.database = RMGDatabase()\n path = os.path.join(settings['database.directory'])\n\n # forbidden structure loading\n self.rmg.database.loadForbiddenStructures(os.path.join(path, 'forbiddenStructures.py'))\n # kinetics family loading\n self.rmg.database.loadKinetics(os.path.join(path, 'kinetics'),\n kineticsFamilies=[TESTFAMILY],\n reactionLibraries=[]\n )","def setup(self):\n self.testInst = pysat.Instrument('pysat', 'testing',\n clean_level='clean')\n self.bounds1 = (dt.datetime(2008, 1, 1), dt.datetime(2008, 1, 3))\n self.bounds2 = (dt.datetime(2009, 1, 1), dt.datetime(2009, 1, 2))\n\n return","def setup(self):\n ...","def setUpClass(self):\n self.c = Simulation(logging_level=50)\n self.c.set_simulation_parameters(\n seed=1,\n task=32,\n output_directory=\"output\",\n min_speciation_rate=0.5,\n sigma=2,\n tau=2,\n deme=1,\n sample_size=0.1,\n max_time=10,\n dispersal_relative_cost=1,\n min_num_species=1,\n )\n self.c.set_map_files(\n sample_file=\"sample/SA_samplemaskINT.tif\",\n fine_file=\"sample/SA_sample_coarse.tif\",\n dispersal_map=\"sample/dispersal_fine.tif\",\n )\n self.c.run()","def setUp(self):\n program = program_utils.seedProgram()\n self.profile = profile_utils.seedSOCStudent(program)","def setup(self):\n self.cwd = os.getcwd()\n self.t = tempfile.mkdtemp()\n dir_path = Path(\"packages\")\n tmp_dir = self.t / dir_path\n src_dir = self.cwd / Path(ROOT_DIR, dir_path)\n shutil.copytree(str(src_dir), str(tmp_dir))\n shutil.copytree(Path(CUR_PATH, \"data\", \"dummy_aea\"), Path(self.t, \"dummy_aea\"))\n os.chdir(Path(self.t, \"dummy_aea\"))\n self.runner = CliRunner()","def setUp(self):\n\n # Load the data\n dataset = tagging.data.DataSet.from_fits(DATA_PATH, extension=1)\n\n # Assign all as field.\n dataset.data[\"FIELD/CLUSTER\"] = \"FIELD\"\n\n # [TODO] Delete benchmarks\n clusters = (\"Cha_I\", \"Br81\", \"M15\", \"NGC2808\", \"NGC6633\", \"IC4665\", \n \"NGC104\", \"gamma2_Vel\", \"GJ880\", \"NGC4815\", \"NGC2547\", \"NGC5927\",\n \"NGC4833\", \"NGC1851\", \"NGC2243\", \"NGC3532\", \"NGC6752\", \"Br25\", \n \"NGC4372\", \"NGC6705\", \"M67\", \"NGC2516\", \"Trumpler20\")\n\n # Assign all as members.\n for cluster in clusters:\n members = dataset.assign_cluster_members(cluster,\n lambda row: row[\"TARGET\"].startswith(cluster))\n\n # Special hack:\n if cluster == \"Trumpler20\":\n members += dataset.assign_cluster_members(cluster,\n lambda row: row[\"TARGET\"].startswith(\"Trumpler_20\"))\n\n logger.info(\"Assigned stars to {} clusters\".format(len(clusters)))\n self.dataset = dataset\n return None","def setup(self):\r\n pass","def setUp(self):\n self.shonan = ShonanAveraging3(\"toyExample.g2o\", DEFAULT_PARAMS)","def setUpClass(self):\n self.coal = Simulation()\n\n self.coal.set_simulation_parameters(\n seed=5, task=4, output_directory=\"output\", min_speciation_rate=0.1, sigma=4, deme=0.25\n )\n self.coal.set_map_files(\n \"null\", fine_file=\"sample/SA_sample_fine.tif\", coarse_file=\"sample/SA_sample_coarse.tif\"\n )\n self.coal.run()\n self.coal2 = Simulation()\n\n self.coal2.set_simulation_parameters(\n seed=6, task=4, output_directory=\"output\", min_speciation_rate=0.1, sigma=4, deme=0.01\n )\n self.coal2.set_map_files(\n \"null\", fine_file=\"sample/SA_sample_fine.tif\", coarse_file=\"sample/SA_sample_coarse.tif\"\n )\n self.coal2.run()\n self.tree = CoalescenceTree(self.coal)\n self.tree2 = CoalescenceTree(self.coal2)","def setUpClass(self):\n self.coal = Simulation()\n self.tree = CoalescenceTree()\n self.coal.set_simulation_parameters(\n 2,\n 2,\n \"output\",\n 0.1,\n 4,\n 4,\n 1,\n 1.0,\n 2,\n dispersal_relative_cost=1,\n min_num_species=1,\n dispersal_method=\"normal\",\n m_prob=1,\n landscape_type=True,\n )\n self.coal.set_map_parameters(\"null\", 10, 10, \"null\", 10, 10, 0, 0, \"null\", 20, 20, 0, 0, 1, \"null\", \"null\")\n self.coal.set_speciation_rates([0.1, 0.2])\n self.coal.run()\n self.tree.set_database(\"output/data_2_2.db\")\n self.tree.calculate_octaves()\n self.tree.calculate_richness()","def setUp(self):\n self._default_call_inputs = (\n np.array([[1,2,3], [4,5,6]]),\n None\n )\n\n self._hash_bins = 10\n self._hash_embedding_dim = 4\n self._embedding_dim = 2\n self._masking = False\n\n self._default_config = {\n \"hash_bins\": self._hash_bins,\n \"hash_embedding_dim\": self._hash_embedding_dim,\n \"embedding_dim\": self._embedding_dim,\n \"masking\": self._masking\n }","def setup(self):\n\n if self.user is 'Daisy':\n import socket\n host = socket.gethostname()\n\n simName = self.name_prefix[:self.name_prefix.find('_')]\n\n if 'ursa' in host:\n self.raw_sim_dir = '/disk01/rad/sim/' + simName + '/' + self.feedback\n self.caesar_dir = '/disk01/rad/sim/' + simName + '/' + self.feedback + 'Groups/'\n self.redshiftFile = '/home/rad/gizmo-extra/outputs_boxspace50.info'\n self.d_data = '/home/dleung/Downloads/SIGAME_dev/sigame/temp/z' + str(int(self.zCloudy)) + '_data_files/'\n elif 'flatironinstitute.org' or 'worker' in host:\n self.raw_sim_dir = '/mnt/ceph/users/daisyleung/simba/sim/' + simName + '/' + self.feedback # dummy\n self.caesar_dir = '/mnt/ceph/users/daisyleung/simba/sim/' + simName + '/' + self.feedback + 'Groups/'\n self.redshiftFile = '/mnt/ceph/users/daisyleung/simba/gizmo-extra/outputs_boxspace50.info'\n self.d_data = '/mnt/home/daisyleung/Downloads/SIGAME_dev/sigame/temp/z' + str(int(self.zCloudy)) + '_data_files/'\n else:\n raise NotImplementedError","def setUp(self):\n rmg_path = os.path.normpath(os.path.join(get_path(), '..'))\n\n self.settings1 = QMSettings(software='mopac',\n method='pm3',\n fileStore=os.path.join(rmg_path, 'testing', 'qm', 'QMfiles'),\n scratchDirectory=None,\n onlyCyclics=False,\n maxRadicalNumber=0,\n )\n\n self.settings2 = QMSettings()","def setup(self):\n\n logger.info('Setting up SimulatedMaps module.')\n\n # Save the cls as a class attribute\n self.cls = self.read_cls()\n\n logger.info('Setup done!')","def setup(self):\n self.create_songs_index()\n self.create_fingerprints_index()\n self.delete_unfingerprinted()","def setup(self) -> None:\n pass","def setup(self) -> None:\n pass","def setup(self) -> None:\n pass","def setup_class(self):\n self._tester = self.get_remote('tester').run_prox_with_config(\"01_handle_none-gen.cfg\", \"-e -t\")\n # TODO tester.run_prox_with_config should raise an exception on error, so the below if block can be removed\n if (self._tester == None):\n raise IOError(\"Could not connect to PROX on the tester system\")\n else:\n logging.debug(\"Connected to PROX on Tester\")\n\n self._sut = self.get_remote('sut').run_prox_with_config(\"01_handle_none-sut.cfg\", \"-t\")\n if (self._sut == None):\n raise IOError(\"Could not connect to PROX on the SUT\")\n else:\n logging.debug(\"Connected to PROX on SUT\")\n\n self._cores = [1, 2, 3, 4]","def setUpClass(self):\n self.coal = Simulation()\n self.tree = CoalescenceTree()\n self.coal.set_simulation_parameters(\n 2,\n 5,\n \"output\",\n 0.1,\n 4,\n 4,\n deme=1,\n sample_size=1.0,\n max_time=2,\n dispersal_relative_cost=1,\n min_num_species=1,\n dispersal_method=\"normal\",\n )\n self.coal.set_map_parameters(\"null\", 10, 10, \"null\", 10, 10, 0, 0, \"null\", 20, 20, 0, 0, 1, \"null\", \"null\")\n self.coal.set_speciation_rates([0.1, 0.2])\n self.coal.run()\n self.tree.set_database(\"output/data_5_2.db\")\n self.tree.calculate_richness()","def _setup(self):\n\n from AlGDock.topology import Topology\n self.top = Topology(self.args)\n self.top_RL = Topology(self.args, includeReceptor=True)\n\n # Initialize rmsd calculation function\n from AlGDock.RMSD import hRMSD\n self.get_rmsds = hRMSD(self.args.FNs['prmtop']['L'], \\\n self.top.inv_prmtop_atom_order_L)\n\n # Obtain reference pose\n if self.data['CD'].pose > -1:\n if ('starting_poses' in self.data['CD'].confs.keys()) and \\\n (self.data['CD'].confs['starting_poses'] is not None):\n starting_pose = np.copy(self.data['CD'].confs['starting_poses'][0])\n else:\n (confs, Es) = self._get_confs_to_rescore(site=False, \\\n minimize=False, sort=False)\n if self.args.params['CD']['pose'] < len(confs):\n starting_pose = np.copy(confs[self.args.params['CD']['pose']])\n self.data['CD'].confs['starting_poses'] = [np.copy(starting_pose)]\n else:\n self._clear('CD')\n self._store_infinite_f_RL()\n raise Exception('Pose index greater than number of poses')\n else:\n starting_pose = None\n\n from AlGDock.system import System\n self.system = System(self.args,\n self.log,\n self.top,\n self.top_RL,\n starting_pose=starting_pose)\n\n # Measure the binding site\n if (self.args.params['CD']['site'] == 'Measure'):\n self.args.params['CD']['site'] = 'Sphere'\n if self.args.params['CD']['site_measured'] is not None:\n (self.args.params['CD']['site_max_R'],self.args.params['CD']['site_center']) = \\\n self.args.params['CD']['site_measured']\n else:\n print '\\n*** Measuring the binding site ***'\n self.system.setParams(\n self.system.paramsFromAlpha(1.0, 'CD', site=False))\n (confs, Es) = self._get_confs_to_rescore(site=False, minimize=True)\n if len(confs) > 0:\n # Use the center of mass for configurations\n # within 20 RT of the lowest energy\n cutoffE = Es['total'][-1] + 20 * (R * self.T)\n coms = []\n for (conf, E) in reversed(zip(confs, Es['total'])):\n if E <= cutoffE:\n self.top.universe.setConfiguration(\n Configuration(self.top.universe, conf))\n coms.append(np.array(self.top.universe.centerOfMass()))\n else:\n break\n print ' %d configurations fit in the binding site' % len(coms)\n coms = np.array(coms)\n center = (np.min(coms, 0) + np.max(coms, 0)) / 2\n max_R = max(\n np.ceil(np.max(np.sqrt(np.sum(\n (coms - center)**2, 1))) * 10.) / 10., 0.6)\n self.args.params['CD']['site_max_R'] = max_R\n self.args.params['CD']['site_center'] = center\n self.top.universe.setConfiguration(\n Configuration(self.top.universe, confs[-1]))\n if ((self.args.params['CD']['site_max_R'] is None) or \\\n (self.args.params['CD']['site_center'] is None)):\n raise Exception('No binding site parameters!')\n else:\n self.args.params['CD']['site_measured'] = \\\n (self.args.params['CD']['site_max_R'], \\\n self.args.params['CD']['site_center'])\n\n # Read the reference ligand and receptor coordinates\n import AlGDock.IO\n IO_crd = AlGDock.IO.crd()\n if self.args.FNs['inpcrd']['R'] is not None:\n if os.path.isfile(self.args.FNs['inpcrd']['L']):\n lig_crd = IO_crd.read(self.args.FNs['inpcrd']['L'], multiplier=0.1)\n self.data['CD'].confs['receptor'] = IO_crd.read(\\\n self.args.FNs['inpcrd']['R'], multiplier=0.1)\n elif self.args.FNs['inpcrd']['RL'] is not None:\n complex_crd = IO_crd.read(self.args.FNs['inpcrd']['RL'], multiplier=0.1)\n lig_crd = complex_crd[self.top_RL.L_first_atom:self.top_RL.L_first_atom + \\\n self.top.universe.numberOfAtoms(),:]\n self.data['CD'].confs['receptor'] = np.vstack(\\\n (complex_crd[:self.top_RL.L_first_atom,:],\\\n complex_crd[self.top_RL.L_first_atom + self.top.universe.numberOfAtoms():,:]))\n elif self.args.FNs['inpcrd']['L'] is not None:\n self.data['CD'].confs['receptor'] = None\n if os.path.isfile(self.args.FNs['inpcrd']['L']):\n lig_crd = IO_crd.read(self.args.FNs['inpcrd']['L'], multiplier=0.1)\n else:\n lig_crd = None\n\n if lig_crd is not None:\n self.data['CD'].confs['ligand'] = lig_crd[self.top.\n inv_prmtop_atom_order_L, :]\n self.top.universe.setConfiguration(\\\n Configuration(self.top.universe,self.data['CD'].confs['ligand']))\n if self.top_RL.universe is not None:\n self.top_RL.universe.setConfiguration(\\\n Configuration(self.top_RL.universe, \\\n np.vstack((self.data['CD'].confs['receptor'],self.data['CD'].confs['ligand']))))\n\n if self.args.params['CD']['rmsd'] is not False:\n if self.args.params['CD']['rmsd'] is True:\n if lig_crd is not None:\n rmsd_crd = lig_crd[self.top.inv_prmtop_atom_order_L, :]\n else:\n raise Exception('Reference structure for rmsd calculations unknown')\n else:\n rmsd_crd = IO_crd.read(self.args.params['CD']['rmsd'], \\\n natoms=self.top.universe.numberOfAtoms(), multiplier=0.1)\n rmsd_crd = rmsd_crd[self.top.inv_prmtop_atom_order_L, :]\n self.data['CD'].confs['rmsd'] = rmsd_crd\n\n self.get_rmsds.set_ref_configuration(self.data['CD'].confs['rmsd'])\n\n # If configurations are being rescored, start with a docked structure\n (confs, Es) = self._get_confs_to_rescore(site=False, minimize=False)\n if len(confs) > 0:\n self.top.universe.setConfiguration(\n Configuration(self.top.universe, confs[-1]))\n\n from AlGDock.simulation_iterator import SimulationIterator\n self.iterator = SimulationIterator(self.args, self.top, self.system)\n\n # Load progress\n from AlGDock.postprocessing import Postprocessing\n Postprocessing(self.args, self.log, self.top, self.top_RL, self.system, self.data, self.save).run(readOnly=True)\n\n self.calc_f_L(readOnly=True)\n self.calc_f_RL(readOnly=True)\n\n if self.args.random_seed > 0:\n np.random.seed(self.args.random_seed)","def setUp(self):\n sumo_bin = sumolib.checkBinary('sumo')\n traci.start([sumo_bin, \"-n\", self.network_path, \"-r\", self.routes_path])\n traci.simulationStep()","def setup(self, phibins = 0, force_create_srcmap=False, overwrite=False, **kwargs):\n\n\tfor c in self.components:\n\t loglevel = kwargs.get('loglevel', c.loglevel)\n\t\t\t\t\t\t\t\t\t\t\t\t \n\t c.logger.log(loglevel, 'Running setup for component %s',c.name)\n\t #use_external_srcmap = c.config['gtlike']['use_external_srcmap']\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t \n\t # Run data selection\n\t #if not use_external_srcmap:\n\t\t#c._select_data(overwrite=overwrite, **kwargs)\n\t # Create LT Cube\n\t if c._ext_ltcube is not None:\n\t\tc.logger.log(loglevel, 'Using external LT cube.')\n\t else:\n\t\tc._create_ltcube(phibins = phibins, overwrite=overwrite, **kwargs)\n\n\t c.logger.debug('Loading LT Cube %s', c.files['ltcube'])\n\t c._ltc = LTCube.create(c.files['ltcube'])\n\t \n\t # Extract tmin, tmax from LT cube\n\t c._tmin = c._ltc.tstart\n\t c._tmax = c._ltc.tstop\n\t c.logger.debug('Creating PSF model')\n\t c._psf = irfs.PSFModel.create(c.roi.skydir, c._ltc,\n\t\tc.config['gtlike']['irfs'],\n\t\tc.config['selection']['evtype'],\n\t\tc.energies)\n\n\t # we don't need this for unbinned analysis\n\t # Bin data and create exposure cube\n\t #if not use_external_srcmap:\n\t\t#c._bin_data(overwrite=overwrite, **kwargs)\n\t\t#c._create_expcube(overwrite=overwrite, **kwargs)\n\t\t#c._bexp = Map.create_from_fits(c.files['bexpmap'])\n\n\t # compute exposure \n\t c._create_expmap(overwrite=overwrite, **kwargs)\n\n\t # Make spatial maps for extended sources\n\t for s in c.roi.sources:\n\t\tif s.diffuse:\n\t\t continue\n\t\tif not s.extended:\n\t\t continue\n\t\tc.make_template(s, c.config['file_suffix'])\n\t # Write ROI XML\n\t c.roi.write_xml(c.files['srcmdl'])\n\n\t # compute diffuse response \n\t c._diffrsp(c.files['srcmdl'], overwrite=overwrite, **kwargs)\n\n\t # we don't need this for unbinned\n\t # Create source maps file\n\t #if force_create_srcmap:\n\t#\tif not use_external_srcmap:\n\t#\t c._create_srcmaps(overwrite=overwrite)\n\t if not c.config['data']['cacheft1'] and os.path.isfile(c.files['ft1']):\n\t\tc.logger.debug('Deleting FT1 file.')\n\t\tos.remove(c.files['ft1'])\n\n\t c.logger.log(loglevel, 'Finished setup for component %s',\n\t\tc.name)\n\treturn","def do_setup_pocs(self, *arg):\n args, kwargs = string_to_params(*arg)\n\n simulator = kwargs.get('simulator', list())\n if isinstance(simulator, str):\n simulator = [simulator]\n\n # TODO(wtgee) Incorporate real power readings\n if 'power' not in simulator:\n simulator.append('power')\n\n if 'POCSTIME' in os.environ:\n print_warning(\"Clearing POCSTIME variable\")\n del os.environ['POCSTIME']\n\n try:\n cameras = create_cameras_from_config(simulator=simulator)\n observatory = Observatory(simulator=simulator, cameras=cameras)\n self.pocs = POCS(observatory, messaging=True)\n self.pocs.initialize()\n except error.PanError as e:\n print_warning('Problem setting up POCS: {}'.format(e))","def _setup_test_infra(world_rank, world_size):\n os.environ['RANK'] = str(world_rank)\n os.environ['WORLD_SIZE'] = str(world_size)\n os.environ['MASTER_ADDR'] = '127.0.0.1'\n os.environ['MASTER_PORT'] = '29500'\n\n set_cuda_device_id(world_rank)\n\n dist.init_process_group(backend='nccl', world_size=world_size, rank=world_rank)","def setupRun(self):\n \n # TBD: for now ignores the \"content\" of a protocol parameter\n \n run = self.run\n protocolInterface = self.protocolInterface\n \n for interfaceParameter in protocolInterface.sortedInterfaceParameters():\n nmrCalcObject = self.makeNmrCalcData(run, interfaceParameter)\n \n self.close()"],"string":"[\n \"def setup(self):\\n insts = []\\n for i in range(5):\\n insts.append(pysat.Instrument('pysat', 'testing',\\n clean_level='clean'))\\n self.testC = pysat.Constellation(instruments=insts)\\n self.testI = pysat.Instrument('pysat', 'testing', clean_level='clean')\\n self.bounds = (dt.datetime(2008, 1, 1), dt.datetime(2008, 1, 3))\\n\\n # Apply bounds to all Instruments in Constellation, and solo Instrument.\\n self.testC.bounds = self.bounds\\n self.testI.bounds = self.bounds\\n\\n # Define variables for 1D testing\\n self.one_d_vars = ['dummy1', 'dummy2', 'dummy3']\\n self.unequal_one_d_vars = []\\n\\n return\",\n \"def setup(self):\\n insts = []\\n for i in range(2):\\n r_date = dt.datetime(2009, 1, i + 1)\\n insts.append(pysat.Instrument('pysat', 'testing',\\n clean_level='clean',\\n root_date=r_date))\\n self.testC = pysat.Constellation(instruments=insts)\\n self.testI = pysat.Instrument('pysat', 'testing', clean_level='clean')\\n self.bounds = (dt.datetime(2008, 1, 1), dt.datetime(2008, 1, 3))\\n\\n # Apply bounds to all Instruments in Constellation, and solo Instrument.\\n self.testC.bounds = self.bounds\\n self.testI.bounds = self.bounds\\n\\n # Define variables for 1D testing. A more limited set that only\\n # depends upon 'mlt'. Other variables also include longitude, which\\n # can differ between instruments when only binning by 'mlt'.\\n self.one_d_vars = ['dummy1']\\n self.unequal_one_d_vars = ['dummy2', 'dummy3']\\n\\n return\",\n \"def setup(self):\\n\\n self.insts = []\\n self.testInst = pysat.Instrument('pysat', 'testing2D',\\n clean_level='clean')\\n self.testInst.bounds = (dt.datetime(2008, 1, 1),\\n dt.datetime(2008, 1, 3))\\n self.insts.append(self.testInst)\\n self.insts.append(self.testInst)\\n\\n self.dname = 'series_profiles'\\n self.test_vals = np.arange(50) * 1.2\\n\\n self.testC = pysat.Constellation(instruments=self.insts)\\n\\n return\",\n \"def setup_simulation(self, **kwargs):\\n\\n self.distance = self.config[\\\"site\\\"][\\\"distance\\\"]\\n self.num_substations = self.config[\\\"num_substations\\\"]\\n\\n self.initialize_substructure_production()\\n self.initialize_installation_vessel()\",\n \"def setup_class(self):\\n args = {'pdb_path':'/sdf/home/a/apeck/tomoxtal/examples/input/193l.pdb', 'resolution':6.0, 'size':250}\\n\\n # generate structure factors and retrieve associated cell information\\n sf = cctbx_tools.reference_sf(args['pdb_path'], args['resolution'], expand_to_p1=True)\\n sf_data = cctbx_tools.reformat_sf(sf)\\n sg_symbol, sg_no, self.cell, cs = cctbx_tools.unit_cell_info(args['pdb_path'])\\n \\n # add random phase shifts\\n hklIp1, hklIp2, hklIp3 = sf_data.copy(), sf_data.copy(), sf_data.copy()\\n hklIp2[:,-1], self.shifts2 = phases_utils.add_random_phase_shift(sf_data[:,:3], sf_data[:,-1])\\n hklIp3[:,-1], self.shifts3 = phases_utils.add_random_phase_shift(sf_data[:,:3], sf_data[:,-1])\\n\\n # retain subset of Millers\\n for data in [hklIp1,hklIp2,hklIp3]:\\n keep_idx = np.unique(np.random.randint(0, high=data.shape[0], size=args['size']))\\n data = data[keep_idx]\\n \\n self.data1, self.data2, self.data3 = hklIp1, hklIp2, hklIp3\\n fshifts_list = np.random.uniform(size=(4,3))\\n self.fshifts_list = np.vstack((fshifts_list, 1-self.shifts2, 1-self.shifts3))\",\n \"def setUp(self):\\n from ampscan.core import AmpObject\\n # Load 2 spheres with radius 1, and 1.2\\n stl_path = get_path(\\\"stl_file_5.stl\\\") # R=1\\n self.amp1 = AmpObject(stl_path)\\n stl_path = get_path(\\\"stl_file_4.stl\\\") # R=1.2\\n self.amp2 = AmpObject(stl_path)\\n stl_path = get_path(\\\"stl_file.stl\\\")\\n self.amp3 = AmpObject(stl_path)\\n self.amp4 = AmpObject(stl_path)\\n stl_path = get_path(\\\"cone1.stl\\\")\\n self.cone1 = AmpObject(stl_path)\\n stl_path = get_path(\\\"cone2.stl\\\")\\n self.cone2 = AmpObject(stl_path)\",\n \"def setUp(self):\\r\\n self.value_for_seed = 20\\r\\n\\r\\n # Single comp.\\r\\n self.labels1 = ['foo', 'bar']\\r\\n self.dists1 = [[1, 2, 3], [7, 8]]\\r\\n\\r\\n # Multiple comps.\\r\\n self.labels2 = ['foo', 'bar', 'baz']\\r\\n self.dists2 = [[1, 2, 3], [7, 8], [9, 10, 11]]\\r\\n\\r\\n # Too few obs.\\r\\n self.labels3 = ['foo', 'bar', 'baz']\\r\\n self.dists3 = [[1], [7], [9, 10, 11]]\",\n \"def setUp(self):\\n lang = self._sim_lang\\n self._simulator = self._find_resource(\\n f\\\"drake/examples/hardware_sim/hardware_sim_{lang}\\\")\\n self._example_scenarios = self._find_resource(\\n \\\"drake/examples/hardware_sim/example_scenarios.yaml\\\")\\n self._test_scenarios = self._find_resource(\\n \\\"drake/examples/hardware_sim/test/test_scenarios.yaml\\\")\\n self._default_extra = {\\n # For our smoke test, exit fairly quickly.\\n \\\"simulation_duration\\\": 0.0625,\\n }\",\n \"def _setup_self(self, model_num =0):\\n self.all_residues = self._setup_all_residues(model_num) #vector1 of Bio Residues\\n self.pdb_info = self._setup_pdb_info() #PDBInfo to map the vector1\\n self.peptide_bond_distances = self._setup_peptide_bond_distances() #map of bond distances to next residue in pose.\",\n \"def setUp(self):\\n self.size = 5\\n self.parking_lot = CarSlots(self.size)\\n self.controller = Controller(self.parking_lot)\",\n \"def setUp(self):\\n np.random.seed(1234)\\n\\n _TEST_FILE_NAME = 'AHN3.las'\\n _TEST_DATA_SOURCE = 'testdata'\\n\\n _CYLINDER = InfiniteCylinder(4)\\n _PC_260807 = load(os.path.join(_TEST_DATA_SOURCE, _TEST_FILE_NAME))\\n _PC_1000 = copy_point_cloud(_PC_260807, array_mask=(\\n np.random.choice(range(len(_PC_260807[keys.point]['x']['data'])), size=1000, replace=False)))\\n _1000_NEIGHBORHOODS_IN_260807 = list(compute_neighbors.compute_neighborhoods(_PC_260807, _PC_1000, _CYLINDER))\\n\\n self.point_cloud = _PC_260807\\n self.neigh = _1000_NEIGHBORHOODS_IN_260807\",\n \"def setUp(self):\\n self.s = Simulation()\\n self.s['Retina']=GeneratorSheet(nominal_density=4.0)\\n self.s['V1']= CFSheet(nominal_density=4.0)\\n self.s['V2'] = CFSheet(nominal_density=4.0)\\n\\n self.s.connect('Retina','V1',delay=0.5,connection_type=CFProjection,\\n name='RtoV1',learning_fn=CFPLF_Hebbian())\\n\\n self.s.connect('Retina','V2',delay=0.5,connection_type=CFProjection,\\n name='RtoV2',learning_fn=CFPLF_Hebbian())\",\n \"def test_setup_smiles(self):\\n from openeye.oechem import OEMolToSmiles\\n\\n with mmtools.utils.temporary_directory() as tmp_dir:\\n yaml_content = \\\"\\\"\\\"\\n ---\\n options:\\n output_dir: {}\\n setup_dir: .\\n molecules:\\n take-first:\\n filepath: {}\\n antechamber: {{charge_method: bcc}}\\n leap: {{parameters: leaprc.gaff}}\\n select-second:\\n filepath: {}\\n antechamber: {{charge_method: bcc}}\\n leap: {{parameters: leaprc.gaff}}\\n select: 1\\n \\\"\\\"\\\".format(tmp_dir, self.smiles_path, self.smiles_path)\\n yaml_content = textwrap.dedent(yaml_content)\\n exp_builder = ExperimentBuilder(yaml_content)\\n\\n for i, mol_id in enumerate(['take-first', 'select-second']):\\n # The molecule now is neither set up nor processed\\n is_setup, is_processed = exp_builder._db.is_molecule_setup(mol_id)\\n assert is_setup is False\\n assert is_processed is False\\n\\n # The single SMILES has been converted to mol2 file\\n exp_builder._db._setup_molecules(mol_id)\\n mol2_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR, mol_id, mol_id + '.mol2')\\n assert os.path.exists(os.path.join(mol2_path))\\n assert os.path.getsize(os.path.join(mol2_path)) > 0\\n\\n # The mol2 represents the right molecule\\n csv_smiles_str = pipeline.read_csv_lines(self.smiles_path, lines=i).strip().split(',')[1]\\n mol2_smiles_str = OEMolToSmiles(utils.load_oe_molecules(mol2_path, molecule_idx=0))\\n assert mol2_smiles_str == csv_smiles_str\\n\\n # The molecule now both set up and processed\\n is_setup, is_processed = exp_builder._db.is_molecule_setup(mol_id)\\n assert is_setup is True\\n assert is_processed is True\\n\\n # A new instance of ExperimentBuilder is able to resume with correct molecule\\n exp_builder = ExperimentBuilder(yaml_content)\\n is_setup, is_processed = exp_builder._db.is_molecule_setup(mol_id)\\n assert is_setup is True\\n assert is_processed is True\",\n \"def setup(self):\\n self.testInst = pysat.Instrument('pysat', 'testing',\\n clean_level='clean')\\n self.bounds1 = (dt.datetime(2008, 1, 1), dt.datetime(2008, 1, 3))\\n self.bounds2 = (dt.datetime(2009, 1, 1), dt.datetime(2009, 1, 2))\\n\\n self.long_bins = [0., 360., 24]\\n self.mlt_bins = [0., 24., 24]\\n self.auto_bin = True\\n\\n return\",\n \"def setup(self):\\n # define misfit function and adjoint source generator\\n self.misfit = getattr(misfit, PAR.MISFIT)\\n self.adjoint = getattr(adjoint, PAR.MISFIT)\\n\\n # define seismic data reader and writer\\n self.reader = getattr(readers, PAR.READER)\\n self.writer = getattr(writers, PAR.WRITER)\\n\\n # prepare channels list\\n self.channels = []\\n for char in PAR.CHANNELS:\\n self.channels += [char]\",\n \"def _setup_simulation(self\\n ) -> None:\\n pass\",\n \"def setUpClass(cls):\\n np.random.seed(2019)\\n # So the 1 st row of the first random number array, random.rand(500, 3)\\n # will be [0.90348221, 0.39308051, 0.62396996]\\n # Accordingly, the first row of\\n # coordinates = (0.5 - np.random.rand(500, 3)) * box_length\\n # should be [-3.31690899, 0.87895379, -1.01912071]\\n cls.sys_obj = monte_carlo.SystemSetup()\\n cls.energy = energy.Energy()\\n cls.parser = monte_carlo.initialize()\\n cls.sim = monte_carlo.MonteCarlo(\\n cls.sys_obj, cls.energy, cls.parser)\\n np.random.seed()\",\n \"def setup(self):\\n\\n self.testInst = pysat.Instrument('pysat', 'testing',\\n clean_level='clean')\\n self.testInst.bounds = (dt.datetime(2008, 1, 1),\\n dt.datetime(2008, 1, 3))\\n\\n self.bounds1 = (dt.datetime(2008, 1, 1), dt.datetime(2008, 1, 3))\\n self.bounds2 = (dt.datetime(2009, 1, 1), dt.datetime(2009, 1, 2))\\n\\n self.long_bins = np.linspace(0., 360., 25)\\n self.mlt_bins = np.linspace(0., 24., 25)\\n\\n self.auto_bin = False\\n\\n return\",\n \"def setUp(self):\\n self.supvisors = DummySupvisors()\",\n \"def setUp(self):\\n\\n self.veh = Vehicle(0, 0)\\n self.R = Random(seed)\",\n \"def _set_up():\\n repl._setUp = self.setUp\",\n \"def setUp(self):\\n\\n self.params = master_phil.extract()\\n\\n self.params.input.xtal_name = \\\"FALZA-x0085\\\"\\n self.params.input.in_path = os.path.join(\\n os.path.realpath(\\\"./test/resources\\\"), self.params.input.xtal_name\\n )\\n self.params.validate.input.base_mtz = os.path.join(\\n self.params.input.in_path, \\\"FALZA-x0085.free.mtz\\\"\\n )\\n self.params.input.mtz = os.path.join(\\n self.params.input.in_path, \\\"FALZA-x0085.free.mtz\\\"\\n )\\n self.params.input.pdb = os.path.join(self.params.input.in_path, \\\"refine.pdb\\\")\\n self.params.output.out_dir = os.path.realpath(\\\"./test/output\\\")\\n self.params.output.log_dir = os.path.realpath(\\n os.path.join(\\\"./test/output\\\", \\\"logs\\\")\\n )\\n self.params.exhaustive.options.step = 0.05\",\n \"def setUp(self):\\n\\n self.params = master_phil.extract()\\n\\n self.params.input.xtal_name = \\\"FALZA-x0085\\\"\\n\\n self.params.input.in_path = os.path.join(\\n os.path.realpath(\\\"./test/resources\\\"), self.params.input.xtal_name\\n )\\n\\n self.params.validate.input.base_mtz = os.path.join(\\n self.params.input.in_path, \\\"FALZA-x0085.free.mtz\\\"\\n )\\n\\n self.params.input.mtz = os.path.join(\\n self.params.input.in_path, \\\"FALZA-x0085.free.mtz\\\"\\n )\\n\\n self.params.input.pdb = os.path.join(self.params.input.in_path, \\\"refine.pdb\\\")\",\n \"def setup(self):\\n self.testInst = pysat.Instrument('pysat', 'testing_xarray',\\n clean_level='clean')\\n self.bounds1 = (dt.datetime(2008, 1, 1), dt.datetime(2008, 1, 3))\\n self.bounds2 = (dt.datetime(2009, 1, 1), dt.datetime(2009, 1, 2))\\n\\n self.long_bins = [0., 360., 24]\\n self.mlt_bins = [0., 24., 24]\\n self.auto_bin = True\\n\\n return\",\n \"def setUp(self):\\n self.testdatapath = os.path.join(mkdtemp())\\n self.testfilenames = [\\n os.path.join(self.testdatapath, \\\"0035.nc\\\"),\\n os.path.join(self.testdatapath, \\\"0107.nc\\\")\\n ]\\n\\n self.gpis = [1, 10, 11, 12]\\n reg_grid = grids.genreg_grid().to_cell_grid()\\n self.grid = reg_grid.subgrid_from_gpis(self.gpis)\",\n \"def setUp(self):\\n self.sc = init_orca_context(cores=4)\",\n \"def setup( self ):\",\n \"def setUp(self):\\n self.compound = PyFBA.metabolism.Compound(\\\"t1\\\", \\\"test compound\\\")\\n self.compound.abbreviation = \\\"Cool\\\"\\n self.compound.add_attribute('What', \\\"Everything\\\")\\n self.compound_with_loc = PyFBA.metabolism.CompoundWithLocation.from_compound(self.compound, \\\"extracellular\\\")\",\n \"def setUp(self):\\n # Explicitly empty the list of segment input files,\\n # otherwise they hang around from previous tests.\\n Segment._input_files = {}\\n self.segment = Segment(\\n file=self.EXPECTED_INPUT_FILE,\\n punch_in=self.EXPECTED_PUNCH_IN,\\n punch_out=self.EXPECTED_PUNCH_OUT,\\n input_stream=self.EXPECTED_INPUT_STREAM)\\n self.expected_input_options = [\\n \\\"-ss\\\", str(self.EXPECTED_PUNCH_IN.total_seconds()),\\n \\\"-t\\\", str(self.EXPECTED_DURATION),\\n \\\"-i\\\", self.EXPECTED_INPUT_FILE\\n ]\\n self.expected_output_options = []\",\n \"def setUp(self):\\n super(PlayTests, self).setUp(\\n \\\"tests/data/shakespeare/\\\", \\\"structure.json\\\", \\\"brief_example.xml\\\")\",\n \"def setUp(self):\\n import protolibs.ics_servers as ics_servers\\n from point import Point\\n from configobj import ConfigObj\\n\\n # Get config file\\n configfile = '/'.join(['sims', 'rtutank', 'config'])\\n config=ConfigObj(infile=configfile, unrepr=True)\\n self.config = config\\n #Set global variable devconfig here \\n devconfig=config['vdevs']['slave'] \\n\\n ##--Set up points\\n points={}\\n for p in devconfig['points']:\\n points.update( { p['name'] : Point(**p) } ) \\n #The ** treats the p dictionary as the arguments to the Point class\\n self.server = ics_servers.ModbusRTU(devconfig['icsifaces'][0], points.values())\\n self.server.start()\",\n \"def do_setup_pocs(self, *arg):\\n args, kwargs = string_to_params(*arg)\\n simulator = kwargs.get('simulator', [])\\n print_info(\\\"Simulator: {}\\\".format(simulator))\\n\\n try:\\n self.pocs = POCS(simulator=simulator)\\n self.pocs.initialize()\\n except error.PanError as e:\\n\\n pass\",\n \"def setup():\\n global RBD_POOL, RBD_STORAGE_CLASS, RBD_SECRET, CEPHFS_OBJ, \\\\\\n CEPHFS_STORAGE_CLASS, CEPHFS_SECRET, RBD_PVC, CEPHFS_PVC\\n log.info(\\\"Creating RBD Pool\\\")\\n RBD_POOL = helpers.create_ceph_block_pool()\\n\\n log.info(\\\"Creating RBD Secret\\\")\\n RBD_SECRET = helpers.create_secret(constants.CEPHBLOCKPOOL)\\n\\n log.info(\\\"Creating RBD StorageClass\\\")\\n RBD_STORAGE_CLASS = helpers.create_storage_class(\\n constants.CEPHBLOCKPOOL, RBD_POOL.name, RBD_SECRET.name\\n )\\n\\n log.info(\\\"Creating CephFilesystem\\\")\\n CEPHFS_OBJ = helpers.create_cephfilesystem()\\n\\n log.info(\\\"Creating FS Secret\\\")\\n CEPHFS_SECRET = helpers.create_secret(constants.CEPHFILESYSTEM)\\n\\n log.info(\\\"Creating FS StorageClass\\\")\\n CEPHFS_STORAGE_CLASS = helpers.create_storage_class(\\n constants.CEPHFILESYSTEM, helpers.get_cephfs_data_pool_name(),\\n CEPHFS_SECRET.name\\n )\\n\\n log.info(\\\"Creating RBC PVC\\\")\\n RBD_PVC = helpers.create_pvc(sc_name=RBD_STORAGE_CLASS.name)\\n\\n log.info(\\\"Creating CephFs PVC\\\")\\n CEPHFS_PVC = helpers.create_pvc(sc_name=CEPHFS_STORAGE_CLASS.name)\",\n \"def setUp(self):\\n\\n self.sold = Soldier(0, 0)\\n self.R = Random(seed)\",\n \"def setUp(self):\\n\\n self.hw = HMMERWrapper\\n\\n modpath = os.path.abspath(os.path.dirname(__file__))\\n self.seqfile = os.path.join(modpath, 'data', 'P00929.fasta')\\n self.badfile = os.path.join(modpath, 'data', 'bad.fasta')\",\n \"def setUp(self):\\n self.number_of_tests = 20 # number of pseudo-random seeds\\n self.max_nq = 2 # maximal number of qubits to check\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setup(self):\\n pass\",\n \"def setUp(self):\\n # obtain separate logs\\n self.update_log_file_names()\\n # Start the servers and agents\\n super(MdtestBase, self).setUp()\\n\\n # Get the parameters for Mdtest\\n self.mdtest_cmd = MdtestCommand()\\n self.mdtest_cmd.get_params(self)\\n self.processes = self.params.get(\\\"np\\\", '/run/mdtest/client_processes/*')\\n self.manager = self.params.get(\\\"manager\\\", '/run/mdtest/*', \\\"MPICH\\\")\",\n \"def setup_pymol():\\n pymol.finish_launching() # Prevent threading errors\\n # Configure global settings\\n cmd.set('scene_buttons', 1)\\n cmd.set('matrix_mode', 1)\\n cmd.set('movie_panel', 1)\\n # Configure quality settings\\n cmd.mset(\\\"1 x500\\\")\\n cmd.set('ray_trace_frames', 1)\\n cmd.viewport(800, 800)\",\n \"def test_set_molecule(self):\\n mol = Molecule.from_smiles(\\\"CCO\\\")\\n atom = Atom(6, 0, False)\\n atom.molecule = mol\",\n \"def setUp(self):\\n # generate lattice\\n self.lattice = lattice.Lattice()\\n self.lattice.addAtom(\\\"He\\\", [0,0,0], 0)\\n self.lattice.addAtom(\\\"He\\\", [2,0,0], 0)\\n self.lattice.addAtom(\\\"He\\\", [0,2,0], 0)\\n self.lattice.addAtom(\\\"He\\\", [0,0,2], 0)\\n self.lattice.addAtom(\\\"He\\\", [9,9,9], 0)\\n self.lattice.addAtom(\\\"He\\\", [2,2,0], 0)\\n self.lattice.addAtom(\\\"He\\\", [2,0,2], 0)\\n self.lattice.addAtom(\\\"He\\\", [0,2,2], 0)\\n self.lattice.addAtom(\\\"He\\\", [2,2,2], 0)\\n \\n # indexes of cluster atoms\\n self.bigClusterIndexes = [0,1,2,3,5,6,7,8]\\n self.smallClusterIndexes = [4]\\n \\n # filter\\n self.filter = clusterFilter.ClusterFilter(\\\"Cluster\\\")\",\n \"def setUp(self):\\n import protolibs.ics_servers as ics_servers\\n from point import Point\\n from configobj import ConfigObj\\n\\n # Get config file\\n configfile = '/'.join(['sims', 'tcptank', 'config'])\\n config=ConfigObj(infile=configfile, unrepr=True)\\n self.config = config\\n #Set global variable devconfig here \\n devconfig=config['vdevs']['slave'] \\n\\n ##--Set up points\\n points={}\\n for p in devconfig['points']:\\n points.update( { p['name'] : Point(**p) } ) \\n #The ** treats the p dictionary as the arguments to the Point class\\n self.server = ics_servers.ModbusTCP( devconfig['icsifaces'][0], points.values() )\\n self.server.start()\",\n \"def setUp(self):\\n\\n self.eps = 0.001 # Accept 0.1 % relative error\\n\\n self.RSISE = Point(-35.27456, 149.12065)\\n self.Home = Point(-35.25629, 149.12494) # 28 Scrivener Street, ACT\\n self.Syd = Point(-33.93479, 151.16794) # Sydney Airport\\n self.Nadi = Point(-17.75330, 177.45148) # Nadi Airport\\n self.Kobenhavn = Point(55.70248, 12.58364) # Kobenhavn, Denmark\\n self.Muncar = Point(-8.43, 114.33) # Muncar, Indonesia\",\n \"def initialise_sim(self):\\n pass\",\n \"def setUp(self):\\n self.sampler = {\\n \\\"name\\\": \\\"samplername\\\",\\n \\\"backend_name\\\": \\\"\\\",\\n \\\"backend_header\\\": \\\"\\\",\\n \\\"backend_prefix\\\": \\\"\\\",\\n \\\"backend_suffix\\\": \\\"\\\",\\n \\\"backend_footer\\\": \\\"\\\",\\n \\\"ncores\\\": 2,\\n \\\"threads_per_core\\\": 1,\\n \\\"omp_enabled\\\": True,\\n \\\"papi_enabled\\\": True,\\n \\\"papi_counters_max\\\": 2,\\n \\\"papi_counters_avail\\\": (\\\"C1\\\", \\\"C2\\\", \\\"C3\\\"),\\n \\\"kernels\\\": {\\\"dgemm\\\": (\\n 'dgemm', 'char*', 'char*', 'int*', 'int*', 'int*', 'double*',\\n 'double*', 'int*', 'double*', 'int*', 'double*', 'float*',\\n 'int*'\\n )},\\n \\\"nt_max\\\": random.randint(1, 10),\\n \\\"exe\\\": \\\"x\\\"\\n }\\n self.i = Symbol(\\\"i\\\")\\n self.j = Symbol(\\\"j\\\")\\n self.k = Symbol(\\\"k\\\")\\n self.ns = [random.randint(1, 100) for _ in range(5)]\",\n \"def setUp(self):\\n self.testdatapath = os.path.join(mkdtemp())\\n self.testfilenames = [os.path.join(self.testdatapath, \\\"0001.nc\\\")]\\n\\n self.gpis = [1, 10, 11, 12]\\n self.lons = [0, 0, 1, 1]\\n self.lats = [1, 1, 0, 0]\\n self.cells = [1, 1, 1, 1]\\n self.grid = grids.CellGrid(self.lons, self.lats, self.cells, self.gpis)\",\n \"def setUp(self):\\n self.pgrid = ProcessorGrid(MPI.COMM_WORLD)\\n\\n m = mpisync(randint)(1, 500)\\n n = mpisync(randint)(1, 500)\\n p = mpisync(randint)(1, 4)\\n q = mpisync(randint)(1, 4)\\n dtype = mpisync(choice)([np.int_, np.float_, np.complex])\\n print(\\\"m = {}, n = {}, p = {}, q = {}, dtype = {}\\\".format(\\n m, n, p, q, dtype\\n ))\\n self.m, self.n, self.p, self.q, self.dtype = m, n, p, q, dtype\\n self.mat = DistributedMatrix(self.pgrid, [m, n, p, q], dtype)\",\n \"def setup(self) -> None:\",\n \"def setup(self):\\n\\n self.points = [[0.360502, 0.535494],\\n [0.476489, 0.560185],\\n [0.503125, 0.601218],\\n [0.462382, 0.666667],\\n [0.504702, 0.5]]\\n self.max_neighbors = 4\\n self.beta = 1\\n self.graph = 'beta skeleton'\\n self.edges = [0, 1, 0, 2, 0, 3, 0, 4,\\n 1, 3, 1, 4,\\n 2, 3, 2, 4,\\n 3, 4]\",\n \"def setUp(self):\\n #width, height,obs_list, zombie_list, human_list\\n self.apoc_1 = Apocalypse(5,5, [(1,1)], [(2,2)], [(4,4)])\\n self.apoc_2 = Apocalypse(3,3, [(0,0)], [(1,1),(2,2)], [(0,1),(1,0),(1,1)])\\n self.apoc_3 = Apocalypse(1,1, [], [], [])\",\n \"def setup(self):\\n self.score = 0\\n self.lives = 3\\n self.state = GameStates.RUNNING\\n self.focus_word = None\\n \\n self.star_list = set()\\n self.word_list = set()\\n\\n for _ in range(5):\\n self.create_word()\\n for _ in range(25):\\n self.create_star()\",\n \"def setup(self):\\n\\t\\tpass\",\n \"def setUp(cls):\\n cls.directory = os.path.join(os.path.dirname(os.path.dirname(rmgpy.__file__)), 'examples', 'arkane')\\n cls.level_of_theory = LevelOfTheory(\\\"cbs-qb3\\\")\\n cls.frequencyScaleFactor = 0.99\\n cls.useHinderedRotors = False\\n cls.useBondCorrections = True\",\n \"def setUp(self):\\n # Start the servers and agents\\n super().setUp()\\n\\n self.obj_class = self.params.get(\\\"dfs_oclass\\\", '/run/ior/objectclass/*')\\n self.ior_chu_trs_blk_size = self.params.get(\\n \\\"chunk_block_transfer_sizes\\\", '/run/ior/*')\\n # Fail IOR test in case of Warnings\\n self.fail_on_warning = True\\n self.server_count = len(self.hostlist_servers) * 2\\n # Create the Pool\\n self.create_pool_max_size()\\n self.update_ior_cmd_with_pool()\",\n \"def setup(self):\\n self.testInst = pysat.Instrument('pysat', 'testing2D',\\n clean_level='clean')\\n self.testInst.bounds = (dt.datetime(2008, 1, 1),\\n dt.datetime(2008, 1, 3))\\n self.dname = 'alt_profiles'\\n self.test_vals = np.arange(50) * 1.2\\n self.test_fracs = np.arange(50) / 50.0\\n\\n return\",\n \"def setup(self, name, chem, conc, Kw, D, x_coord, y_coord, dx, dy, dz): \\r\\n self.name = name\\r\\n \\r\\n self.chem = chem # a list of objectives of the class Chemical\\r\\n if chem is None:\\r\\n self.nSpecies = 0\\r\\n elif type(chem) is not list :\\r\\n self.nSpecies = 1\\r\\n else :\\r\\n self.nSpecies = len(chem) # Number of chemcial species\\r\\n self.conc = conc # The dependent variable (named 'conc') of interest\\r\\n self.Kw = Kw\\r\\n self.D = D\\r\\n \\r\\n self.x_coord = x_coord\\r\\n self.y_coord = y_coord\\r\\n self.dx = dx\\r\\n self.dy = dy\\r\\n self.dz = dz\",\n \"def setUp(self):\\n self.setup_beets()\",\n \"def _initialize_tests(self):\\n # Access the sentries for inspecting service units\\n self.compute_sentry = self.d.sentry['nova-compute'][0]\\n self.rabbitmq_sentry = self.d.sentry['rabbitmq-server'][0]\\n self.neutron_api_sentry = self.d.sentry['neutron-api'][0]\\n self.n_ovs_sentry = self.d.sentry['neutron-openvswitch'][0]\\n\\n # pidof is failing to find neutron-server on stein\\n # use pgrep instead.\\n if self._get_openstack_release() >= self.bionic_stein:\\n self.pgrep_full = True\\n else:\\n self.pgrep_full = False\",\n \"def prepare_simulations(self):\\n # Parse all recording sites into a tuple containing the variable name,\\n # segment name and component names\\n for setup in self._simulation_setups:\\n for i, rec in enumerate(setup.record_variables):\\n if rec is None:\\n # Records the voltage in the default segment by default\\n var = 'v'\\n segname = self.default_seg\\n component = None\\n else:\\n parts = rec.split('.')\\n if len(parts) == 1:\\n var = parts[0]\\n segname = self.default_seg\\n component = None\\n elif len(parts) == 2:\\n segname, var = parts\\n component = None\\n else:\\n segname, component, var = parts\\n setup.record_variables[i] = (var, segname, component)\\n # Check to see if there are multiple setups, because if there aren't\\n # the cell can be initialised (they can't in general if there are\\n # multiple as there is only ever one instance of NEURON running)\\n if len(self._simulation_setups) == 1:\\n self._prepare(self._simulation_setups[0])\",\n \"def setup(self):\\n pass\",\n \"def setup_class(cls):\\n # Creating a temporary directory and generating paths for output files\\n cls.tmp_dir = tempfile.mkdtemp()\\n cls.pdb_path = os.path.join(cls.tmp_dir, 'multipdb.pdb')\\n cls.smiles_path = os.path.join(cls.tmp_dir, 'multismiles.smiles')\\n cls.sdf_path = os.path.join(cls.tmp_dir, 'multisdf.sdf')\\n cls.mol2_path = os.path.join(cls.tmp_dir, 'multimol2.mol2')\\n\\n # Rotation matrix to invert z-coordinate, i.e. flip molecule w.r.t. x-y plane\\n rot = np.array([[1, 0, 0], [0, 1, 0], [0, 0, -1]])\\n\\n # Create 2-frame PDB file. First frame is lysozyme, second is lysozyme with inverted z\\n lysozyme_path = examples_paths()['lysozyme']\\n lysozyme = PDBFile(lysozyme_path)\\n\\n # Rotate positions to invert z for the second frame\\n symmetric_pos = lysozyme.getPositions(asNumpy=True).value_in_unit(unit.angstrom)\\n symmetric_pos = symmetric_pos.dot(rot) * unit.angstrom\\n\\n with open(cls.pdb_path, 'w') as f:\\n PDBFile.writeHeader(lysozyme.topology, file=f)\\n PDBFile.writeModel(lysozyme.topology, lysozyme.positions, file=f, modelIndex=0)\\n PDBFile.writeModel(lysozyme.topology, symmetric_pos, file=f, modelIndex=1)\\n\\n # Create 2-molecule SMILES file\\n with open(cls.smiles_path, 'w') as f:\\n f.write('# comment\\\\n')\\n f.write('benzene,c1ccccc1\\\\n')\\n f.write('toluene,Cc1ccccc1\\\\n')\\n\\n # Create 2-molecule sdf and mol2 with OpenEye\\n if utils.is_openeye_installed():\\n from openeye import oechem\\n oe_benzene = utils.load_oe_molecules(examples_paths()['benzene'], molecule_idx=0)\\n oe_benzene_pos = utils.get_oe_mol_positions(oe_benzene).dot(rot)\\n oe_benzene.NewConf(oechem.OEFloatArray(oe_benzene_pos.flatten()))\\n\\n # Save 2-conformer benzene in sdf and mol2 format\\n utils.write_oe_molecule(oe_benzene, cls.sdf_path)\\n utils.write_oe_molecule(oe_benzene, cls.mol2_path, mol2_resname='MOL')\",\n \"def setup(bot):\\n bot.add_cog(Miniscape(bot))\",\n \"def setUp(self):\\n TESTFAMILY = 'H_Abstraction'\\n\\n # set-up RMG object\\n self.rmg = RMG()\\n\\n # load kinetic database and forbidden structures\\n self.rmg.database = RMGDatabase()\\n path = os.path.join(settings['database.directory'])\\n\\n # forbidden structure loading\\n self.rmg.database.loadForbiddenStructures(os.path.join(path, 'forbiddenStructures.py'))\\n # kinetics family loading\\n self.rmg.database.loadKinetics(os.path.join(path, 'kinetics'),\\n kineticsFamilies=[TESTFAMILY],\\n reactionLibraries=[]\\n )\",\n \"def setup(self):\\n self.testInst = pysat.Instrument('pysat', 'testing',\\n clean_level='clean')\\n self.bounds1 = (dt.datetime(2008, 1, 1), dt.datetime(2008, 1, 3))\\n self.bounds2 = (dt.datetime(2009, 1, 1), dt.datetime(2009, 1, 2))\\n\\n return\",\n \"def setup(self):\\n ...\",\n \"def setUpClass(self):\\n self.c = Simulation(logging_level=50)\\n self.c.set_simulation_parameters(\\n seed=1,\\n task=32,\\n output_directory=\\\"output\\\",\\n min_speciation_rate=0.5,\\n sigma=2,\\n tau=2,\\n deme=1,\\n sample_size=0.1,\\n max_time=10,\\n dispersal_relative_cost=1,\\n min_num_species=1,\\n )\\n self.c.set_map_files(\\n sample_file=\\\"sample/SA_samplemaskINT.tif\\\",\\n fine_file=\\\"sample/SA_sample_coarse.tif\\\",\\n dispersal_map=\\\"sample/dispersal_fine.tif\\\",\\n )\\n self.c.run()\",\n \"def setUp(self):\\n program = program_utils.seedProgram()\\n self.profile = profile_utils.seedSOCStudent(program)\",\n \"def setup(self):\\n self.cwd = os.getcwd()\\n self.t = tempfile.mkdtemp()\\n dir_path = Path(\\\"packages\\\")\\n tmp_dir = self.t / dir_path\\n src_dir = self.cwd / Path(ROOT_DIR, dir_path)\\n shutil.copytree(str(src_dir), str(tmp_dir))\\n shutil.copytree(Path(CUR_PATH, \\\"data\\\", \\\"dummy_aea\\\"), Path(self.t, \\\"dummy_aea\\\"))\\n os.chdir(Path(self.t, \\\"dummy_aea\\\"))\\n self.runner = CliRunner()\",\n \"def setUp(self):\\n\\n # Load the data\\n dataset = tagging.data.DataSet.from_fits(DATA_PATH, extension=1)\\n\\n # Assign all as field.\\n dataset.data[\\\"FIELD/CLUSTER\\\"] = \\\"FIELD\\\"\\n\\n # [TODO] Delete benchmarks\\n clusters = (\\\"Cha_I\\\", \\\"Br81\\\", \\\"M15\\\", \\\"NGC2808\\\", \\\"NGC6633\\\", \\\"IC4665\\\", \\n \\\"NGC104\\\", \\\"gamma2_Vel\\\", \\\"GJ880\\\", \\\"NGC4815\\\", \\\"NGC2547\\\", \\\"NGC5927\\\",\\n \\\"NGC4833\\\", \\\"NGC1851\\\", \\\"NGC2243\\\", \\\"NGC3532\\\", \\\"NGC6752\\\", \\\"Br25\\\", \\n \\\"NGC4372\\\", \\\"NGC6705\\\", \\\"M67\\\", \\\"NGC2516\\\", \\\"Trumpler20\\\")\\n\\n # Assign all as members.\\n for cluster in clusters:\\n members = dataset.assign_cluster_members(cluster,\\n lambda row: row[\\\"TARGET\\\"].startswith(cluster))\\n\\n # Special hack:\\n if cluster == \\\"Trumpler20\\\":\\n members += dataset.assign_cluster_members(cluster,\\n lambda row: row[\\\"TARGET\\\"].startswith(\\\"Trumpler_20\\\"))\\n\\n logger.info(\\\"Assigned stars to {} clusters\\\".format(len(clusters)))\\n self.dataset = dataset\\n return None\",\n \"def setup(self):\\r\\n pass\",\n \"def setUp(self):\\n self.shonan = ShonanAveraging3(\\\"toyExample.g2o\\\", DEFAULT_PARAMS)\",\n \"def setUpClass(self):\\n self.coal = Simulation()\\n\\n self.coal.set_simulation_parameters(\\n seed=5, task=4, output_directory=\\\"output\\\", min_speciation_rate=0.1, sigma=4, deme=0.25\\n )\\n self.coal.set_map_files(\\n \\\"null\\\", fine_file=\\\"sample/SA_sample_fine.tif\\\", coarse_file=\\\"sample/SA_sample_coarse.tif\\\"\\n )\\n self.coal.run()\\n self.coal2 = Simulation()\\n\\n self.coal2.set_simulation_parameters(\\n seed=6, task=4, output_directory=\\\"output\\\", min_speciation_rate=0.1, sigma=4, deme=0.01\\n )\\n self.coal2.set_map_files(\\n \\\"null\\\", fine_file=\\\"sample/SA_sample_fine.tif\\\", coarse_file=\\\"sample/SA_sample_coarse.tif\\\"\\n )\\n self.coal2.run()\\n self.tree = CoalescenceTree(self.coal)\\n self.tree2 = CoalescenceTree(self.coal2)\",\n \"def setUpClass(self):\\n self.coal = Simulation()\\n self.tree = CoalescenceTree()\\n self.coal.set_simulation_parameters(\\n 2,\\n 2,\\n \\\"output\\\",\\n 0.1,\\n 4,\\n 4,\\n 1,\\n 1.0,\\n 2,\\n dispersal_relative_cost=1,\\n min_num_species=1,\\n dispersal_method=\\\"normal\\\",\\n m_prob=1,\\n landscape_type=True,\\n )\\n self.coal.set_map_parameters(\\\"null\\\", 10, 10, \\\"null\\\", 10, 10, 0, 0, \\\"null\\\", 20, 20, 0, 0, 1, \\\"null\\\", \\\"null\\\")\\n self.coal.set_speciation_rates([0.1, 0.2])\\n self.coal.run()\\n self.tree.set_database(\\\"output/data_2_2.db\\\")\\n self.tree.calculate_octaves()\\n self.tree.calculate_richness()\",\n \"def setUp(self):\\n self._default_call_inputs = (\\n np.array([[1,2,3], [4,5,6]]),\\n None\\n )\\n\\n self._hash_bins = 10\\n self._hash_embedding_dim = 4\\n self._embedding_dim = 2\\n self._masking = False\\n\\n self._default_config = {\\n \\\"hash_bins\\\": self._hash_bins,\\n \\\"hash_embedding_dim\\\": self._hash_embedding_dim,\\n \\\"embedding_dim\\\": self._embedding_dim,\\n \\\"masking\\\": self._masking\\n }\",\n \"def setup(self):\\n\\n if self.user is 'Daisy':\\n import socket\\n host = socket.gethostname()\\n\\n simName = self.name_prefix[:self.name_prefix.find('_')]\\n\\n if 'ursa' in host:\\n self.raw_sim_dir = '/disk01/rad/sim/' + simName + '/' + self.feedback\\n self.caesar_dir = '/disk01/rad/sim/' + simName + '/' + self.feedback + 'Groups/'\\n self.redshiftFile = '/home/rad/gizmo-extra/outputs_boxspace50.info'\\n self.d_data = '/home/dleung/Downloads/SIGAME_dev/sigame/temp/z' + str(int(self.zCloudy)) + '_data_files/'\\n elif 'flatironinstitute.org' or 'worker' in host:\\n self.raw_sim_dir = '/mnt/ceph/users/daisyleung/simba/sim/' + simName + '/' + self.feedback # dummy\\n self.caesar_dir = '/mnt/ceph/users/daisyleung/simba/sim/' + simName + '/' + self.feedback + 'Groups/'\\n self.redshiftFile = '/mnt/ceph/users/daisyleung/simba/gizmo-extra/outputs_boxspace50.info'\\n self.d_data = '/mnt/home/daisyleung/Downloads/SIGAME_dev/sigame/temp/z' + str(int(self.zCloudy)) + '_data_files/'\\n else:\\n raise NotImplementedError\",\n \"def setUp(self):\\n rmg_path = os.path.normpath(os.path.join(get_path(), '..'))\\n\\n self.settings1 = QMSettings(software='mopac',\\n method='pm3',\\n fileStore=os.path.join(rmg_path, 'testing', 'qm', 'QMfiles'),\\n scratchDirectory=None,\\n onlyCyclics=False,\\n maxRadicalNumber=0,\\n )\\n\\n self.settings2 = QMSettings()\",\n \"def setup(self):\\n\\n logger.info('Setting up SimulatedMaps module.')\\n\\n # Save the cls as a class attribute\\n self.cls = self.read_cls()\\n\\n logger.info('Setup done!')\",\n \"def setup(self):\\n self.create_songs_index()\\n self.create_fingerprints_index()\\n self.delete_unfingerprinted()\",\n \"def setup(self) -> None:\\n pass\",\n \"def setup(self) -> None:\\n pass\",\n \"def setup(self) -> None:\\n pass\",\n \"def setup_class(self):\\n self._tester = self.get_remote('tester').run_prox_with_config(\\\"01_handle_none-gen.cfg\\\", \\\"-e -t\\\")\\n # TODO tester.run_prox_with_config should raise an exception on error, so the below if block can be removed\\n if (self._tester == None):\\n raise IOError(\\\"Could not connect to PROX on the tester system\\\")\\n else:\\n logging.debug(\\\"Connected to PROX on Tester\\\")\\n\\n self._sut = self.get_remote('sut').run_prox_with_config(\\\"01_handle_none-sut.cfg\\\", \\\"-t\\\")\\n if (self._sut == None):\\n raise IOError(\\\"Could not connect to PROX on the SUT\\\")\\n else:\\n logging.debug(\\\"Connected to PROX on SUT\\\")\\n\\n self._cores = [1, 2, 3, 4]\",\n \"def setUpClass(self):\\n self.coal = Simulation()\\n self.tree = CoalescenceTree()\\n self.coal.set_simulation_parameters(\\n 2,\\n 5,\\n \\\"output\\\",\\n 0.1,\\n 4,\\n 4,\\n deme=1,\\n sample_size=1.0,\\n max_time=2,\\n dispersal_relative_cost=1,\\n min_num_species=1,\\n dispersal_method=\\\"normal\\\",\\n )\\n self.coal.set_map_parameters(\\\"null\\\", 10, 10, \\\"null\\\", 10, 10, 0, 0, \\\"null\\\", 20, 20, 0, 0, 1, \\\"null\\\", \\\"null\\\")\\n self.coal.set_speciation_rates([0.1, 0.2])\\n self.coal.run()\\n self.tree.set_database(\\\"output/data_5_2.db\\\")\\n self.tree.calculate_richness()\",\n \"def _setup(self):\\n\\n from AlGDock.topology import Topology\\n self.top = Topology(self.args)\\n self.top_RL = Topology(self.args, includeReceptor=True)\\n\\n # Initialize rmsd calculation function\\n from AlGDock.RMSD import hRMSD\\n self.get_rmsds = hRMSD(self.args.FNs['prmtop']['L'], \\\\\\n self.top.inv_prmtop_atom_order_L)\\n\\n # Obtain reference pose\\n if self.data['CD'].pose > -1:\\n if ('starting_poses' in self.data['CD'].confs.keys()) and \\\\\\n (self.data['CD'].confs['starting_poses'] is not None):\\n starting_pose = np.copy(self.data['CD'].confs['starting_poses'][0])\\n else:\\n (confs, Es) = self._get_confs_to_rescore(site=False, \\\\\\n minimize=False, sort=False)\\n if self.args.params['CD']['pose'] < len(confs):\\n starting_pose = np.copy(confs[self.args.params['CD']['pose']])\\n self.data['CD'].confs['starting_poses'] = [np.copy(starting_pose)]\\n else:\\n self._clear('CD')\\n self._store_infinite_f_RL()\\n raise Exception('Pose index greater than number of poses')\\n else:\\n starting_pose = None\\n\\n from AlGDock.system import System\\n self.system = System(self.args,\\n self.log,\\n self.top,\\n self.top_RL,\\n starting_pose=starting_pose)\\n\\n # Measure the binding site\\n if (self.args.params['CD']['site'] == 'Measure'):\\n self.args.params['CD']['site'] = 'Sphere'\\n if self.args.params['CD']['site_measured'] is not None:\\n (self.args.params['CD']['site_max_R'],self.args.params['CD']['site_center']) = \\\\\\n self.args.params['CD']['site_measured']\\n else:\\n print '\\\\n*** Measuring the binding site ***'\\n self.system.setParams(\\n self.system.paramsFromAlpha(1.0, 'CD', site=False))\\n (confs, Es) = self._get_confs_to_rescore(site=False, minimize=True)\\n if len(confs) > 0:\\n # Use the center of mass for configurations\\n # within 20 RT of the lowest energy\\n cutoffE = Es['total'][-1] + 20 * (R * self.T)\\n coms = []\\n for (conf, E) in reversed(zip(confs, Es['total'])):\\n if E <= cutoffE:\\n self.top.universe.setConfiguration(\\n Configuration(self.top.universe, conf))\\n coms.append(np.array(self.top.universe.centerOfMass()))\\n else:\\n break\\n print ' %d configurations fit in the binding site' % len(coms)\\n coms = np.array(coms)\\n center = (np.min(coms, 0) + np.max(coms, 0)) / 2\\n max_R = max(\\n np.ceil(np.max(np.sqrt(np.sum(\\n (coms - center)**2, 1))) * 10.) / 10., 0.6)\\n self.args.params['CD']['site_max_R'] = max_R\\n self.args.params['CD']['site_center'] = center\\n self.top.universe.setConfiguration(\\n Configuration(self.top.universe, confs[-1]))\\n if ((self.args.params['CD']['site_max_R'] is None) or \\\\\\n (self.args.params['CD']['site_center'] is None)):\\n raise Exception('No binding site parameters!')\\n else:\\n self.args.params['CD']['site_measured'] = \\\\\\n (self.args.params['CD']['site_max_R'], \\\\\\n self.args.params['CD']['site_center'])\\n\\n # Read the reference ligand and receptor coordinates\\n import AlGDock.IO\\n IO_crd = AlGDock.IO.crd()\\n if self.args.FNs['inpcrd']['R'] is not None:\\n if os.path.isfile(self.args.FNs['inpcrd']['L']):\\n lig_crd = IO_crd.read(self.args.FNs['inpcrd']['L'], multiplier=0.1)\\n self.data['CD'].confs['receptor'] = IO_crd.read(\\\\\\n self.args.FNs['inpcrd']['R'], multiplier=0.1)\\n elif self.args.FNs['inpcrd']['RL'] is not None:\\n complex_crd = IO_crd.read(self.args.FNs['inpcrd']['RL'], multiplier=0.1)\\n lig_crd = complex_crd[self.top_RL.L_first_atom:self.top_RL.L_first_atom + \\\\\\n self.top.universe.numberOfAtoms(),:]\\n self.data['CD'].confs['receptor'] = np.vstack(\\\\\\n (complex_crd[:self.top_RL.L_first_atom,:],\\\\\\n complex_crd[self.top_RL.L_first_atom + self.top.universe.numberOfAtoms():,:]))\\n elif self.args.FNs['inpcrd']['L'] is not None:\\n self.data['CD'].confs['receptor'] = None\\n if os.path.isfile(self.args.FNs['inpcrd']['L']):\\n lig_crd = IO_crd.read(self.args.FNs['inpcrd']['L'], multiplier=0.1)\\n else:\\n lig_crd = None\\n\\n if lig_crd is not None:\\n self.data['CD'].confs['ligand'] = lig_crd[self.top.\\n inv_prmtop_atom_order_L, :]\\n self.top.universe.setConfiguration(\\\\\\n Configuration(self.top.universe,self.data['CD'].confs['ligand']))\\n if self.top_RL.universe is not None:\\n self.top_RL.universe.setConfiguration(\\\\\\n Configuration(self.top_RL.universe, \\\\\\n np.vstack((self.data['CD'].confs['receptor'],self.data['CD'].confs['ligand']))))\\n\\n if self.args.params['CD']['rmsd'] is not False:\\n if self.args.params['CD']['rmsd'] is True:\\n if lig_crd is not None:\\n rmsd_crd = lig_crd[self.top.inv_prmtop_atom_order_L, :]\\n else:\\n raise Exception('Reference structure for rmsd calculations unknown')\\n else:\\n rmsd_crd = IO_crd.read(self.args.params['CD']['rmsd'], \\\\\\n natoms=self.top.universe.numberOfAtoms(), multiplier=0.1)\\n rmsd_crd = rmsd_crd[self.top.inv_prmtop_atom_order_L, :]\\n self.data['CD'].confs['rmsd'] = rmsd_crd\\n\\n self.get_rmsds.set_ref_configuration(self.data['CD'].confs['rmsd'])\\n\\n # If configurations are being rescored, start with a docked structure\\n (confs, Es) = self._get_confs_to_rescore(site=False, minimize=False)\\n if len(confs) > 0:\\n self.top.universe.setConfiguration(\\n Configuration(self.top.universe, confs[-1]))\\n\\n from AlGDock.simulation_iterator import SimulationIterator\\n self.iterator = SimulationIterator(self.args, self.top, self.system)\\n\\n # Load progress\\n from AlGDock.postprocessing import Postprocessing\\n Postprocessing(self.args, self.log, self.top, self.top_RL, self.system, self.data, self.save).run(readOnly=True)\\n\\n self.calc_f_L(readOnly=True)\\n self.calc_f_RL(readOnly=True)\\n\\n if self.args.random_seed > 0:\\n np.random.seed(self.args.random_seed)\",\n \"def setUp(self):\\n sumo_bin = sumolib.checkBinary('sumo')\\n traci.start([sumo_bin, \\\"-n\\\", self.network_path, \\\"-r\\\", self.routes_path])\\n traci.simulationStep()\",\n \"def setup(self, phibins = 0, force_create_srcmap=False, overwrite=False, **kwargs):\\n\\n\\tfor c in self.components:\\n\\t loglevel = kwargs.get('loglevel', c.loglevel)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t \\n\\t c.logger.log(loglevel, 'Running setup for component %s',c.name)\\n\\t #use_external_srcmap = c.config['gtlike']['use_external_srcmap']\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t \\n\\t # Run data selection\\n\\t #if not use_external_srcmap:\\n\\t\\t#c._select_data(overwrite=overwrite, **kwargs)\\n\\t # Create LT Cube\\n\\t if c._ext_ltcube is not None:\\n\\t\\tc.logger.log(loglevel, 'Using external LT cube.')\\n\\t else:\\n\\t\\tc._create_ltcube(phibins = phibins, overwrite=overwrite, **kwargs)\\n\\n\\t c.logger.debug('Loading LT Cube %s', c.files['ltcube'])\\n\\t c._ltc = LTCube.create(c.files['ltcube'])\\n\\t \\n\\t # Extract tmin, tmax from LT cube\\n\\t c._tmin = c._ltc.tstart\\n\\t c._tmax = c._ltc.tstop\\n\\t c.logger.debug('Creating PSF model')\\n\\t c._psf = irfs.PSFModel.create(c.roi.skydir, c._ltc,\\n\\t\\tc.config['gtlike']['irfs'],\\n\\t\\tc.config['selection']['evtype'],\\n\\t\\tc.energies)\\n\\n\\t # we don't need this for unbinned analysis\\n\\t # Bin data and create exposure cube\\n\\t #if not use_external_srcmap:\\n\\t\\t#c._bin_data(overwrite=overwrite, **kwargs)\\n\\t\\t#c._create_expcube(overwrite=overwrite, **kwargs)\\n\\t\\t#c._bexp = Map.create_from_fits(c.files['bexpmap'])\\n\\n\\t # compute exposure \\n\\t c._create_expmap(overwrite=overwrite, **kwargs)\\n\\n\\t # Make spatial maps for extended sources\\n\\t for s in c.roi.sources:\\n\\t\\tif s.diffuse:\\n\\t\\t continue\\n\\t\\tif not s.extended:\\n\\t\\t continue\\n\\t\\tc.make_template(s, c.config['file_suffix'])\\n\\t # Write ROI XML\\n\\t c.roi.write_xml(c.files['srcmdl'])\\n\\n\\t # compute diffuse response \\n\\t c._diffrsp(c.files['srcmdl'], overwrite=overwrite, **kwargs)\\n\\n\\t # we don't need this for unbinned\\n\\t # Create source maps file\\n\\t #if force_create_srcmap:\\n\\t#\\tif not use_external_srcmap:\\n\\t#\\t c._create_srcmaps(overwrite=overwrite)\\n\\t if not c.config['data']['cacheft1'] and os.path.isfile(c.files['ft1']):\\n\\t\\tc.logger.debug('Deleting FT1 file.')\\n\\t\\tos.remove(c.files['ft1'])\\n\\n\\t c.logger.log(loglevel, 'Finished setup for component %s',\\n\\t\\tc.name)\\n\\treturn\",\n \"def do_setup_pocs(self, *arg):\\n args, kwargs = string_to_params(*arg)\\n\\n simulator = kwargs.get('simulator', list())\\n if isinstance(simulator, str):\\n simulator = [simulator]\\n\\n # TODO(wtgee) Incorporate real power readings\\n if 'power' not in simulator:\\n simulator.append('power')\\n\\n if 'POCSTIME' in os.environ:\\n print_warning(\\\"Clearing POCSTIME variable\\\")\\n del os.environ['POCSTIME']\\n\\n try:\\n cameras = create_cameras_from_config(simulator=simulator)\\n observatory = Observatory(simulator=simulator, cameras=cameras)\\n self.pocs = POCS(observatory, messaging=True)\\n self.pocs.initialize()\\n except error.PanError as e:\\n print_warning('Problem setting up POCS: {}'.format(e))\",\n \"def _setup_test_infra(world_rank, world_size):\\n os.environ['RANK'] = str(world_rank)\\n os.environ['WORLD_SIZE'] = str(world_size)\\n os.environ['MASTER_ADDR'] = '127.0.0.1'\\n os.environ['MASTER_PORT'] = '29500'\\n\\n set_cuda_device_id(world_rank)\\n\\n dist.init_process_group(backend='nccl', world_size=world_size, rank=world_rank)\",\n \"def setupRun(self):\\n \\n # TBD: for now ignores the \\\"content\\\" of a protocol parameter\\n \\n run = self.run\\n protocolInterface = self.protocolInterface\\n \\n for interfaceParameter in protocolInterface.sortedInterfaceParameters():\\n nmrCalcObject = self.makeNmrCalcData(run, interfaceParameter)\\n \\n self.close()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.68977237","0.68746495","0.65944415","0.6475946","0.64491606","0.6416783","0.63493866","0.6320015","0.62843525","0.62730145","0.62586296","0.621708","0.62119216","0.6208113","0.618722","0.61871713","0.61690503","0.60853016","0.6070992","0.60702187","0.6040254","0.6034298","0.6028555","0.6026642","0.6022751","0.6020598","0.6016242","0.6014492","0.60012","0.5998168","0.59977806","0.5993459","0.5992009","0.59615546","0.5954492","0.59445006","0.5939325","0.5939325","0.5939325","0.5939325","0.5939325","0.5939325","0.5939325","0.5939325","0.5939325","0.5939325","0.5939325","0.5939325","0.5938775","0.5933685","0.59309995","0.59249175","0.5910991","0.5910919","0.590237","0.59003913","0.5899939","0.5899743","0.5894959","0.5893764","0.5883803","0.5881553","0.58797556","0.5878205","0.58719355","0.5870042","0.5869538","0.58663666","0.5856474","0.58547956","0.58502936","0.5849172","0.58478194","0.584491","0.58344805","0.5834228","0.5823796","0.58207667","0.5818091","0.58176094","0.58105236","0.5798373","0.5791579","0.5788116","0.5784614","0.57840484","0.5783507","0.57834345","0.57827103","0.57823807","0.57823807","0.57823807","0.5773799","0.57611156","0.575997","0.57592916","0.5754221","0.57537776","0.57519424","0.5751228"],"string":"[\n \"0.68977237\",\n \"0.68746495\",\n \"0.65944415\",\n \"0.6475946\",\n \"0.64491606\",\n \"0.6416783\",\n \"0.63493866\",\n \"0.6320015\",\n \"0.62843525\",\n \"0.62730145\",\n \"0.62586296\",\n \"0.621708\",\n \"0.62119216\",\n \"0.6208113\",\n \"0.618722\",\n \"0.61871713\",\n \"0.61690503\",\n \"0.60853016\",\n \"0.6070992\",\n \"0.60702187\",\n \"0.6040254\",\n \"0.6034298\",\n \"0.6028555\",\n \"0.6026642\",\n \"0.6022751\",\n \"0.6020598\",\n \"0.6016242\",\n \"0.6014492\",\n \"0.60012\",\n \"0.5998168\",\n \"0.59977806\",\n \"0.5993459\",\n \"0.5992009\",\n \"0.59615546\",\n \"0.5954492\",\n \"0.59445006\",\n \"0.5939325\",\n \"0.5939325\",\n \"0.5939325\",\n \"0.5939325\",\n \"0.5939325\",\n \"0.5939325\",\n \"0.5939325\",\n \"0.5939325\",\n \"0.5939325\",\n \"0.5939325\",\n \"0.5939325\",\n \"0.5939325\",\n \"0.5938775\",\n \"0.5933685\",\n \"0.59309995\",\n \"0.59249175\",\n \"0.5910991\",\n \"0.5910919\",\n \"0.590237\",\n \"0.59003913\",\n \"0.5899939\",\n \"0.5899743\",\n \"0.5894959\",\n \"0.5893764\",\n \"0.5883803\",\n \"0.5881553\",\n \"0.58797556\",\n \"0.5878205\",\n \"0.58719355\",\n \"0.5870042\",\n \"0.5869538\",\n \"0.58663666\",\n \"0.5856474\",\n \"0.58547956\",\n \"0.58502936\",\n \"0.5849172\",\n \"0.58478194\",\n \"0.584491\",\n \"0.58344805\",\n \"0.5834228\",\n \"0.5823796\",\n \"0.58207667\",\n \"0.5818091\",\n \"0.58176094\",\n \"0.58105236\",\n \"0.5798373\",\n \"0.5791579\",\n \"0.5788116\",\n \"0.5784614\",\n \"0.57840484\",\n \"0.5783507\",\n \"0.57834345\",\n \"0.57827103\",\n \"0.57823807\",\n \"0.57823807\",\n \"0.57823807\",\n \"0.5773799\",\n \"0.57611156\",\n \"0.575997\",\n \"0.57592916\",\n \"0.5754221\",\n \"0.57537776\",\n \"0.57519424\",\n \"0.5751228\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6524442"},"document_rank":{"kind":"string","value":"3"}}},{"rowIdx":81471,"cells":{"query":{"kind":"string","value":"Test that the number of spins can be properly counted. The function tested is pipe_control.mol_res_spin.count_spins()."},"document":{"kind":"string","value":"def test_count_spins(self):\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 4)\n self.assertEqual(mol_res_spin.count_spins(skip_desel=False), 8)\n self.assertEqual(mol_res_spin.count_spins(selection='@N5'), 1)\n self.assertEqual(mol_res_spin.count_spins(selection='@N5', skip_desel=False), 2)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_count_no_spins(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 0)","def test_count_spins_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Test for the error.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.count_spins)","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def _n_spin_states(self) -> int:\n if self.spin is None:\n raise Exception(\n \"cannot request number of spin states for spinless fermions\"\n )\n return round(2 * self.spin + 1)","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def _get_slr_count(slot_list: List[Slot]) -> int:\n slr_count_list = [slot.board.SLR_NUM for slot in slot_list]\n assert all(slr_count_list[i] == slr_count_list[0] for i in range(len(slr_count_list)))\n return slr_count_list[0]","def test_svm_count():\n assert templates.svms() > 0","def test_spin_loop(self):\n\n # Spin data.\n select = [1, 0]\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, 'N5')\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 2)","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def nspins(self):\n return len(self)","def test_svm_vs_vm_count():\n assert templates.svms() >= templates.vm_count()","def getNumRings(self, nPins, silent=False):\n numPositions = 0\n for nRings in itertools.count(0):\n numPositions += self.getNumPosInRing(nRings)\n if not silent and numPositions > nPins:\n runLog.warning(\n \"{0} does not fit exactly into a cartisian grid of any number of rings. \"\n \"Rounding up to {1} rings which can hold {2} pins)\"\n \"\".format(nPins, nRings, numPositions),\n single=True,\n label=\"Non-exact number of positions in cartesian lattice\",\n )\n if numPositions >= nPins:\n return nRings","def test_count_resources(ops_and_shots, expected_resources):\n ops, shots = ops_and_shots\n computed_resources = _count_resources(QuantumScript(ops=ops, shots=shots))\n assert computed_resources == expected_resources","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_svm_vs_vm_count():\n assert environments.svms() >= environments.vm_count()","def spine_switch_count(self):\n spines = GetSwitchDetails().get_spine_switch_ip()\n totalSpines = len(spines)\n return totalSpines","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_pressure_count(self):\n self.assertEqual(self.Pcount, 7)","def test_count_173(self):\n value: int = 173\n result: int = 55\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_1719(self):\n value: int = 2645\n result: int = 1113\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_2645(self):\n value: int = 1719\n result: int = 723\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_own_count(self):\n self._test_count_func(it_count)","def test_count_1_000_000_000_000_000_000(self):\n value: int = 1_000_000_000_000_000_000\n result: int = 264160473575034274\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count(self):\n self._test_count_func(count)","def test_count_361_080(self):\n value: int = 361_080\n result: int = 188_067\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_459(self):\n value: int = 459\n result: int = 148\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_10(self):\n value: int = 10\n result: int = 2\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def testSectionCount(self):\n\n self.sectionCount(3640)","def test_counter(self):\n self.assertEqual(self._n_registered, 1)","def test_count_9(self):\n value: int = 9\n result: int = 2\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_361_077(self):\n value: int = 361_077\n result: int = 188_065\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_35(self):\n value: int = 35\n result: int = 6\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def test_count_0(self):\n self.assertEqual(count(0), 0, 'Between 0 and 0, there is 0 lucky numbers.')","def test_count_361_000(self):\n value: int = 361_000\n result: int = 187_995\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def calc_score(pins_stats):\n count = 0\n new = pins_stats[:, :2] - ORIG_PINS_LOC\n for p in new:\n if np.linalg.norm(p) > R_PIN / 2:\n count += 1\n return count","def getNumRings(self, nPins, silent=False):\n nRings = hexagon.numRingsToHoldNumCells(nPins)\n if not silent:\n nPinsFullRings = self.getNumPositions(rings=nRings)\n if nPins != nPinsFullRings:\n runLog.warning(\n \"{0} does not fit exactly into a hex grid of any number of rings. \"\n \"Rounding up to {1} rings which can hold {2} pins)\"\n \"\".format(nPins, nRings, nPinsFullRings),\n single=True,\n label=\"Non-exact number of positions in hex lattice\",\n )\n return nRings","def test_count_361_087(self):\n value: int = 361_087\n result: int = 188_067\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_72(self):\n value: int = 72\n result: int = 21\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_20(self):\n value: int = 20\n result: int = 4\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_66(self):\n value: int = 66\n result: int = 18\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def count_turns(spline):\n func = spline(spline._data[0])\n turns = sum(abs(diff(sign(diff(func))))) / 2\n return turns","def test_count_361_070(self):\n value: int = 361_070\n result: int = 188_058\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_getSampleCount(self):\r\n self.assertEqual(self.res1.getSampleCount(), 0)\r\n\r\n self.res1.addSample('S1', 42)\r\n self.assertEqual(self.res1.getSampleCount(), 1)\r\n\r\n self.res1.addSample('S2', 43)\r\n self.assertEqual(self.res1.getSampleCount(), 2)","def test_svm_count():\n assert environments.svms() > 0\n count = 0\n for l in list(environments.data):\n e = environments[l]\n count += e.svms\n msg = ('SVM count mismatch. Environments says: ' +\n str(environments.svms()) +\n ', actual count: ' + str(count))\n assert count == environments.svms(), msg","def runcount(test_keys, sigma, sigma_max, sigma_step,\n npoints_min, npoints_max, npoints_step):\n run = 1\n for key in test_keys:\n if key:\n while sigma < sigma_max:\n npoints = npoints_min\n while npoints < npoints_max:\n npoints += npoints_step\n run += 1\n sigma += sigma_step\n return run","def count():","def test_add_spawning_profile():\n center = Coordinates(1 , 1)\n radius = 10\n speed_limit = 20\n\n i = Intersection(center, radius, speed_limit)\n\n assert not i.get_spawning_profile_list()\n\n default_driver = DriverProfile(\"Default\", 8, 2, 2, 0, 30, 3, 1)\n default_vehicle = VehicleProfile(\"Default\", 5, 15, 2, 2, 1000, 65)\n default_spawn = SpawningProfile(\"Default\", default_driver, default_vehicle)\n spawn2 = SpawningProfile(\"spawn2\", default_driver, default_vehicle)\n\n i.add_spawning_profile(default_spawn)\n\n assert i.get_spawning_profile_list()\n assert len(i.get_spawning_profile_list()) == 1\n\n i.add_spawning_profile(spawn2)\n\n assert len(i.get_spawning_profile_list()) == 2","def test_spin_loop_no_selection(self):\n\n # Spin data.\n select = [0, 1, 0, 0, 1, 1, 0, 1]\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 8)","def test_count_883_904(self):\n value: int = 883_904\n result: int = 475_749\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def testCounting(self):\n \n clk = Signal(0)\n clock_gen = ClkDriver(clk, period=4)\n \n for i in range(1, 6):\n #print \"Testing\", i, \"bits\"\n out = Signal(intbv(0)[i:])\n prev_out = Signal(intbv(2**i - 1)[i:])\n counter = Counter(out, clk, Signal(1))\n \n # make sure it increments and wraps at modulo 2^n\n @always(clk.posedge)\n def test():\n #print out, prev_out\n self.assertEqual(int(out), int((prev_out + 1) % 2**(len(prev_out))))\n prev_out.next = out\n \n sim = Simulation(counter, clock_gen, test)\n sim.run(12 * 2**i, quiet=1)","def test_amount_of_listings(self):\n listings = steam_market.get_total_amount_of_listings(soup=get_soup_from_path(TEST_FILE_NORMAL_LISTING))\n self.assertEqual(10, listings)","def test_count_6_645_243(self):\n value: int = 6_645_243\n result: int = 3_615_948\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def count_single_spikes_and_bursts(info):\r\n\r\n singles = 0\r\n bursts = 0\r\n inBurst = False\r\n\r\n spikesperbursts = []\r\n spb = 2\r\n\r\n prev_start = -1000\r\n prev_end = -1000\r\n for spike in info:\r\n if spike[0] - prev_end > 80:\r\n #print('single:', spike[0])\r\n singles += 1\r\n if inBurst:\r\n spikesperbursts.append(spb)\r\n inBurst = False\r\n else:\r\n #print('burst:',inBurst, spike[0])\r\n if not inBurst:\r\n spb = 2\r\n singles -=1\r\n bursts += 1\r\n else:\r\n spb += 1\r\n inBurst = True\r\n prev_start = spike[0]\r\n prev_end = spike[1]\r\n return singles, bursts, spikesperbursts, sum(spikesperbursts)/len(spikesperbursts)","def test_count_880_000(self):\n value: int = 880_000\n result: int = 472_910\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_770(self):\n value: int = 770\n result: int = 306\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_666(self):\n value: int = 666\n result: int = 264\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_get_spawning_profile_list():\n center = Coordinates(1 , 1)\n radius = 10\n speed_limit = 20\n default_driver = DriverProfile(\"Default\", 8, 2, 2, 0, 30, 3, 1)\n default_vehicle = VehicleProfile(\"Default\", 5, 15, 2, 2, 1000, 65)\n default_spawn = SpawningProfile(\"Default\", default_driver, default_vehicle)\n\n i = Intersection(center, radius, speed_limit)\n\n l = i.get_spawning_profile_list()\n\n assert not l\n\n i.add_spawning_profile(default_spawn)\n\n assert l\n\n assert len(l) == 1\n\n i.remove_spawning_profile(default_spawn)\n\n assert len(l) == 0\n assert not l","def test_count_reads_in_region_total(self):\n self.c.skipZeros = False\n self.c.stepSize = 200\n self.c.binLength = 200\n resp, _ = self.c.count_reads_in_region(self.chrom, 0, 200)\n nt.assert_equal(resp, np.array([[2, 4.]]))","def test_solvation_potassium_control(self):\n waters = np.random.randint(1000, 10000)\n log.debug('Trying {} waters with potassium...'.format(waters))\n solvate(tleapfile='./cb6-but/tleap.in', pdbfile='cb6-but.pdb',\n bufferwater=waters, counter_cation='K+')\n potassium = sp.check_output([\"grep -oh 'K+' ./cb6-but/solvated.prmtop | wc -w\"],\n shell=True)\n self.assertEqual(int(potassium), 0)","def test_count_reads_per_cluster(self):\n \n bedtool = pybedtools.BedTool(clipper.test_file(\"clip_analysis_test_peak_results.bed\"))\n \n total_reads, reads_per_cluster = count_reads_per_cluster(bedtool, None)\n \n self.assertListEqual([147,52, 239, 85, 47, 119, 58, 588, 92, 59, 196, 36], reads_per_cluster)\n self.assertEqual(sum([147,52, 239, 85, 47, 119, 58, 588, 92, 59, 196, 36]), total_reads)","def count_benchmarks():\n return len(setup_storage().fetch_benchmark({}))","def test_results_length(spheroid_convex_fixture):\n assert(len(spheroid_convex_fixture.pairs) == 1000)\n assert(len(spheroid_convex_fixture.combinations) == 1000)\n assert(len(spheroid_convex_fixture.deltas) == 1000)","def test_count_increments():\n\n # Signals and interface etc.\n clk = Clock()\n reset = Reset(async=True)\n count = Signal(intbv()[8:])\n\n def _bench():\n dut = Cosimulation('vvp -m ./myhdl.vpi ./bin/example_module/example_module', \n clk=clk, \n reset=reset,\n count=count)\n\n @instance\n def stimulus():\n yield delay(255 * 2 + 4)\n print(count)\n assert count == 0xff\n raise StopSimulation\n\n return dut, clk.gen(), reset.pulse(), stimulus\n\n # = traceSignals(_bench)\n Simulation(_bench()).run()","def test_count_800_000(self):\n value: int = 800_000\n result: int = 426_983\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_count_7000(self):\n value: int = 7000\n result: int = 3333\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def Count():\n return CheckForError(lib.Generators_Get_Count())","def test_number_of_regions(i07_nexus: I07Nexus, correct_num):\n assert i07_nexus._number_of_regions == correct_num","def _is_valid_count(self, count: int, gp: GriddedPerm) -> bool:\n return self._point_in_fuse_region(gp) + 1 == count","def test_count_773_904(self):\n value: int = 773_904\n result: int = 412_264\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def countObjects(inputImb, inputIma):\n\n lb = label(inputImb)\n obefore = len(regionprops(lb))\n lbc = label(1 - inputImb, connectivity=1)\n ocbefore = len(regionprops(lbc))\n la = label(inputIma)\n oafter = len(regionprops(la))\n lac = label(1 - inputIma, connectivity=1)\n ocafter = len(regionprops(lac))\n\n if obefore == oafter and ocbefore == ocafter:\n deletableTemp = 1\n else:\n deletableTemp = 0\n\n return deletableTemp","def count_spikes(spk):\n shspk = numpy.shape(spk)\n if len(shspk) == 0:\n nspk = 0\n elif shspk[0] == 0:\n nspk = 0\n else:\n nspk = shspk[0]\n return(nspk)","def test_data_source_soaps_count_get(self):\n pass","def test_counts(contrib_data):\n ## Find the probands - they should always contribute their own alleles\n P = ped.Pedigree(args.pedfile)\n\n ## TODO: Test individuals with multiple offspring +p2 id:112\n ## Case when no regions are specified - only all probands\n regions = contrib_data.keys()\n if len(regions) == 1:\n all_contribs = contrib_data[regions[0]]\n for prob in P.probands:\n ## Probands should always contribute 1 allele\n assert all_contribs[prob, 1] == args.iterations\n\n ## Test specific individuals\n counts = Counter(all_contribs[11])\n binomial_sd = np.sqrt(args.iterations * 0.25)\n mean = np.mean(counts.values())\n conf95 = (mean - 2 * binomial_sd, mean + 2 * binomial_sd)\n\n for count in counts.values():\n assert conf95[0] < count < conf95[1]","def test_num_circs_shots(self):\n backend = FakeValencia()\n generator = Generator(backend)\n max_experiments = 5\n max_shots = 10\n backend._configuration.max_experiments = max_experiments\n backend._configuration.max_shots = max_shots\n sub_tests = [1, 3*max_shots, 3*max_shots+1, 3*max_shots-1,\n 3*max_shots*2, 3*max_shots*2+1, 3*max_shots*max_experiments-1]\n for num_raw_bits in sub_tests:\n with self.subTest(num_raw_bits=num_raw_bits):\n result = generator.sample(num_raw_bits=num_raw_bits).block_until_ready()\n self.assertGreaterEqual(len(result.raw_bits), num_raw_bits)","def test_getTotalIndividualCount(self):\r\n # Verified with iNEXT.\r\n self.assertEqual(self.est1.getTotalIndividualCount(), 15)\r\n\r\n # Verified against results in Colwell 2012 paper.\r\n self.assertEqual(self.est2.getTotalIndividualCount(), 976)\r\n self.assertEqual(self.est3.getTotalIndividualCount(), 237)","def test_get_resource_license_resource_count_list(self):\n pass","def test_update_ncount(self):\n sim_interface = SimInterface(setup_populated_instr_McStas())\n sim_interface.show_interface()\n\n fake_change = FakeChange(new=100)\n sim_interface.update_ncount(fake_change)\n self.assertEqual(sim_interface.ncount, 100)","def test_count_5(self):\n value: int = 5\n result: int = 0\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_sinc_list():\n x,sc = cw04.gen_sinc_list(-1,1,3)\n desired = [0.8414709848078965, 1.0 , 0.8414709848078965]\n print(\"Obtained:\",sc)\n print(\"Desired:\",desired)\n # For comparing floating point values, nose has useful helper functions\n # to ensure they are equal up to a numerical precision tolerance\n nose.tools.assert_almost_equal(sc, desired)","def sight_resight_count(nvisit1, nvisit2, resight):\n import math\n\n try:\n nvisit1 = float(nvisit1)\n nvisit2 = float(nvisit2)\n resight = float(resight)\n pl_index = int(math.ceil((nvisit1 * nvisit2) / resight))\n pl_error_num = float((nvisit1 ** 2) * nvisit2 * (nvisit2 - resight))\n pl_error_dom = float(resight ** 3)\n pl_error = int(math.ceil(1.96 * math.sqrt(pl_error_num / pl_error_dom)))\n except ZeroDivisionError:\n # pl_index = 'Undefined - Zero recaptured (k = 0)'\n pl_index = 0\n pl_error = 0\n return pl_index, pl_error","def test_amount_of_listings_many_listings(self):\n listings = steam_market.get_total_amount_of_listings(soup=get_soup_from_path(TEST_FILE_MANY_RESULTS))\n self.assertEqual(164720, listings)","def test_count_roll_fail():\n expected = np.array([3, 0, 1, 5, 0, 0])\n result = analyze_roll.count_roll(np.array([1, 1, 3, 1, 4, 4]))\n assert np.array_equal(expected, result) is False","def test_getSampleCount(self):\r\n self.assertEqual(self.estimator1.getSampleCount(), 1)","def test_count_700_000(self):\n value: int = 700_000\n result: int = 374_421\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def count() -> int:\n pass","def test_count_roll():\n expected = np.array([3, 0, 1, 2, 0, 0])\n result = analyze_roll.count_roll(np.array([1, 1, 3, 1, 4, 4]))\n assert np.array_equal(expected, result) is True","def count_standard_residues(self):\n n = 0\n for na in self.iter_standard_residues():\n n += 1\n return n","def num_trials(self):","def _count_occupied_seats(grid: List[List[str]]) -> int:\n total = 0\n for row in grid:\n total += row.count('#')\n return total","def test_final_result():\n img = cv2.imread(os.path.join(TESTS_ASSETS_VISION_DIR, \"mussels_sample.PNG\"))\n _orig, _circles_removed, _blurred_and_smoothed, _convex_hull, _mussels_found, _mussels_count = count_mussels(img)\n final_result = _mussels_count\n assert final_result == 8","def count_inside(self):\n time.sleep(2) #1\n self.count += 1","def test_spin_loop_wildcard(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N*'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_simulator_0_shots():\n dev = _aws_device(wires=2, device_type=AwsDeviceType.SIMULATOR, shots=0)\n assert dev.shots == 1\n assert dev.analytic","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_bababc():\n assert part_01.count_for('bababc', 2) == 1\n assert part_01.count_for('bababc', 3) == 1","def test_count_770_000(self):\n value: int = 770_000\n result: int = 410_562\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_total_procs():\n result = _run_metric('total_procs')\n assert result.exit_code == 0"],"string":"[\n \"def test_count_no_spins(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Test the number of spins counted.\\n self.assertEqual(mol_res_spin.count_spins(), 0)\",\n \"def test_count_spins_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Test for the error.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.count_spins)\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def _n_spin_states(self) -> int:\\n if self.spin is None:\\n raise Exception(\\n \\\"cannot request number of spin states for spinless fermions\\\"\\n )\\n return round(2 * self.spin + 1)\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def _get_slr_count(slot_list: List[Slot]) -> int:\\n slr_count_list = [slot.board.SLR_NUM for slot in slot_list]\\n assert all(slr_count_list[i] == slr_count_list[0] for i in range(len(slr_count_list)))\\n return slr_count_list[0]\",\n \"def test_svm_count():\\n assert templates.svms() > 0\",\n \"def test_spin_loop(self):\\n\\n # Spin data.\\n select = [1, 0]\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, 'N5')\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 2)\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def nspins(self):\\n return len(self)\",\n \"def test_svm_vs_vm_count():\\n assert templates.svms() >= templates.vm_count()\",\n \"def getNumRings(self, nPins, silent=False):\\n numPositions = 0\\n for nRings in itertools.count(0):\\n numPositions += self.getNumPosInRing(nRings)\\n if not silent and numPositions > nPins:\\n runLog.warning(\\n \\\"{0} does not fit exactly into a cartisian grid of any number of rings. \\\"\\n \\\"Rounding up to {1} rings which can hold {2} pins)\\\"\\n \\\"\\\".format(nPins, nRings, numPositions),\\n single=True,\\n label=\\\"Non-exact number of positions in cartesian lattice\\\",\\n )\\n if numPositions >= nPins:\\n return nRings\",\n \"def test_count_resources(ops_and_shots, expected_resources):\\n ops, shots = ops_and_shots\\n computed_resources = _count_resources(QuantumScript(ops=ops, shots=shots))\\n assert computed_resources == expected_resources\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_svm_vs_vm_count():\\n assert environments.svms() >= environments.vm_count()\",\n \"def spine_switch_count(self):\\n spines = GetSwitchDetails().get_spine_switch_ip()\\n totalSpines = len(spines)\\n return totalSpines\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_pressure_count(self):\\n self.assertEqual(self.Pcount, 7)\",\n \"def test_count_173(self):\\n value: int = 173\\n result: int = 55\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_1719(self):\\n value: int = 2645\\n result: int = 1113\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_2645(self):\\n value: int = 1719\\n result: int = 723\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_own_count(self):\\n self._test_count_func(it_count)\",\n \"def test_count_1_000_000_000_000_000_000(self):\\n value: int = 1_000_000_000_000_000_000\\n result: int = 264160473575034274\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count(self):\\n self._test_count_func(count)\",\n \"def test_count_361_080(self):\\n value: int = 361_080\\n result: int = 188_067\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_459(self):\\n value: int = 459\\n result: int = 148\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_10(self):\\n value: int = 10\\n result: int = 2\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def testSectionCount(self):\\n\\n self.sectionCount(3640)\",\n \"def test_counter(self):\\n self.assertEqual(self._n_registered, 1)\",\n \"def test_count_9(self):\\n value: int = 9\\n result: int = 2\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_361_077(self):\\n value: int = 361_077\\n result: int = 188_065\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_35(self):\\n value: int = 35\\n result: int = 6\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def test_count_0(self):\\n self.assertEqual(count(0), 0, 'Between 0 and 0, there is 0 lucky numbers.')\",\n \"def test_count_361_000(self):\\n value: int = 361_000\\n result: int = 187_995\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def calc_score(pins_stats):\\n count = 0\\n new = pins_stats[:, :2] - ORIG_PINS_LOC\\n for p in new:\\n if np.linalg.norm(p) > R_PIN / 2:\\n count += 1\\n return count\",\n \"def getNumRings(self, nPins, silent=False):\\n nRings = hexagon.numRingsToHoldNumCells(nPins)\\n if not silent:\\n nPinsFullRings = self.getNumPositions(rings=nRings)\\n if nPins != nPinsFullRings:\\n runLog.warning(\\n \\\"{0} does not fit exactly into a hex grid of any number of rings. \\\"\\n \\\"Rounding up to {1} rings which can hold {2} pins)\\\"\\n \\\"\\\".format(nPins, nRings, nPinsFullRings),\\n single=True,\\n label=\\\"Non-exact number of positions in hex lattice\\\",\\n )\\n return nRings\",\n \"def test_count_361_087(self):\\n value: int = 361_087\\n result: int = 188_067\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_72(self):\\n value: int = 72\\n result: int = 21\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_20(self):\\n value: int = 20\\n result: int = 4\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_66(self):\\n value: int = 66\\n result: int = 18\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def count_turns(spline):\\n func = spline(spline._data[0])\\n turns = sum(abs(diff(sign(diff(func))))) / 2\\n return turns\",\n \"def test_count_361_070(self):\\n value: int = 361_070\\n result: int = 188_058\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_getSampleCount(self):\\r\\n self.assertEqual(self.res1.getSampleCount(), 0)\\r\\n\\r\\n self.res1.addSample('S1', 42)\\r\\n self.assertEqual(self.res1.getSampleCount(), 1)\\r\\n\\r\\n self.res1.addSample('S2', 43)\\r\\n self.assertEqual(self.res1.getSampleCount(), 2)\",\n \"def test_svm_count():\\n assert environments.svms() > 0\\n count = 0\\n for l in list(environments.data):\\n e = environments[l]\\n count += e.svms\\n msg = ('SVM count mismatch. Environments says: ' +\\n str(environments.svms()) +\\n ', actual count: ' + str(count))\\n assert count == environments.svms(), msg\",\n \"def runcount(test_keys, sigma, sigma_max, sigma_step,\\n npoints_min, npoints_max, npoints_step):\\n run = 1\\n for key in test_keys:\\n if key:\\n while sigma < sigma_max:\\n npoints = npoints_min\\n while npoints < npoints_max:\\n npoints += npoints_step\\n run += 1\\n sigma += sigma_step\\n return run\",\n \"def count():\",\n \"def test_add_spawning_profile():\\n center = Coordinates(1 , 1)\\n radius = 10\\n speed_limit = 20\\n\\n i = Intersection(center, radius, speed_limit)\\n\\n assert not i.get_spawning_profile_list()\\n\\n default_driver = DriverProfile(\\\"Default\\\", 8, 2, 2, 0, 30, 3, 1)\\n default_vehicle = VehicleProfile(\\\"Default\\\", 5, 15, 2, 2, 1000, 65)\\n default_spawn = SpawningProfile(\\\"Default\\\", default_driver, default_vehicle)\\n spawn2 = SpawningProfile(\\\"spawn2\\\", default_driver, default_vehicle)\\n\\n i.add_spawning_profile(default_spawn)\\n\\n assert i.get_spawning_profile_list()\\n assert len(i.get_spawning_profile_list()) == 1\\n\\n i.add_spawning_profile(spawn2)\\n\\n assert len(i.get_spawning_profile_list()) == 2\",\n \"def test_spin_loop_no_selection(self):\\n\\n # Spin data.\\n select = [0, 1, 0, 0, 1, 1, 0, 1]\\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 8)\",\n \"def test_count_883_904(self):\\n value: int = 883_904\\n result: int = 475_749\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def testCounting(self):\\n \\n clk = Signal(0)\\n clock_gen = ClkDriver(clk, period=4)\\n \\n for i in range(1, 6):\\n #print \\\"Testing\\\", i, \\\"bits\\\"\\n out = Signal(intbv(0)[i:])\\n prev_out = Signal(intbv(2**i - 1)[i:])\\n counter = Counter(out, clk, Signal(1))\\n \\n # make sure it increments and wraps at modulo 2^n\\n @always(clk.posedge)\\n def test():\\n #print out, prev_out\\n self.assertEqual(int(out), int((prev_out + 1) % 2**(len(prev_out))))\\n prev_out.next = out\\n \\n sim = Simulation(counter, clock_gen, test)\\n sim.run(12 * 2**i, quiet=1)\",\n \"def test_amount_of_listings(self):\\n listings = steam_market.get_total_amount_of_listings(soup=get_soup_from_path(TEST_FILE_NORMAL_LISTING))\\n self.assertEqual(10, listings)\",\n \"def test_count_6_645_243(self):\\n value: int = 6_645_243\\n result: int = 3_615_948\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def count_single_spikes_and_bursts(info):\\r\\n\\r\\n singles = 0\\r\\n bursts = 0\\r\\n inBurst = False\\r\\n\\r\\n spikesperbursts = []\\r\\n spb = 2\\r\\n\\r\\n prev_start = -1000\\r\\n prev_end = -1000\\r\\n for spike in info:\\r\\n if spike[0] - prev_end > 80:\\r\\n #print('single:', spike[0])\\r\\n singles += 1\\r\\n if inBurst:\\r\\n spikesperbursts.append(spb)\\r\\n inBurst = False\\r\\n else:\\r\\n #print('burst:',inBurst, spike[0])\\r\\n if not inBurst:\\r\\n spb = 2\\r\\n singles -=1\\r\\n bursts += 1\\r\\n else:\\r\\n spb += 1\\r\\n inBurst = True\\r\\n prev_start = spike[0]\\r\\n prev_end = spike[1]\\r\\n return singles, bursts, spikesperbursts, sum(spikesperbursts)/len(spikesperbursts)\",\n \"def test_count_880_000(self):\\n value: int = 880_000\\n result: int = 472_910\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_770(self):\\n value: int = 770\\n result: int = 306\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_666(self):\\n value: int = 666\\n result: int = 264\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_get_spawning_profile_list():\\n center = Coordinates(1 , 1)\\n radius = 10\\n speed_limit = 20\\n default_driver = DriverProfile(\\\"Default\\\", 8, 2, 2, 0, 30, 3, 1)\\n default_vehicle = VehicleProfile(\\\"Default\\\", 5, 15, 2, 2, 1000, 65)\\n default_spawn = SpawningProfile(\\\"Default\\\", default_driver, default_vehicle)\\n\\n i = Intersection(center, radius, speed_limit)\\n\\n l = i.get_spawning_profile_list()\\n\\n assert not l\\n\\n i.add_spawning_profile(default_spawn)\\n\\n assert l\\n\\n assert len(l) == 1\\n\\n i.remove_spawning_profile(default_spawn)\\n\\n assert len(l) == 0\\n assert not l\",\n \"def test_count_reads_in_region_total(self):\\n self.c.skipZeros = False\\n self.c.stepSize = 200\\n self.c.binLength = 200\\n resp, _ = self.c.count_reads_in_region(self.chrom, 0, 200)\\n nt.assert_equal(resp, np.array([[2, 4.]]))\",\n \"def test_solvation_potassium_control(self):\\n waters = np.random.randint(1000, 10000)\\n log.debug('Trying {} waters with potassium...'.format(waters))\\n solvate(tleapfile='./cb6-but/tleap.in', pdbfile='cb6-but.pdb',\\n bufferwater=waters, counter_cation='K+')\\n potassium = sp.check_output([\\\"grep -oh 'K+' ./cb6-but/solvated.prmtop | wc -w\\\"],\\n shell=True)\\n self.assertEqual(int(potassium), 0)\",\n \"def test_count_reads_per_cluster(self):\\n \\n bedtool = pybedtools.BedTool(clipper.test_file(\\\"clip_analysis_test_peak_results.bed\\\"))\\n \\n total_reads, reads_per_cluster = count_reads_per_cluster(bedtool, None)\\n \\n self.assertListEqual([147,52, 239, 85, 47, 119, 58, 588, 92, 59, 196, 36], reads_per_cluster)\\n self.assertEqual(sum([147,52, 239, 85, 47, 119, 58, 588, 92, 59, 196, 36]), total_reads)\",\n \"def count_benchmarks():\\n return len(setup_storage().fetch_benchmark({}))\",\n \"def test_results_length(spheroid_convex_fixture):\\n assert(len(spheroid_convex_fixture.pairs) == 1000)\\n assert(len(spheroid_convex_fixture.combinations) == 1000)\\n assert(len(spheroid_convex_fixture.deltas) == 1000)\",\n \"def test_count_increments():\\n\\n # Signals and interface etc.\\n clk = Clock()\\n reset = Reset(async=True)\\n count = Signal(intbv()[8:])\\n\\n def _bench():\\n dut = Cosimulation('vvp -m ./myhdl.vpi ./bin/example_module/example_module', \\n clk=clk, \\n reset=reset,\\n count=count)\\n\\n @instance\\n def stimulus():\\n yield delay(255 * 2 + 4)\\n print(count)\\n assert count == 0xff\\n raise StopSimulation\\n\\n return dut, clk.gen(), reset.pulse(), stimulus\\n\\n # = traceSignals(_bench)\\n Simulation(_bench()).run()\",\n \"def test_count_800_000(self):\\n value: int = 800_000\\n result: int = 426_983\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_count_7000(self):\\n value: int = 7000\\n result: int = 3333\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def Count():\\n return CheckForError(lib.Generators_Get_Count())\",\n \"def test_number_of_regions(i07_nexus: I07Nexus, correct_num):\\n assert i07_nexus._number_of_regions == correct_num\",\n \"def _is_valid_count(self, count: int, gp: GriddedPerm) -> bool:\\n return self._point_in_fuse_region(gp) + 1 == count\",\n \"def test_count_773_904(self):\\n value: int = 773_904\\n result: int = 412_264\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def countObjects(inputImb, inputIma):\\n\\n lb = label(inputImb)\\n obefore = len(regionprops(lb))\\n lbc = label(1 - inputImb, connectivity=1)\\n ocbefore = len(regionprops(lbc))\\n la = label(inputIma)\\n oafter = len(regionprops(la))\\n lac = label(1 - inputIma, connectivity=1)\\n ocafter = len(regionprops(lac))\\n\\n if obefore == oafter and ocbefore == ocafter:\\n deletableTemp = 1\\n else:\\n deletableTemp = 0\\n\\n return deletableTemp\",\n \"def count_spikes(spk):\\n shspk = numpy.shape(spk)\\n if len(shspk) == 0:\\n nspk = 0\\n elif shspk[0] == 0:\\n nspk = 0\\n else:\\n nspk = shspk[0]\\n return(nspk)\",\n \"def test_data_source_soaps_count_get(self):\\n pass\",\n \"def test_counts(contrib_data):\\n ## Find the probands - they should always contribute their own alleles\\n P = ped.Pedigree(args.pedfile)\\n\\n ## TODO: Test individuals with multiple offspring +p2 id:112\\n ## Case when no regions are specified - only all probands\\n regions = contrib_data.keys()\\n if len(regions) == 1:\\n all_contribs = contrib_data[regions[0]]\\n for prob in P.probands:\\n ## Probands should always contribute 1 allele\\n assert all_contribs[prob, 1] == args.iterations\\n\\n ## Test specific individuals\\n counts = Counter(all_contribs[11])\\n binomial_sd = np.sqrt(args.iterations * 0.25)\\n mean = np.mean(counts.values())\\n conf95 = (mean - 2 * binomial_sd, mean + 2 * binomial_sd)\\n\\n for count in counts.values():\\n assert conf95[0] < count < conf95[1]\",\n \"def test_num_circs_shots(self):\\n backend = FakeValencia()\\n generator = Generator(backend)\\n max_experiments = 5\\n max_shots = 10\\n backend._configuration.max_experiments = max_experiments\\n backend._configuration.max_shots = max_shots\\n sub_tests = [1, 3*max_shots, 3*max_shots+1, 3*max_shots-1,\\n 3*max_shots*2, 3*max_shots*2+1, 3*max_shots*max_experiments-1]\\n for num_raw_bits in sub_tests:\\n with self.subTest(num_raw_bits=num_raw_bits):\\n result = generator.sample(num_raw_bits=num_raw_bits).block_until_ready()\\n self.assertGreaterEqual(len(result.raw_bits), num_raw_bits)\",\n \"def test_getTotalIndividualCount(self):\\r\\n # Verified with iNEXT.\\r\\n self.assertEqual(self.est1.getTotalIndividualCount(), 15)\\r\\n\\r\\n # Verified against results in Colwell 2012 paper.\\r\\n self.assertEqual(self.est2.getTotalIndividualCount(), 976)\\r\\n self.assertEqual(self.est3.getTotalIndividualCount(), 237)\",\n \"def test_get_resource_license_resource_count_list(self):\\n pass\",\n \"def test_update_ncount(self):\\n sim_interface = SimInterface(setup_populated_instr_McStas())\\n sim_interface.show_interface()\\n\\n fake_change = FakeChange(new=100)\\n sim_interface.update_ncount(fake_change)\\n self.assertEqual(sim_interface.ncount, 100)\",\n \"def test_count_5(self):\\n value: int = 5\\n result: int = 0\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_sinc_list():\\n x,sc = cw04.gen_sinc_list(-1,1,3)\\n desired = [0.8414709848078965, 1.0 , 0.8414709848078965]\\n print(\\\"Obtained:\\\",sc)\\n print(\\\"Desired:\\\",desired)\\n # For comparing floating point values, nose has useful helper functions\\n # to ensure they are equal up to a numerical precision tolerance\\n nose.tools.assert_almost_equal(sc, desired)\",\n \"def sight_resight_count(nvisit1, nvisit2, resight):\\n import math\\n\\n try:\\n nvisit1 = float(nvisit1)\\n nvisit2 = float(nvisit2)\\n resight = float(resight)\\n pl_index = int(math.ceil((nvisit1 * nvisit2) / resight))\\n pl_error_num = float((nvisit1 ** 2) * nvisit2 * (nvisit2 - resight))\\n pl_error_dom = float(resight ** 3)\\n pl_error = int(math.ceil(1.96 * math.sqrt(pl_error_num / pl_error_dom)))\\n except ZeroDivisionError:\\n # pl_index = 'Undefined - Zero recaptured (k = 0)'\\n pl_index = 0\\n pl_error = 0\\n return pl_index, pl_error\",\n \"def test_amount_of_listings_many_listings(self):\\n listings = steam_market.get_total_amount_of_listings(soup=get_soup_from_path(TEST_FILE_MANY_RESULTS))\\n self.assertEqual(164720, listings)\",\n \"def test_count_roll_fail():\\n expected = np.array([3, 0, 1, 5, 0, 0])\\n result = analyze_roll.count_roll(np.array([1, 1, 3, 1, 4, 4]))\\n assert np.array_equal(expected, result) is False\",\n \"def test_getSampleCount(self):\\r\\n self.assertEqual(self.estimator1.getSampleCount(), 1)\",\n \"def test_count_700_000(self):\\n value: int = 700_000\\n result: int = 374_421\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def count() -> int:\\n pass\",\n \"def test_count_roll():\\n expected = np.array([3, 0, 1, 2, 0, 0])\\n result = analyze_roll.count_roll(np.array([1, 1, 3, 1, 4, 4]))\\n assert np.array_equal(expected, result) is True\",\n \"def count_standard_residues(self):\\n n = 0\\n for na in self.iter_standard_residues():\\n n += 1\\n return n\",\n \"def num_trials(self):\",\n \"def _count_occupied_seats(grid: List[List[str]]) -> int:\\n total = 0\\n for row in grid:\\n total += row.count('#')\\n return total\",\n \"def test_final_result():\\n img = cv2.imread(os.path.join(TESTS_ASSETS_VISION_DIR, \\\"mussels_sample.PNG\\\"))\\n _orig, _circles_removed, _blurred_and_smoothed, _convex_hull, _mussels_found, _mussels_count = count_mussels(img)\\n final_result = _mussels_count\\n assert final_result == 8\",\n \"def count_inside(self):\\n time.sleep(2) #1\\n self.count += 1\",\n \"def test_spin_loop_wildcard(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N*'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_simulator_0_shots():\\n dev = _aws_device(wires=2, device_type=AwsDeviceType.SIMULATOR, shots=0)\\n assert dev.shots == 1\\n assert dev.analytic\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_bababc():\\n assert part_01.count_for('bababc', 2) == 1\\n assert part_01.count_for('bababc', 3) == 1\",\n \"def test_count_770_000(self):\\n value: int = 770_000\\n result: int = 410_562\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_total_procs():\\n result = _run_metric('total_procs')\\n assert result.exit_code == 0\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.8216668","0.79208726","0.6061253","0.59907717","0.5961885","0.59412616","0.59404606","0.59132665","0.5879472","0.5839816","0.5767341","0.57627225","0.5760211","0.5658254","0.5647766","0.56327945","0.5631395","0.5559625","0.55477506","0.5539356","0.54946417","0.54895943","0.54789454","0.54513824","0.54492533","0.5446411","0.5446173","0.54459035","0.54400736","0.5434825","0.54339117","0.5428919","0.5421709","0.5396782","0.5390711","0.5384566","0.5383599","0.53643805","0.53641784","0.5359458","0.53414875","0.5340149","0.5334811","0.5321325","0.53180397","0.5312851","0.5309244","0.5290805","0.5289168","0.5288518","0.52610546","0.52586013","0.52553165","0.5250255","0.5247397","0.5240108","0.5238773","0.52355236","0.5228555","0.5226584","0.5222649","0.5221744","0.5220698","0.52113205","0.5206592","0.5205135","0.5196224","0.5189809","0.518671","0.51863545","0.5185375","0.5171892","0.51709706","0.51649654","0.5152365","0.51505506","0.5148432","0.51447475","0.51441735","0.51427805","0.5139691","0.5136202","0.5127037","0.5105122","0.5100687","0.5098355","0.50942624","0.5091694","0.50871885","0.5084768","0.50809085","0.50804883","0.5079553","0.5074056","0.50727075","0.50518566","0.5051323","0.50290275","0.5024593","0.50215226"],"string":"[\n \"0.8216668\",\n \"0.79208726\",\n \"0.6061253\",\n \"0.59907717\",\n \"0.5961885\",\n \"0.59412616\",\n \"0.59404606\",\n \"0.59132665\",\n \"0.5879472\",\n \"0.5839816\",\n \"0.5767341\",\n \"0.57627225\",\n \"0.5760211\",\n \"0.5658254\",\n \"0.5647766\",\n \"0.56327945\",\n \"0.5631395\",\n \"0.5559625\",\n \"0.55477506\",\n \"0.5539356\",\n \"0.54946417\",\n \"0.54895943\",\n \"0.54789454\",\n \"0.54513824\",\n \"0.54492533\",\n \"0.5446411\",\n \"0.5446173\",\n \"0.54459035\",\n \"0.54400736\",\n \"0.5434825\",\n \"0.54339117\",\n \"0.5428919\",\n \"0.5421709\",\n \"0.5396782\",\n \"0.5390711\",\n \"0.5384566\",\n \"0.5383599\",\n \"0.53643805\",\n \"0.53641784\",\n \"0.5359458\",\n \"0.53414875\",\n \"0.5340149\",\n \"0.5334811\",\n \"0.5321325\",\n \"0.53180397\",\n \"0.5312851\",\n \"0.5309244\",\n \"0.5290805\",\n \"0.5289168\",\n \"0.5288518\",\n \"0.52610546\",\n \"0.52586013\",\n \"0.52553165\",\n \"0.5250255\",\n \"0.5247397\",\n \"0.5240108\",\n \"0.5238773\",\n \"0.52355236\",\n \"0.5228555\",\n \"0.5226584\",\n \"0.5222649\",\n \"0.5221744\",\n \"0.5220698\",\n \"0.52113205\",\n \"0.5206592\",\n \"0.5205135\",\n \"0.5196224\",\n \"0.5189809\",\n \"0.518671\",\n \"0.51863545\",\n \"0.5185375\",\n \"0.5171892\",\n \"0.51709706\",\n \"0.51649654\",\n \"0.5152365\",\n \"0.51505506\",\n \"0.5148432\",\n \"0.51447475\",\n \"0.51441735\",\n \"0.51427805\",\n \"0.5139691\",\n \"0.5136202\",\n \"0.5127037\",\n \"0.5105122\",\n \"0.5100687\",\n \"0.5098355\",\n \"0.50942624\",\n \"0.5091694\",\n \"0.50871885\",\n \"0.5084768\",\n \"0.50809085\",\n \"0.50804883\",\n \"0.5079553\",\n \"0.5074056\",\n \"0.50727075\",\n \"0.50518566\",\n \"0.5051323\",\n \"0.50290275\",\n \"0.5024593\",\n \"0.50215226\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.87852323"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81472,"cells":{"query":{"kind":"string","value":"Test that the number of spins (zero) can be properly counted. The function tested is pipe_control.mol_res_spin.count_spins()."},"document":{"kind":"string","value":"def test_count_no_spins(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 0)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_count_spins(self):\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 4)\n self.assertEqual(mol_res_spin.count_spins(skip_desel=False), 8)\n self.assertEqual(mol_res_spin.count_spins(selection='@N5'), 1)\n self.assertEqual(mol_res_spin.count_spins(selection='@N5', skip_desel=False), 2)","def test_count_spins_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Test for the error.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.count_spins)","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def _n_spin_states(self) -> int:\n if self.spin is None:\n raise Exception(\n \"cannot request number of spin states for spinless fermions\"\n )\n return round(2 * self.spin + 1)","def test_svm_count():\n assert templates.svms() > 0","def test_count_0(self):\n self.assertEqual(count(0), 0, 'Between 0 and 0, there is 0 lucky numbers.')","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def _get_slr_count(slot_list: List[Slot]) -> int:\n slr_count_list = [slot.board.SLR_NUM for slot in slot_list]\n assert all(slr_count_list[i] == slr_count_list[0] for i in range(len(slr_count_list)))\n return slr_count_list[0]","def test_spin_loop(self):\n\n # Spin data.\n select = [1, 0]\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, 'N5')\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 2)","def nspins(self):\n return len(self)","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def test_svm_vs_vm_count():\n assert templates.svms() >= templates.vm_count()","def getNumRings(self, nPins, silent=False):\n numPositions = 0\n for nRings in itertools.count(0):\n numPositions += self.getNumPosInRing(nRings)\n if not silent and numPositions > nPins:\n runLog.warning(\n \"{0} does not fit exactly into a cartisian grid of any number of rings. \"\n \"Rounding up to {1} rings which can hold {2} pins)\"\n \"\".format(nPins, nRings, numPositions),\n single=True,\n label=\"Non-exact number of positions in cartesian lattice\",\n )\n if numPositions >= nPins:\n return nRings","def count_turns(spline):\n func = spline(spline._data[0])\n turns = sum(abs(diff(sign(diff(func))))) / 2\n return turns","def test_init():\n mesh = CuboidMesh(nx=100, ny=1, nz=1)\n sim = Sim(mesh)\n sim.set_m(init_m)\n\n expected = np.array([0, 0, 1,\n 0, np.sin(0.1), np.cos(0.1)])\n\n assert max(abs(sim.spin[:6] - expected)) < 1e-15","def count_spikes(spk):\n shspk = numpy.shape(spk)\n if len(shspk) == 0:\n nspk = 0\n elif shspk[0] == 0:\n nspk = 0\n else:\n nspk = shspk[0]\n return(nspk)","def test_svm_vs_vm_count():\n assert environments.svms() >= environments.vm_count()","def test_count_resources(ops_and_shots, expected_resources):\n ops, shots = ops_and_shots\n computed_resources = _count_resources(QuantumScript(ops=ops, shots=shots))\n assert computed_resources == expected_resources","def test_spin_loop_no_selection(self):\n\n # Spin data.\n select = [0, 1, 0, 0, 1, 1, 0, 1]\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 8)","def test_count_1_000_000_000_000_000_000(self):\n value: int = 1_000_000_000_000_000_000\n result: int = 264160473575034274\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def spine_switch_count(self):\n spines = GetSwitchDetails().get_spine_switch_ip()\n totalSpines = len(spines)\n return totalSpines","def test_count_361_080(self):\n value: int = 361_080\n result: int = 188_067\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_pressure_count(self):\n self.assertEqual(self.Pcount, 7)","def test_counter_start_at_zero(self):\n pass","def test_count_1719(self):\n value: int = 2645\n result: int = 1113\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_simulator_0_shots():\n dev = _aws_device(wires=2, device_type=AwsDeviceType.SIMULATOR, shots=0)\n assert dev.shots == 1\n assert dev.analytic","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_count_173(self):\n value: int = 173\n result: int = 55\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_361_077(self):\n value: int = 361_077\n result: int = 188_065\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_counter(self):\n self.assertEqual(self._n_registered, 1)","def test_snc_closed_segment(grid):\n space = bempp.api.function_space(\n grid, \"SNC\", 0, segments=[1], include_boundary_dofs=True\n )\n\n for elem_index in range(grid.number_of_elements):\n if space.support[elem_index]:\n assert _np.all(space.local_multipliers[elem_index] != 0)\n else:\n assert _np.all(space.local_multipliers[elem_index] == 0)","def test_count_ways_null():\n assert f.count_ways(0) == 1","def test_count_2645(self):\n value: int = 1719\n result: int = 723\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_returns_zero_for_empty_grid(self):\n grid = []\n result = num_islands(grid)\n self.assertEqual(result, 0)","def test_own_count(self):\n self._test_count_func(it_count)","def test_count_roll_fail():\n expected = np.array([3, 0, 1, 5, 0, 0])\n result = analyze_roll.count_roll(np.array([1, 1, 3, 1, 4, 4]))\n assert np.array_equal(expected, result) is False","def test_count_increments():\n\n # Signals and interface etc.\n clk = Clock()\n reset = Reset(async=True)\n count = Signal(intbv()[8:])\n\n def _bench():\n dut = Cosimulation('vvp -m ./myhdl.vpi ./bin/example_module/example_module', \n clk=clk, \n reset=reset,\n count=count)\n\n @instance\n def stimulus():\n yield delay(255 * 2 + 4)\n print(count)\n assert count == 0xff\n raise StopSimulation\n\n return dut, clk.gen(), reset.pulse(), stimulus\n\n # = traceSignals(_bench)\n Simulation(_bench()).run()","def calc_score(pins_stats):\n count = 0\n new = pins_stats[:, :2] - ORIG_PINS_LOC\n for p in new:\n if np.linalg.norm(p) > R_PIN / 2:\n count += 1\n return count","def NumberOfEmptySpots(self):\n\n return np.count_nonzero(self.state == EMPTY)","def test_count_459(self):\n value: int = 459\n result: int = 148\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def countObjects(inputImb, inputIma):\n\n lb = label(inputImb)\n obefore = len(regionprops(lb))\n lbc = label(1 - inputImb, connectivity=1)\n ocbefore = len(regionprops(lbc))\n la = label(inputIma)\n oafter = len(regionprops(la))\n lac = label(1 - inputIma, connectivity=1)\n ocafter = len(regionprops(lac))\n\n if obefore == oafter and ocbefore == ocafter:\n deletableTemp = 1\n else:\n deletableTemp = 0\n\n return deletableTemp","def test_sinc_list():\n x,sc = cw04.gen_sinc_list(-1,1,3)\n desired = [0.8414709848078965, 1.0 , 0.8414709848078965]\n print(\"Obtained:\",sc)\n print(\"Desired:\",desired)\n # For comparing floating point values, nose has useful helper functions\n # to ensure they are equal up to a numerical precision tolerance\n nose.tools.assert_almost_equal(sc, desired)","def test_solvation_potassium_control(self):\n waters = np.random.randint(1000, 10000)\n log.debug('Trying {} waters with potassium...'.format(waters))\n solvate(tleapfile='./cb6-but/tleap.in', pdbfile='cb6-but.pdb',\n bufferwater=waters, counter_cation='K+')\n potassium = sp.check_output([\"grep -oh 'K+' ./cb6-but/solvated.prmtop | wc -w\"],\n shell=True)\n self.assertEqual(int(potassium), 0)","def test_count_ways_positive(inputs, outputs):\n assert f.count_ways(inputs) == outputs","def getNumRings(self, nPins, silent=False):\n nRings = hexagon.numRingsToHoldNumCells(nPins)\n if not silent:\n nPinsFullRings = self.getNumPositions(rings=nRings)\n if nPins != nPinsFullRings:\n runLog.warning(\n \"{0} does not fit exactly into a hex grid of any number of rings. \"\n \"Rounding up to {1} rings which can hold {2} pins)\"\n \"\".format(nPins, nRings, nPinsFullRings),\n single=True,\n label=\"Non-exact number of positions in hex lattice\",\n )\n return nRings","def testCounting(self):\n \n clk = Signal(0)\n clock_gen = ClkDriver(clk, period=4)\n \n for i in range(1, 6):\n #print \"Testing\", i, \"bits\"\n out = Signal(intbv(0)[i:])\n prev_out = Signal(intbv(2**i - 1)[i:])\n counter = Counter(out, clk, Signal(1))\n \n # make sure it increments and wraps at modulo 2^n\n @always(clk.posedge)\n def test():\n #print out, prev_out\n self.assertEqual(int(out), int((prev_out + 1) % 2**(len(prev_out))))\n prev_out.next = out\n \n sim = Simulation(counter, clock_gen, test)\n sim.run(12 * 2**i, quiet=1)","def test_count_9(self):\n value: int = 9\n result: int = 2\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_shared_cards_are_zero(self):\n self.assertEqual(len(self.hand.sharedCards), 0)","def get_zero_nonzero_idx(spins):\n idx_zero = spins.index(0)\n idx_nonzero = tuple([idx for idx, spin in enumerate(spins) if spin != 0])\n if len(idx_nonzero) + 1 != len(spins):\n raise ValueError(\"`spins` must contain exactly one zero.\")\n return idx_zero, idx_nonzero","def test_svm_count():\n assert environments.svms() > 0\n count = 0\n for l in list(environments.data):\n e = environments[l]\n count += e.svms\n msg = ('SVM count mismatch. Environments says: ' +\n str(environments.svms()) +\n ', actual count: ' + str(count))\n assert count == environments.svms(), msg","def test_count_10(self):\n value: int = 10\n result: int = 2\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_count_35(self):\n value: int = 35\n result: int = 6\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_361_087(self):\n value: int = 361_087\n result: int = 188_067\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_361_000(self):\n value: int = 361_000\n result: int = 187_995\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def testSectionCount(self):\n\n self.sectionCount(3640)","def test_count_361_070(self):\n value: int = 361_070\n result: int = 188_058\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_reads_in_region_total(self):\n self.c.skipZeros = False\n self.c.stepSize = 200\n self.c.binLength = 200\n resp, _ = self.c.count_reads_in_region(self.chrom, 0, 200)\n nt.assert_equal(resp, np.array([[2, 4.]]))","def test_negative_electrode_potential_profile(self):\n np.testing.assert_array_almost_equal(self.phi_s_n(self.t, x=0), 0, decimal=5)","def count_single_spikes_and_bursts(info):\r\n\r\n singles = 0\r\n bursts = 0\r\n inBurst = False\r\n\r\n spikesperbursts = []\r\n spb = 2\r\n\r\n prev_start = -1000\r\n prev_end = -1000\r\n for spike in info:\r\n if spike[0] - prev_end > 80:\r\n #print('single:', spike[0])\r\n singles += 1\r\n if inBurst:\r\n spikesperbursts.append(spb)\r\n inBurst = False\r\n else:\r\n #print('burst:',inBurst, spike[0])\r\n if not inBurst:\r\n spb = 2\r\n singles -=1\r\n bursts += 1\r\n else:\r\n spb += 1\r\n inBurst = True\r\n prev_start = spike[0]\r\n prev_end = spike[1]\r\n return singles, bursts, spikesperbursts, sum(spikesperbursts)/len(spikesperbursts)","def test_getSampleCount(self):\r\n self.assertEqual(self.res1.getSampleCount(), 0)\r\n\r\n self.res1.addSample('S1', 42)\r\n self.assertEqual(self.res1.getSampleCount(), 1)\r\n\r\n self.res1.addSample('S2', 43)\r\n self.assertEqual(self.res1.getSampleCount(), 2)","def test_count_66(self):\n value: int = 66\n result: int = 18\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def count():","def test_count_880_000(self):\n value: int = 880_000\n result: int = 472_910\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def _is_valid_count(self, count: int, gp: GriddedPerm) -> bool:\n return self._point_in_fuse_region(gp) + 1 == count","def runcount(test_keys, sigma, sigma_max, sigma_step,\n npoints_min, npoints_max, npoints_step):\n run = 1\n for key in test_keys:\n if key:\n while sigma < sigma_max:\n npoints = npoints_min\n while npoints < npoints_max:\n npoints += npoints_step\n run += 1\n sigma += sigma_step\n return run","def test_count(self):\n self._test_count_func(count)","def sight_resight_count(nvisit1, nvisit2, resight):\n import math\n\n try:\n nvisit1 = float(nvisit1)\n nvisit2 = float(nvisit2)\n resight = float(resight)\n pl_index = int(math.ceil((nvisit1 * nvisit2) / resight))\n pl_error_num = float((nvisit1 ** 2) * nvisit2 * (nvisit2 - resight))\n pl_error_dom = float(resight ** 3)\n pl_error = int(math.ceil(1.96 * math.sqrt(pl_error_num / pl_error_dom)))\n except ZeroDivisionError:\n # pl_index = 'Undefined - Zero recaptured (k = 0)'\n pl_index = 0\n pl_error = 0\n return pl_index, pl_error","def test_count_72(self):\n value: int = 72\n result: int = 21\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_amount_of_listings_no_listings(self):\n listings = steam_market.get_total_amount_of_listings(soup=get_soup_from_path(TEST_FILE_NO_RESULTS))\n self.assertEqual(0, listings)","def run_null(parcellation, scale, spintype):\n\n nsdata = load_data(parcellation, scale)\n\n # run the damn thing\n print(f'Running {spintype:>9} spins for {scale}: ', end='', flush=True)\n out = NSDIR / parcellation / 'nulls' / spintype / f'{scale}_nulls.csv'\n if out.exists():\n permcorrs = np.loadtxt(out).reshape(-1, 1)\n elif spintype == 'cornblath':\n # even though we're working with parcellated data we need to project\n # that to the surface + spin the vertices, so let's load our\n # pre-generated vertex-level spins\n spins = SPDIR / 'vertex' / 'vazquez-rodriguez' / 'fsaverage5_spins.csv'\n\n # get annotation files\n fetcher = getattr(nndata, f\"fetch_{parcellation.replace('atl-', '')}\")\n annotations = fetcher('fsaverage5', data_dir=ROIDIR)[scale]\n\n # pre-load the spins for this function (assumes `spins` is array)\n # permdata will be an (R, T, n_rotate) array\n print('Pre-loading spins...', end='\\b' * 20, flush=True)\n spins = np.loadtxt(spins, delimiter=',', dtype='int32')\n permdata = nnsurf.spin_data(nsdata, version='fsaverage5',\n lhannot=annotations.lh,\n rhannot=annotations.rh,\n spins=spins, n_rotate=spins.shape[-1],\n verbose=True)\n permcorrs = np.vstack([\n _get_permcorr(nsdata, permdata[..., n])\n for n in range(permdata.shape[-1])\n ])\n putils.save_dir(out, permcorrs)\n elif spintype in ['burt2018', 'burt2020']:\n surrdir = SURRDIR / parcellation / spintype / 'neurosynth'\n # generate the permuted data from the surrogate resampling arrays\n print('Generating surrogates...', end='\\b' * 24, flush=True)\n permdata = get_surrogates(nsdata, surrdir, scale)\n permcorrs = np.vstack([\n _get_permcorr(nsdata, permdata[..., n])\n for n in range(permdata.shape[-1])\n ])\n putils.save_dir(out, permcorrs)\n elif spintype == 'moran':\n surrogates = np.zeros((*nsdata.shape, 10000))\n for hemi, dist, idx in putils.yield_data_dist(DISTDIR, parcellation,\n scale, nsdata):\n mrs = moran.MoranRandomization(joint=True, n_rep=10000,\n tol=1e-6, random_state=1234)\n mrs.fit(dist)\n surrogates[idx] = mrs.randomize(hemi).transpose(1, 2, 0)\n\n permcorrs = np.vstack([\n _get_permcorr(nsdata, surrogates[..., n])\n for n in range(surrogates.shape[-1])\n ])\n putils.save_dir(out, permcorrs)\n else:\n spins = SPDIR / parcellation / spintype / f'{scale}_spins.csv'\n permcorrs = gen_permcorrs(nsdata, spins, out)\n\n nsdata = nsdata.dropna(axis=0, how='all')\n pvals = get_fwe(np.corrcoef(nsdata.T), permcorrs)\n\n out = pd.DataFrame(dict(\n parcellation=parcellation,\n scale=scale,\n spintype=spintype,\n n_sig=np.sum(np.triu(pvals < ALPHA, k=1))\n ), index=[0])\n\n return out","def test_qpu_0_shots():\n _aws_device(wires=2, shots=0)","def get_nrof_pumps(self):\n pumps = 0\n for p in self.pump_array:\n if p:\n pumps += 1\n return pumps","def test_count_20(self):\n value: int = 20\n result: int = 4\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_800_000(self):\n value: int = 800_000\n result: int = 426_983\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_roll():\n expected = np.array([3, 0, 1, 2, 0, 0])\n result = analyze_roll.count_roll(np.array([1, 1, 3, 1, 4, 4]))\n assert np.array_equal(expected, result) is True","def test_count_7000(self):\n value: int = 7000\n result: int = 3333\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_770(self):\n value: int = 770\n result: int = 306\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def count_standard_residues(self):\n n = 0\n for na in self.iter_standard_residues():\n n += 1\n return n","def test_withCountIntervalZero(self):\n clock = task.Clock()\n accumulator = []\n\n def foo(cnt):\n accumulator.append(cnt)\n if len(accumulator) > 4:\n loop.stop()\n\n loop = task.LoopingCall.withCount(foo)\n loop.clock = clock\n deferred = loop.start(0, now=False)\n\n clock.advance(0)\n self.successResultOf(deferred)\n\n self.assertEqual([1, 1, 1, 1, 1], accumulator)","def count() -> int:\n pass","def test_count_883_904(self):\n value: int = 883_904\n result: int = 475_749\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_666(self):\n value: int = 666\n result: int = 264\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_6_645_243(self):\n value: int = 6_645_243\n result: int = 3_615_948\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_count_5(self):\n value: int = 5\n result: int = 0\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","async def test_txn_list_with_zero_count(self):\n response = await self.get_assert_status('/transactions?count=0', 400)\n\n self.assert_has_valid_error(response, 53)","def count_benchmarks():\n return len(setup_storage().fetch_benchmark({}))","def Count():\n return CheckForError(lib.Generators_Get_Count())","def _success_count(cls, samples: Samples) -> int:\n return cls.__sample_count(samples, \"true\")","def test_count_700_000(self):\n value: int = 700_000\n result: int = 374_421\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_song_counts(self):\n self.assertEqual(self.show.total_song_count, None)","def test_vm_count():\n assert templates.vm_count() > 0","def test_measure(self):\n\n result = qubit.measure(polarization)\n self.assertEqual(0, result)","def monte_carlo_trials(nb_trials, nb_ok, lock):\n\n # First perform the trials\n # Do not use shared resource because other processes doesn't need to know\n # about computation step\n nb_in_quarter_results = 0\n for i in range(nb_trials):\n x = random.uniform(0, 1)\n y = random.uniform(0, 1)\n if x * x + y * y <= 1.0:\n nb_in_quarter_results += 1\n\n # Finally update shared resource\n # Do it only once, then processes doesn't struggle with each other to\n # update it\n with lock:\n nb_ok.value += nb_in_quarter_results","def test_count_reads_per_cluster(self):\n \n bedtool = pybedtools.BedTool(clipper.test_file(\"clip_analysis_test_peak_results.bed\"))\n \n total_reads, reads_per_cluster = count_reads_per_cluster(bedtool, None)\n \n self.assertListEqual([147,52, 239, 85, 47, 119, 58, 588, 92, 59, 196, 36], reads_per_cluster)\n self.assertEqual(sum([147,52, 239, 85, 47, 119, 58, 588, 92, 59, 196, 36]), total_reads)","def test_total_procs():\n result = _run_metric('total_procs')\n assert result.exit_code == 0"],"string":"[\n \"def test_count_spins(self):\\n\\n # Test the number of spins counted.\\n self.assertEqual(mol_res_spin.count_spins(), 4)\\n self.assertEqual(mol_res_spin.count_spins(skip_desel=False), 8)\\n self.assertEqual(mol_res_spin.count_spins(selection='@N5'), 1)\\n self.assertEqual(mol_res_spin.count_spins(selection='@N5', skip_desel=False), 2)\",\n \"def test_count_spins_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Test for the error.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.count_spins)\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def _n_spin_states(self) -> int:\\n if self.spin is None:\\n raise Exception(\\n \\\"cannot request number of spin states for spinless fermions\\\"\\n )\\n return round(2 * self.spin + 1)\",\n \"def test_svm_count():\\n assert templates.svms() > 0\",\n \"def test_count_0(self):\\n self.assertEqual(count(0), 0, 'Between 0 and 0, there is 0 lucky numbers.')\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def _get_slr_count(slot_list: List[Slot]) -> int:\\n slr_count_list = [slot.board.SLR_NUM for slot in slot_list]\\n assert all(slr_count_list[i] == slr_count_list[0] for i in range(len(slr_count_list)))\\n return slr_count_list[0]\",\n \"def test_spin_loop(self):\\n\\n # Spin data.\\n select = [1, 0]\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, 'N5')\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 2)\",\n \"def nspins(self):\\n return len(self)\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_svm_vs_vm_count():\\n assert templates.svms() >= templates.vm_count()\",\n \"def getNumRings(self, nPins, silent=False):\\n numPositions = 0\\n for nRings in itertools.count(0):\\n numPositions += self.getNumPosInRing(nRings)\\n if not silent and numPositions > nPins:\\n runLog.warning(\\n \\\"{0} does not fit exactly into a cartisian grid of any number of rings. \\\"\\n \\\"Rounding up to {1} rings which can hold {2} pins)\\\"\\n \\\"\\\".format(nPins, nRings, numPositions),\\n single=True,\\n label=\\\"Non-exact number of positions in cartesian lattice\\\",\\n )\\n if numPositions >= nPins:\\n return nRings\",\n \"def count_turns(spline):\\n func = spline(spline._data[0])\\n turns = sum(abs(diff(sign(diff(func))))) / 2\\n return turns\",\n \"def test_init():\\n mesh = CuboidMesh(nx=100, ny=1, nz=1)\\n sim = Sim(mesh)\\n sim.set_m(init_m)\\n\\n expected = np.array([0, 0, 1,\\n 0, np.sin(0.1), np.cos(0.1)])\\n\\n assert max(abs(sim.spin[:6] - expected)) < 1e-15\",\n \"def count_spikes(spk):\\n shspk = numpy.shape(spk)\\n if len(shspk) == 0:\\n nspk = 0\\n elif shspk[0] == 0:\\n nspk = 0\\n else:\\n nspk = shspk[0]\\n return(nspk)\",\n \"def test_svm_vs_vm_count():\\n assert environments.svms() >= environments.vm_count()\",\n \"def test_count_resources(ops_and_shots, expected_resources):\\n ops, shots = ops_and_shots\\n computed_resources = _count_resources(QuantumScript(ops=ops, shots=shots))\\n assert computed_resources == expected_resources\",\n \"def test_spin_loop_no_selection(self):\\n\\n # Spin data.\\n select = [0, 1, 0, 0, 1, 1, 0, 1]\\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 8)\",\n \"def test_count_1_000_000_000_000_000_000(self):\\n value: int = 1_000_000_000_000_000_000\\n result: int = 264160473575034274\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def spine_switch_count(self):\\n spines = GetSwitchDetails().get_spine_switch_ip()\\n totalSpines = len(spines)\\n return totalSpines\",\n \"def test_count_361_080(self):\\n value: int = 361_080\\n result: int = 188_067\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_pressure_count(self):\\n self.assertEqual(self.Pcount, 7)\",\n \"def test_counter_start_at_zero(self):\\n pass\",\n \"def test_count_1719(self):\\n value: int = 2645\\n result: int = 1113\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_simulator_0_shots():\\n dev = _aws_device(wires=2, device_type=AwsDeviceType.SIMULATOR, shots=0)\\n assert dev.shots == 1\\n assert dev.analytic\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_count_173(self):\\n value: int = 173\\n result: int = 55\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_361_077(self):\\n value: int = 361_077\\n result: int = 188_065\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_counter(self):\\n self.assertEqual(self._n_registered, 1)\",\n \"def test_snc_closed_segment(grid):\\n space = bempp.api.function_space(\\n grid, \\\"SNC\\\", 0, segments=[1], include_boundary_dofs=True\\n )\\n\\n for elem_index in range(grid.number_of_elements):\\n if space.support[elem_index]:\\n assert _np.all(space.local_multipliers[elem_index] != 0)\\n else:\\n assert _np.all(space.local_multipliers[elem_index] == 0)\",\n \"def test_count_ways_null():\\n assert f.count_ways(0) == 1\",\n \"def test_count_2645(self):\\n value: int = 1719\\n result: int = 723\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_returns_zero_for_empty_grid(self):\\n grid = []\\n result = num_islands(grid)\\n self.assertEqual(result, 0)\",\n \"def test_own_count(self):\\n self._test_count_func(it_count)\",\n \"def test_count_roll_fail():\\n expected = np.array([3, 0, 1, 5, 0, 0])\\n result = analyze_roll.count_roll(np.array([1, 1, 3, 1, 4, 4]))\\n assert np.array_equal(expected, result) is False\",\n \"def test_count_increments():\\n\\n # Signals and interface etc.\\n clk = Clock()\\n reset = Reset(async=True)\\n count = Signal(intbv()[8:])\\n\\n def _bench():\\n dut = Cosimulation('vvp -m ./myhdl.vpi ./bin/example_module/example_module', \\n clk=clk, \\n reset=reset,\\n count=count)\\n\\n @instance\\n def stimulus():\\n yield delay(255 * 2 + 4)\\n print(count)\\n assert count == 0xff\\n raise StopSimulation\\n\\n return dut, clk.gen(), reset.pulse(), stimulus\\n\\n # = traceSignals(_bench)\\n Simulation(_bench()).run()\",\n \"def calc_score(pins_stats):\\n count = 0\\n new = pins_stats[:, :2] - ORIG_PINS_LOC\\n for p in new:\\n if np.linalg.norm(p) > R_PIN / 2:\\n count += 1\\n return count\",\n \"def NumberOfEmptySpots(self):\\n\\n return np.count_nonzero(self.state == EMPTY)\",\n \"def test_count_459(self):\\n value: int = 459\\n result: int = 148\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def countObjects(inputImb, inputIma):\\n\\n lb = label(inputImb)\\n obefore = len(regionprops(lb))\\n lbc = label(1 - inputImb, connectivity=1)\\n ocbefore = len(regionprops(lbc))\\n la = label(inputIma)\\n oafter = len(regionprops(la))\\n lac = label(1 - inputIma, connectivity=1)\\n ocafter = len(regionprops(lac))\\n\\n if obefore == oafter and ocbefore == ocafter:\\n deletableTemp = 1\\n else:\\n deletableTemp = 0\\n\\n return deletableTemp\",\n \"def test_sinc_list():\\n x,sc = cw04.gen_sinc_list(-1,1,3)\\n desired = [0.8414709848078965, 1.0 , 0.8414709848078965]\\n print(\\\"Obtained:\\\",sc)\\n print(\\\"Desired:\\\",desired)\\n # For comparing floating point values, nose has useful helper functions\\n # to ensure they are equal up to a numerical precision tolerance\\n nose.tools.assert_almost_equal(sc, desired)\",\n \"def test_solvation_potassium_control(self):\\n waters = np.random.randint(1000, 10000)\\n log.debug('Trying {} waters with potassium...'.format(waters))\\n solvate(tleapfile='./cb6-but/tleap.in', pdbfile='cb6-but.pdb',\\n bufferwater=waters, counter_cation='K+')\\n potassium = sp.check_output([\\\"grep -oh 'K+' ./cb6-but/solvated.prmtop | wc -w\\\"],\\n shell=True)\\n self.assertEqual(int(potassium), 0)\",\n \"def test_count_ways_positive(inputs, outputs):\\n assert f.count_ways(inputs) == outputs\",\n \"def getNumRings(self, nPins, silent=False):\\n nRings = hexagon.numRingsToHoldNumCells(nPins)\\n if not silent:\\n nPinsFullRings = self.getNumPositions(rings=nRings)\\n if nPins != nPinsFullRings:\\n runLog.warning(\\n \\\"{0} does not fit exactly into a hex grid of any number of rings. \\\"\\n \\\"Rounding up to {1} rings which can hold {2} pins)\\\"\\n \\\"\\\".format(nPins, nRings, nPinsFullRings),\\n single=True,\\n label=\\\"Non-exact number of positions in hex lattice\\\",\\n )\\n return nRings\",\n \"def testCounting(self):\\n \\n clk = Signal(0)\\n clock_gen = ClkDriver(clk, period=4)\\n \\n for i in range(1, 6):\\n #print \\\"Testing\\\", i, \\\"bits\\\"\\n out = Signal(intbv(0)[i:])\\n prev_out = Signal(intbv(2**i - 1)[i:])\\n counter = Counter(out, clk, Signal(1))\\n \\n # make sure it increments and wraps at modulo 2^n\\n @always(clk.posedge)\\n def test():\\n #print out, prev_out\\n self.assertEqual(int(out), int((prev_out + 1) % 2**(len(prev_out))))\\n prev_out.next = out\\n \\n sim = Simulation(counter, clock_gen, test)\\n sim.run(12 * 2**i, quiet=1)\",\n \"def test_count_9(self):\\n value: int = 9\\n result: int = 2\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_shared_cards_are_zero(self):\\n self.assertEqual(len(self.hand.sharedCards), 0)\",\n \"def get_zero_nonzero_idx(spins):\\n idx_zero = spins.index(0)\\n idx_nonzero = tuple([idx for idx, spin in enumerate(spins) if spin != 0])\\n if len(idx_nonzero) + 1 != len(spins):\\n raise ValueError(\\\"`spins` must contain exactly one zero.\\\")\\n return idx_zero, idx_nonzero\",\n \"def test_svm_count():\\n assert environments.svms() > 0\\n count = 0\\n for l in list(environments.data):\\n e = environments[l]\\n count += e.svms\\n msg = ('SVM count mismatch. Environments says: ' +\\n str(environments.svms()) +\\n ', actual count: ' + str(count))\\n assert count == environments.svms(), msg\",\n \"def test_count_10(self):\\n value: int = 10\\n result: int = 2\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_count_35(self):\\n value: int = 35\\n result: int = 6\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_361_087(self):\\n value: int = 361_087\\n result: int = 188_067\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_361_000(self):\\n value: int = 361_000\\n result: int = 187_995\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def testSectionCount(self):\\n\\n self.sectionCount(3640)\",\n \"def test_count_361_070(self):\\n value: int = 361_070\\n result: int = 188_058\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_reads_in_region_total(self):\\n self.c.skipZeros = False\\n self.c.stepSize = 200\\n self.c.binLength = 200\\n resp, _ = self.c.count_reads_in_region(self.chrom, 0, 200)\\n nt.assert_equal(resp, np.array([[2, 4.]]))\",\n \"def test_negative_electrode_potential_profile(self):\\n np.testing.assert_array_almost_equal(self.phi_s_n(self.t, x=0), 0, decimal=5)\",\n \"def count_single_spikes_and_bursts(info):\\r\\n\\r\\n singles = 0\\r\\n bursts = 0\\r\\n inBurst = False\\r\\n\\r\\n spikesperbursts = []\\r\\n spb = 2\\r\\n\\r\\n prev_start = -1000\\r\\n prev_end = -1000\\r\\n for spike in info:\\r\\n if spike[0] - prev_end > 80:\\r\\n #print('single:', spike[0])\\r\\n singles += 1\\r\\n if inBurst:\\r\\n spikesperbursts.append(spb)\\r\\n inBurst = False\\r\\n else:\\r\\n #print('burst:',inBurst, spike[0])\\r\\n if not inBurst:\\r\\n spb = 2\\r\\n singles -=1\\r\\n bursts += 1\\r\\n else:\\r\\n spb += 1\\r\\n inBurst = True\\r\\n prev_start = spike[0]\\r\\n prev_end = spike[1]\\r\\n return singles, bursts, spikesperbursts, sum(spikesperbursts)/len(spikesperbursts)\",\n \"def test_getSampleCount(self):\\r\\n self.assertEqual(self.res1.getSampleCount(), 0)\\r\\n\\r\\n self.res1.addSample('S1', 42)\\r\\n self.assertEqual(self.res1.getSampleCount(), 1)\\r\\n\\r\\n self.res1.addSample('S2', 43)\\r\\n self.assertEqual(self.res1.getSampleCount(), 2)\",\n \"def test_count_66(self):\\n value: int = 66\\n result: int = 18\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def count():\",\n \"def test_count_880_000(self):\\n value: int = 880_000\\n result: int = 472_910\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def _is_valid_count(self, count: int, gp: GriddedPerm) -> bool:\\n return self._point_in_fuse_region(gp) + 1 == count\",\n \"def runcount(test_keys, sigma, sigma_max, sigma_step,\\n npoints_min, npoints_max, npoints_step):\\n run = 1\\n for key in test_keys:\\n if key:\\n while sigma < sigma_max:\\n npoints = npoints_min\\n while npoints < npoints_max:\\n npoints += npoints_step\\n run += 1\\n sigma += sigma_step\\n return run\",\n \"def test_count(self):\\n self._test_count_func(count)\",\n \"def sight_resight_count(nvisit1, nvisit2, resight):\\n import math\\n\\n try:\\n nvisit1 = float(nvisit1)\\n nvisit2 = float(nvisit2)\\n resight = float(resight)\\n pl_index = int(math.ceil((nvisit1 * nvisit2) / resight))\\n pl_error_num = float((nvisit1 ** 2) * nvisit2 * (nvisit2 - resight))\\n pl_error_dom = float(resight ** 3)\\n pl_error = int(math.ceil(1.96 * math.sqrt(pl_error_num / pl_error_dom)))\\n except ZeroDivisionError:\\n # pl_index = 'Undefined - Zero recaptured (k = 0)'\\n pl_index = 0\\n pl_error = 0\\n return pl_index, pl_error\",\n \"def test_count_72(self):\\n value: int = 72\\n result: int = 21\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_amount_of_listings_no_listings(self):\\n listings = steam_market.get_total_amount_of_listings(soup=get_soup_from_path(TEST_FILE_NO_RESULTS))\\n self.assertEqual(0, listings)\",\n \"def run_null(parcellation, scale, spintype):\\n\\n nsdata = load_data(parcellation, scale)\\n\\n # run the damn thing\\n print(f'Running {spintype:>9} spins for {scale}: ', end='', flush=True)\\n out = NSDIR / parcellation / 'nulls' / spintype / f'{scale}_nulls.csv'\\n if out.exists():\\n permcorrs = np.loadtxt(out).reshape(-1, 1)\\n elif spintype == 'cornblath':\\n # even though we're working with parcellated data we need to project\\n # that to the surface + spin the vertices, so let's load our\\n # pre-generated vertex-level spins\\n spins = SPDIR / 'vertex' / 'vazquez-rodriguez' / 'fsaverage5_spins.csv'\\n\\n # get annotation files\\n fetcher = getattr(nndata, f\\\"fetch_{parcellation.replace('atl-', '')}\\\")\\n annotations = fetcher('fsaverage5', data_dir=ROIDIR)[scale]\\n\\n # pre-load the spins for this function (assumes `spins` is array)\\n # permdata will be an (R, T, n_rotate) array\\n print('Pre-loading spins...', end='\\\\b' * 20, flush=True)\\n spins = np.loadtxt(spins, delimiter=',', dtype='int32')\\n permdata = nnsurf.spin_data(nsdata, version='fsaverage5',\\n lhannot=annotations.lh,\\n rhannot=annotations.rh,\\n spins=spins, n_rotate=spins.shape[-1],\\n verbose=True)\\n permcorrs = np.vstack([\\n _get_permcorr(nsdata, permdata[..., n])\\n for n in range(permdata.shape[-1])\\n ])\\n putils.save_dir(out, permcorrs)\\n elif spintype in ['burt2018', 'burt2020']:\\n surrdir = SURRDIR / parcellation / spintype / 'neurosynth'\\n # generate the permuted data from the surrogate resampling arrays\\n print('Generating surrogates...', end='\\\\b' * 24, flush=True)\\n permdata = get_surrogates(nsdata, surrdir, scale)\\n permcorrs = np.vstack([\\n _get_permcorr(nsdata, permdata[..., n])\\n for n in range(permdata.shape[-1])\\n ])\\n putils.save_dir(out, permcorrs)\\n elif spintype == 'moran':\\n surrogates = np.zeros((*nsdata.shape, 10000))\\n for hemi, dist, idx in putils.yield_data_dist(DISTDIR, parcellation,\\n scale, nsdata):\\n mrs = moran.MoranRandomization(joint=True, n_rep=10000,\\n tol=1e-6, random_state=1234)\\n mrs.fit(dist)\\n surrogates[idx] = mrs.randomize(hemi).transpose(1, 2, 0)\\n\\n permcorrs = np.vstack([\\n _get_permcorr(nsdata, surrogates[..., n])\\n for n in range(surrogates.shape[-1])\\n ])\\n putils.save_dir(out, permcorrs)\\n else:\\n spins = SPDIR / parcellation / spintype / f'{scale}_spins.csv'\\n permcorrs = gen_permcorrs(nsdata, spins, out)\\n\\n nsdata = nsdata.dropna(axis=0, how='all')\\n pvals = get_fwe(np.corrcoef(nsdata.T), permcorrs)\\n\\n out = pd.DataFrame(dict(\\n parcellation=parcellation,\\n scale=scale,\\n spintype=spintype,\\n n_sig=np.sum(np.triu(pvals < ALPHA, k=1))\\n ), index=[0])\\n\\n return out\",\n \"def test_qpu_0_shots():\\n _aws_device(wires=2, shots=0)\",\n \"def get_nrof_pumps(self):\\n pumps = 0\\n for p in self.pump_array:\\n if p:\\n pumps += 1\\n return pumps\",\n \"def test_count_20(self):\\n value: int = 20\\n result: int = 4\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_800_000(self):\\n value: int = 800_000\\n result: int = 426_983\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_roll():\\n expected = np.array([3, 0, 1, 2, 0, 0])\\n result = analyze_roll.count_roll(np.array([1, 1, 3, 1, 4, 4]))\\n assert np.array_equal(expected, result) is True\",\n \"def test_count_7000(self):\\n value: int = 7000\\n result: int = 3333\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_770(self):\\n value: int = 770\\n result: int = 306\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def count_standard_residues(self):\\n n = 0\\n for na in self.iter_standard_residues():\\n n += 1\\n return n\",\n \"def test_withCountIntervalZero(self):\\n clock = task.Clock()\\n accumulator = []\\n\\n def foo(cnt):\\n accumulator.append(cnt)\\n if len(accumulator) > 4:\\n loop.stop()\\n\\n loop = task.LoopingCall.withCount(foo)\\n loop.clock = clock\\n deferred = loop.start(0, now=False)\\n\\n clock.advance(0)\\n self.successResultOf(deferred)\\n\\n self.assertEqual([1, 1, 1, 1, 1], accumulator)\",\n \"def count() -> int:\\n pass\",\n \"def test_count_883_904(self):\\n value: int = 883_904\\n result: int = 475_749\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_666(self):\\n value: int = 666\\n result: int = 264\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_6_645_243(self):\\n value: int = 6_645_243\\n result: int = 3_615_948\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_count_5(self):\\n value: int = 5\\n result: int = 0\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"async def test_txn_list_with_zero_count(self):\\n response = await self.get_assert_status('/transactions?count=0', 400)\\n\\n self.assert_has_valid_error(response, 53)\",\n \"def count_benchmarks():\\n return len(setup_storage().fetch_benchmark({}))\",\n \"def Count():\\n return CheckForError(lib.Generators_Get_Count())\",\n \"def _success_count(cls, samples: Samples) -> int:\\n return cls.__sample_count(samples, \\\"true\\\")\",\n \"def test_count_700_000(self):\\n value: int = 700_000\\n result: int = 374_421\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_song_counts(self):\\n self.assertEqual(self.show.total_song_count, None)\",\n \"def test_vm_count():\\n assert templates.vm_count() > 0\",\n \"def test_measure(self):\\n\\n result = qubit.measure(polarization)\\n self.assertEqual(0, result)\",\n \"def monte_carlo_trials(nb_trials, nb_ok, lock):\\n\\n # First perform the trials\\n # Do not use shared resource because other processes doesn't need to know\\n # about computation step\\n nb_in_quarter_results = 0\\n for i in range(nb_trials):\\n x = random.uniform(0, 1)\\n y = random.uniform(0, 1)\\n if x * x + y * y <= 1.0:\\n nb_in_quarter_results += 1\\n\\n # Finally update shared resource\\n # Do it only once, then processes doesn't struggle with each other to\\n # update it\\n with lock:\\n nb_ok.value += nb_in_quarter_results\",\n \"def test_count_reads_per_cluster(self):\\n \\n bedtool = pybedtools.BedTool(clipper.test_file(\\\"clip_analysis_test_peak_results.bed\\\"))\\n \\n total_reads, reads_per_cluster = count_reads_per_cluster(bedtool, None)\\n \\n self.assertListEqual([147,52, 239, 85, 47, 119, 58, 588, 92, 59, 196, 36], reads_per_cluster)\\n self.assertEqual(sum([147,52, 239, 85, 47, 119, 58, 588, 92, 59, 196, 36]), total_reads)\",\n \"def test_total_procs():\\n result = _run_metric('total_procs')\\n assert result.exit_code == 0\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.8364899","0.80283797","0.63442856","0.609039","0.6043598","0.6036848","0.6035397","0.5966873","0.58482337","0.58064646","0.57407767","0.56835514","0.56486934","0.563143","0.5597956","0.55912817","0.55141515","0.546807","0.54593736","0.5443237","0.54408234","0.54126966","0.5412613","0.5386389","0.5380152","0.53402996","0.5321691","0.53123707","0.53089154","0.5301288","0.53005767","0.5298365","0.52921015","0.5288457","0.5279972","0.52794653","0.52727294","0.5268899","0.5264794","0.52482486","0.5245055","0.52439994","0.5234967","0.52269846","0.52262163","0.52252793","0.5220203","0.520297","0.5192593","0.5188092","0.51877934","0.51866496","0.5181811","0.5181595","0.5180903","0.5178887","0.51752895","0.5174474","0.51744586","0.517314","0.517304","0.5159788","0.51391137","0.51359296","0.5116057","0.5107787","0.5106652","0.50962144","0.5094826","0.509186","0.50906384","0.50892645","0.50884736","0.50846446","0.50795764","0.50773036","0.5077083","0.50759137","0.50734377","0.50724214","0.50650287","0.5046272","0.50430626","0.5039967","0.5027117","0.50241345","0.5022899","0.50209737","0.50080097","0.5005456","0.5005403","0.500292","0.49974865","0.49777794","0.49747956","0.49690458","0.49631298","0.49588457","0.49563485","0.49530622"],"string":"[\n \"0.8364899\",\n \"0.80283797\",\n \"0.63442856\",\n \"0.609039\",\n \"0.6043598\",\n \"0.6036848\",\n \"0.6035397\",\n \"0.5966873\",\n \"0.58482337\",\n \"0.58064646\",\n \"0.57407767\",\n \"0.56835514\",\n \"0.56486934\",\n \"0.563143\",\n \"0.5597956\",\n \"0.55912817\",\n \"0.55141515\",\n \"0.546807\",\n \"0.54593736\",\n \"0.5443237\",\n \"0.54408234\",\n \"0.54126966\",\n \"0.5412613\",\n \"0.5386389\",\n \"0.5380152\",\n \"0.53402996\",\n \"0.5321691\",\n \"0.53123707\",\n \"0.53089154\",\n \"0.5301288\",\n \"0.53005767\",\n \"0.5298365\",\n \"0.52921015\",\n \"0.5288457\",\n \"0.5279972\",\n \"0.52794653\",\n \"0.52727294\",\n \"0.5268899\",\n \"0.5264794\",\n \"0.52482486\",\n \"0.5245055\",\n \"0.52439994\",\n \"0.5234967\",\n \"0.52269846\",\n \"0.52262163\",\n \"0.52252793\",\n \"0.5220203\",\n \"0.520297\",\n \"0.5192593\",\n \"0.5188092\",\n \"0.51877934\",\n \"0.51866496\",\n \"0.5181811\",\n \"0.5181595\",\n \"0.5180903\",\n \"0.5178887\",\n \"0.51752895\",\n \"0.5174474\",\n \"0.51744586\",\n \"0.517314\",\n \"0.517304\",\n \"0.5159788\",\n \"0.51391137\",\n \"0.51359296\",\n \"0.5116057\",\n \"0.5107787\",\n \"0.5106652\",\n \"0.50962144\",\n \"0.5094826\",\n \"0.509186\",\n \"0.50906384\",\n \"0.50892645\",\n \"0.50884736\",\n \"0.50846446\",\n \"0.50795764\",\n \"0.50773036\",\n \"0.5077083\",\n \"0.50759137\",\n \"0.50734377\",\n \"0.50724214\",\n \"0.50650287\",\n \"0.5046272\",\n \"0.50430626\",\n \"0.5039967\",\n \"0.5027117\",\n \"0.50241345\",\n \"0.5022899\",\n \"0.50209737\",\n \"0.50080097\",\n \"0.5005456\",\n \"0.5005403\",\n \"0.500292\",\n \"0.49974865\",\n \"0.49777794\",\n \"0.49747956\",\n \"0.49690458\",\n \"0.49631298\",\n \"0.49588457\",\n \"0.49563485\",\n \"0.49530622\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.846338"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81473,"cells":{"query":{"kind":"string","value":"Test that the counting of the number of spins raises an error when no pipe exists. The function tested is pipe_control.mol_res_spin.count_spins()."},"document":{"kind":"string","value":"def test_count_spins_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Test for the error.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.count_spins)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_count_no_spins(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 0)","def test_count_spins(self):\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 4)\n self.assertEqual(mol_res_spin.count_spins(skip_desel=False), 8)\n self.assertEqual(mol_res_spin.count_spins(selection='@N5'), 1)\n self.assertEqual(mol_res_spin.count_spins(selection='@N5', skip_desel=False), 2)","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_return_spin_pipe_fail(self):\n\n # Try to get a spin from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_spin_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for spin in mol_res_spin.spin_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_svm_count():\n assert templates.svms() > 0","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def test_count_resources(ops_and_shots, expected_resources):\n ops, shots = ops_and_shots\n computed_resources = _count_resources(QuantumScript(ops=ops, shots=shots))\n assert computed_resources == expected_resources","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def Count():\n return CheckForError(lib.Generators_Get_Count())","def test_svm_vs_vm_count():\n assert templates.svms() >= templates.vm_count()","def test_get_counturingErr(self):\n for app_num, servo_type in app_nr.items():\n try:\n par = self.get_parameter(servo_type, app_num, COUNTURING_ERR_IDX, COUNTURING_ERR_SUB)\n param_obj = self.__dict__[servo_type]._get_counturingErr()\n acs_par, completion = param_obj.get_sync()\n if(completion.code):\n print \"\\nError code found in counturingErr...\"\n continue\n self.data_match(acs_par, par)\n except NackEx:\n continue","def _get_slr_count(slot_list: List[Slot]) -> int:\n slr_count_list = [slot.board.SLR_NUM for slot in slot_list]\n assert all(slr_count_list[i] == slr_count_list[0] for i in range(len(slr_count_list)))\n return slr_count_list[0]","def test_total_procs():\n result = _run_metric('total_procs')\n assert result.exit_code == 0","def test_svm_vs_vm_count():\n assert environments.svms() >= environments.vm_count()","def test_pressure_count(self):\n self.assertEqual(self.Pcount, 7)","def test_residue_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for residue in mol_res_spin.residue_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_count_ways_null():\n assert f.count_ways(0) == 1","def testPipeFound(self):\n safeFoundHelper(self)\n self.assertCurrentState(safe.Seeking)","def test_count_0(self):\n self.assertEqual(count(0), 0, 'Between 0 and 0, there is 0 lucky numbers.')","def test_vm_count():\n assert templates.vm_count() > 0","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def getNumRings(self, nPins, silent=False):\n numPositions = 0\n for nRings in itertools.count(0):\n numPositions += self.getNumPosInRing(nRings)\n if not silent and numPositions > nPins:\n runLog.warning(\n \"{0} does not fit exactly into a cartisian grid of any number of rings. \"\n \"Rounding up to {1} rings which can hold {2} pins)\"\n \"\".format(nPins, nRings, numPositions),\n single=True,\n label=\"Non-exact number of positions in cartesian lattice\",\n )\n if numPositions >= nPins:\n return nRings","def test_molecule_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for molecule in mol_res_spin.molecule_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def nspins(self):\n return len(self)","def test_spin_loop(self):\n\n # Spin data.\n select = [1, 0]\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, 'N5')\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 2)","def _n_spin_states(self) -> int:\n if self.spin is None:\n raise Exception(\n \"cannot request number of spin states for spinless fermions\"\n )\n return round(2 * self.spin + 1)","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_return_residue_pipe_fail(self):\n\n # Try to get a residue from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')","def test_return_molecule_pipe_fail(self):\n\n # Try to get a molecule from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')","def test_amount_of_listings_no_listings(self):\n listings = steam_market.get_total_amount_of_listings(soup=get_soup_from_path(TEST_FILE_NO_RESULTS))\n self.assertEqual(0, listings)","def test_svm_count():\n assert environments.svms() > 0\n count = 0\n for l in list(environments.data):\n e = environments[l]\n count += e.svms\n msg = ('SVM count mismatch. Environments says: ' +\n str(environments.svms()) +\n ', actual count: ' + str(count))\n assert count == environments.svms(), msg","def test_solvation_potassium_control(self):\n waters = np.random.randint(1000, 10000)\n log.debug('Trying {} waters with potassium...'.format(waters))\n solvate(tleapfile='./cb6-but/tleap.in', pdbfile='cb6-but.pdb',\n bufferwater=waters, counter_cation='K+')\n potassium = sp.check_output([\"grep -oh 'K+' ./cb6-but/solvated.prmtop | wc -w\"],\n shell=True)\n self.assertEqual(int(potassium), 0)","def test_spin_loop_no_selection(self):\n\n # Spin data.\n select = [0, 1, 0, 0, 1, 1, 0, 1]\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 8)","def test_data_source_soaps_count_get(self):\n pass","def test_test(self):\n\n # The following should do nothing as the pipes exist.\n pipes.check_pipe()\n pipes.check_pipe('orig')\n pipes.check_pipe('empty')\n\n # Assert that a RelaxNoPipeError occurs when the pipe doesn't exist.\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe, 'x')\n\n # Reset relax.\n reset()\n\n # Now none of the following pipes exist, hence errors should be thrown.\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe)\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe, 'orig')\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe, 'empty')","def get_spitfp_error_count(self):\n return GetSPITFPErrorCount(*self.ipcon.send_request(self, BrickletBarometerV2.FUNCTION_GET_SPITFP_ERROR_COUNT, (), '', 'I I I I'))","def test_count(self):\n self._test_count_func(count)","def Test_NumSegments(Daten):\n N_Leitungen = len(Daten.PipeSegments)\n\n return N_Leitungen","def test_own_count(self):\n self._test_count_func(it_count)","def test_count_roll_fail():\n expected = np.array([3, 0, 1, 5, 0, 0])\n result = analyze_roll.count_roll(np.array([1, 1, 3, 1, 4, 4]))\n assert np.array_equal(expected, result) is False","def test_count_when_data_is_not_present(self):\n\n temp_data = []\n\n tt = TemperatureTracker()\n result = tt.count_from(temp_data)\n self.assertEqual(result, 0)","def test_vm_count():\n assert environments.vm_count() > 0, 'Total VM count should be over 1.'\n count = 0\n for l in list(environments.data):\n e = environments[l]\n count += e.vm_count\n msg = ('VM count mismatch. Environments says: ' +\n str(environments.vm_count()) +\n ', actual count: ' + str(count))\n assert count == environments.vm_count(), msg","def test_empty_system_error():\n system = vermouth.system.System()\n sequence = \"not empty\"\n processor = dssp.AnnotateResidues(\"test\", sequence)\n with pytest.raises(ValueError):\n processor.run_system(system)","def test_count_ways_wrong_value_raise(inputs, outputs):\n with pytest.raises(outputs):\n f.count_ways(inputs)","def test_count_ways_positive(inputs, outputs):\n assert f.count_ways(inputs) == outputs","def test_count_10(self):\n value: int = 10\n result: int = 2\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","async def test_txn_list_with_zero_count(self):\n response = await self.get_assert_status('/transactions?count=0', 400)\n\n self.assert_has_valid_error(response, 53)","def count() -> int:\n pass","def count():","def get_spitfp_error_count(self):\n self.check_validity()\n\n return GetSPITFPErrorCount(*self.ipcon.send_request(self, BrickletIndustrialDualAnalogInV2.FUNCTION_GET_SPITFP_ERROR_COUNT, (), '', 24, 'I I I I'))","def test_returns_zero_for_empty_grid(self):\n grid = []\n result = num_islands(grid)\n self.assertEqual(result, 0)","def test_getSampleCount(self):\r\n self.assertEqual(self.res1.getSampleCount(), 0)\r\n\r\n self.res1.addSample('S1', 42)\r\n self.assertEqual(self.res1.getSampleCount(), 1)\r\n\r\n self.res1.addSample('S2', 43)\r\n self.assertEqual(self.res1.getSampleCount(), 2)","def getnumbarablocktriplets(self): # 3\n res,resargs = self.__obj.getnumbarablocktriplets()\n if res != 0:\n result,msg = self.__getlasterror(res)\n raise Error(rescode(res),msg)\n _num_return_value = resargs\n return _num_return_value","def test_get_resource_license_resource_count_list(self):\n pass","def test_count_9(self):\n value: int = 9\n result: int = 2\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def getNumRings(self, nPins, silent=False):\n nRings = hexagon.numRingsToHoldNumCells(nPins)\n if not silent:\n nPinsFullRings = self.getNumPositions(rings=nRings)\n if nPins != nPinsFullRings:\n runLog.warning(\n \"{0} does not fit exactly into a hex grid of any number of rings. \"\n \"Rounding up to {1} rings which can hold {2} pins)\"\n \"\".format(nPins, nRings, nPinsFullRings),\n single=True,\n label=\"Non-exact number of positions in hex lattice\",\n )\n return nRings","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_counter(self):\n self.assertEqual(self._n_registered, 1)","def test_count_173(self):\n value: int = 173\n result: int = 55\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_simulator_0_shots():\n dev = _aws_device(wires=2, device_type=AwsDeviceType.SIMULATOR, shots=0)\n assert dev.shots == 1\n assert dev.analytic","def spine_switch_count(self):\n spines = GetSwitchDetails().get_spine_switch_ip()\n totalSpines = len(spines)\n return totalSpines","def test_count_increments():\n\n # Signals and interface etc.\n clk = Clock()\n reset = Reset(async=True)\n count = Signal(intbv()[8:])\n\n def _bench():\n dut = Cosimulation('vvp -m ./myhdl.vpi ./bin/example_module/example_module', \n clk=clk, \n reset=reset,\n count=count)\n\n @instance\n def stimulus():\n yield delay(255 * 2 + 4)\n print(count)\n assert count == 0xff\n raise StopSimulation\n\n return dut, clk.gen(), reset.pulse(), stimulus\n\n # = traceSignals(_bench)\n Simulation(_bench()).run()","def test_count_35(self):\n value: int = 35\n result: int = 6\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_invoke_pipe_not_found():\n\n testapp = holocron.Application()\n\n with pytest.raises(ValueError) as excinfo:\n next(testapp.invoke(\"test\"))\n\n assert str(excinfo.value) == \"no such pipe: 'test'\"","def test_getSampleCount(self):\r\n self.assertEqual(self.estimator1.getSampleCount(), 1)","def test_specific_qubit_pauli_error_gate_100percent(self):\n qr = QuantumRegister(2, 'qr')\n cr = ClassicalRegister(2, 'cr')\n circuit = QuantumCircuit(qr, cr)\n circuit.iden(qr)\n circuit.barrier(qr)\n circuit.measure(qr, cr)\n backend = QasmSimulator()\n shots = 100\n # test noise model\n error = pauli_error([('X', 1)])\n noise_model = NoiseModel()\n noise_model.add_quantum_error(error, 'id', [1])\n # Execute\n target = {'0x2': shots}\n circuit = transpile(circuit, basis_gates=noise_model.basis_gates)\n qobj = assemble([circuit], backend, shots=shots)\n result = backend.run(qobj, noise_model=noise_model).result()\n self.is_completed(result)\n self.compare_counts(result, [circuit], [target], delta=0)","def test_getReferenceIndividualCount(self):\r\n with self.assertRaises(ValueError):\r\n self.res1.getReferenceIndividualCount('S1')\r\n\r\n self.res1.addSample('S1', 42)\r\n self.assertEqual(self.res1.getReferenceIndividualCount('S1'), 42)","def test_count_459(self):\n value: int = 459\n result: int = 148\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_get_spawning_profile_list():\n center = Coordinates(1 , 1)\n radius = 10\n speed_limit = 20\n default_driver = DriverProfile(\"Default\", 8, 2, 2, 0, 30, 3, 1)\n default_vehicle = VehicleProfile(\"Default\", 5, 15, 2, 2, 1000, 65)\n default_spawn = SpawningProfile(\"Default\", default_driver, default_vehicle)\n\n i = Intersection(center, radius, speed_limit)\n\n l = i.get_spawning_profile_list()\n\n assert not l\n\n i.add_spawning_profile(default_spawn)\n\n assert l\n\n assert len(l) == 1\n\n i.remove_spawning_profile(default_spawn)\n\n assert len(l) == 0\n assert not l","def test_song_counts(self):\n self.assertEqual(self.show.total_song_count, None)","def get_nrof_pumps(self):\n pumps = 0\n for p in self.pump_array:\n if p:\n pumps += 1\n return pumps","def testSectionCount(self):\n\n self.sectionCount(3640)","def test_all_qubit_pauli_error_gate_100percent(self):\n qr = QuantumRegister(2, 'qr')\n cr = ClassicalRegister(2, 'cr')\n circuit = QuantumCircuit(qr, cr)\n circuit.iden(qr)\n circuit.barrier(qr)\n circuit.measure(qr, cr)\n backend = QasmSimulator()\n shots = 100\n # test noise model\n error = pauli_error([('X', 1)])\n noise_model = NoiseModel()\n noise_model.add_all_qubit_quantum_error(error, 'id')\n # Execute\n target = {'0x3': shots}\n circuit = transpile(circuit, basis_gates=noise_model.basis_gates)\n qobj = assemble([circuit], backend, shots=shots)\n result = backend.run(qobj, noise_model=noise_model).result()\n self.is_completed(result)\n self.compare_counts(result, [circuit], [target], delta=0)","def _error_count(cls, samples: Samples) -> int:\n return cls.__sample_count(samples, \"false\")","def test_retry_count_query():\n error_list = [OperationalError, OperationalError, OperationalError, SystemError, RuntimeError]\n with mock.patch(\"snowshu.adapters.source_adapters.SnowflakeAdapter._count_query\", side_effect=error_list):\n sf = SnowflakeAdapter()\n with pytest.raises(SystemError) as exc:\n sf.check_count_and_query(\"select * from unknown_table\", 10, False)\n \n # assert that the 4th error was raised\n assert exc.errisinstance(SystemError)\n assert sf.check_count_and_query.retry.statistics[\"attempt_number\"] == 4","def test_count_reads_per_cluster(self):\n \n bedtool = pybedtools.BedTool(clipper.test_file(\"clip_analysis_test_peak_results.bed\"))\n \n total_reads, reads_per_cluster = count_reads_per_cluster(bedtool, None)\n \n self.assertListEqual([147,52, 239, 85, 47, 119, 58, 588, 92, 59, 196, 36], reads_per_cluster)\n self.assertEqual(sum([147,52, 239, 85, 47, 119, 58, 588, 92, 59, 196, 36]), total_reads)","def test_step_count(self):\n inp = [(0, 0), (1, 1), (1, 2)]\n expected = 2\n actual = get_num_steps(inp)\n self.assertEqual(expected, actual)","def test_count_1719(self):\n value: int = 2645\n result: int = 1113\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def __init__(self, pins_nbr=10, throws_nbr=2, throws=None):\n self.pins_nbr = pins_nbr\n self.throws_nbr = throws_nbr\n\n if throws is None:\n self.throws = []\n else:\n self.throws = throws\n if len(self.throws):\n self.sanity_check() # runs sanity_check\n assert self.complete() # assert completeness","def test_error_num_entries(self, state_vector, wires):\n\n with pytest.raises(ValueError, match=\"'state_vector' must be of shape\"):\n MottonenStatePreparation(state_vector, wires)","def test_mount_status_nas_share_by_pool(self):\n pass","def test_specific_qubit_pauli_error_gate_25percent(self):\n qr = QuantumRegister(2, 'qr')\n cr = ClassicalRegister(2, 'cr')\n circuit = QuantumCircuit(qr, cr)\n circuit.iden(qr)\n circuit.barrier(qr)\n circuit.measure(qr, cr)\n backend = QasmSimulator()\n shots = 2000\n # test noise model\n error = pauli_error([('X', 0.25), ('I', 0.75)])\n noise_model = NoiseModel()\n noise_model.add_quantum_error(error, 'id', [0])\n # Execute\n target = {'0x0': 3 * shots / 4, '0x1': shots / 4}\n circuit = transpile(circuit, basis_gates=noise_model.basis_gates)\n qobj = assemble([circuit], backend, shots=shots)\n result = backend.run(qobj, noise_model=noise_model).result()\n self.is_completed(result)\n self.compare_counts(result, [circuit], [target], delta=0.05 * shots)","def test_get_resource_license_resource_count_by_moid(self):\n pass","def test_count_2645(self):\n value: int = 1719\n result: int = 723\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')","def test_results_length(spheroid_convex_fixture):\n assert(len(spheroid_convex_fixture.pairs) == 1000)\n assert(len(spheroid_convex_fixture.combinations) == 1000)\n assert(len(spheroid_convex_fixture.deltas) == 1000)","def test_count_bad(self):\n with self.assertRaises(KeyError):\n models.storage.count(\"2\")","def test_bababc():\n assert part_01.count_for('bababc', 2) == 1\n assert part_01.count_for('bababc', 3) == 1","def test_cell_list_limit_0_success(self, mock_list):\n self.shell('cell-list -r 1 --limit 0')\n mock_list.assert_called_once_with(limit=0)","def test_triangle_count_04(self):\n body = {\"direction\": \"OUT\"}\n code, res = Algorithm().post_triangle_count(body, auth=auth)\n id = res[\"task_id\"]\n if id > 0:\n result = get_task_res(id, 120, auth=auth)\n print(result)\n assert result == {'edges_out': 13, 'vertices_out': 7, 'triangles': 2}\n else:\n assert 0","def test_cell_list_limit_positive_num_success(self, mock_list):\n self.shell('cell-list -r 1 --limit 1')\n mock_list.assert_called_once_with(limit=1)","def countObjects(inputImb, inputIma):\n\n lb = label(inputImb)\n obefore = len(regionprops(lb))\n lbc = label(1 - inputImb, connectivity=1)\n ocbefore = len(regionprops(lbc))\n la = label(inputIma)\n oafter = len(regionprops(la))\n lac = label(1 - inputIma, connectivity=1)\n ocafter = len(regionprops(lac))\n\n if obefore == oafter and ocbefore == ocafter:\n deletableTemp = 1\n else:\n deletableTemp = 0\n\n return deletableTemp","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def get_num_slots(self):\n # Your code here\n return len(self.data)","def _check_n_results(self, n_results, sub):\n \n if sub[1].upper() != \"S\":\n try:\n int(n_results)\n if int(n_results) == 0:\n raise ValueError\n except ValueError:\n raise ValueError","def test_fixture_available_results(tmp_sample_project):\n config_dir = tmp_sample_project\n output = subprocess.run([\"smif\", \"available_results\", \"energy_central\", \"-d\", config_dir],\n stdout=subprocess.PIPE)\n\n out_str = str(output.stdout)\n assert(out_str.count('model run: energy_central') == 1)\n assert(out_str.count('sos model: energy') == 1)\n assert(out_str.count('sector model:') == 1)\n assert(out_str.count('output:') == 2)\n assert(out_str.count('output: cost') == 1)\n assert(out_str.count('output: water_demand') == 1)\n assert(out_str.count('no results') == 2)\n assert(out_str.count('decision') == 0)\n\n # Run energy_central and re-check output with optional flag for completed results\n subprocess.run([\"smif\", \"run\", \"energy_central\", \"-d\", config_dir], stdout=subprocess.PIPE)\n output = subprocess.run([\"smif\", \"available_results\", \"energy_central\", \"-d\", config_dir],\n stdout=subprocess.PIPE)\n\n out_str = str(output.stdout)\n assert(out_str.count('model run: energy_central') == 1)\n assert(out_str.count('sos model: energy') == 1)\n assert(out_str.count('sector model:') == 1)\n assert(out_str.count('output:') == 2)\n assert(out_str.count('output: cost') == 1)\n assert(out_str.count('output: water_demand') == 1)\n assert(out_str.count('no results') == 0)\n assert(out_str.count('decision') == 8)\n assert(out_str.count('decision 1') == 2)\n assert(out_str.count('decision 2') == 2)\n assert(out_str.count('decision 3') == 2)\n assert(out_str.count('decision 4') == 2)\n assert(out_str.count(': 2010') == 4)\n assert(out_str.count(': 2015') == 2)\n assert(out_str.count(': 2020') == 2)"],"string":"[\n \"def test_count_no_spins(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Test the number of spins counted.\\n self.assertEqual(mol_res_spin.count_spins(), 0)\",\n \"def test_count_spins(self):\\n\\n # Test the number of spins counted.\\n self.assertEqual(mol_res_spin.count_spins(), 4)\\n self.assertEqual(mol_res_spin.count_spins(skip_desel=False), 8)\\n self.assertEqual(mol_res_spin.count_spins(selection='@N5'), 1)\\n self.assertEqual(mol_res_spin.count_spins(selection='@N5', skip_desel=False), 2)\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_return_spin_pipe_fail(self):\\n\\n # Try to get a spin from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_spin_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for spin in mol_res_spin.spin_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_svm_count():\\n assert templates.svms() > 0\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_count_resources(ops_and_shots, expected_resources):\\n ops, shots = ops_and_shots\\n computed_resources = _count_resources(QuantumScript(ops=ops, shots=shots))\\n assert computed_resources == expected_resources\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def Count():\\n return CheckForError(lib.Generators_Get_Count())\",\n \"def test_svm_vs_vm_count():\\n assert templates.svms() >= templates.vm_count()\",\n \"def test_get_counturingErr(self):\\n for app_num, servo_type in app_nr.items():\\n try:\\n par = self.get_parameter(servo_type, app_num, COUNTURING_ERR_IDX, COUNTURING_ERR_SUB)\\n param_obj = self.__dict__[servo_type]._get_counturingErr()\\n acs_par, completion = param_obj.get_sync()\\n if(completion.code):\\n print \\\"\\\\nError code found in counturingErr...\\\"\\n continue\\n self.data_match(acs_par, par)\\n except NackEx:\\n continue\",\n \"def _get_slr_count(slot_list: List[Slot]) -> int:\\n slr_count_list = [slot.board.SLR_NUM for slot in slot_list]\\n assert all(slr_count_list[i] == slr_count_list[0] for i in range(len(slr_count_list)))\\n return slr_count_list[0]\",\n \"def test_total_procs():\\n result = _run_metric('total_procs')\\n assert result.exit_code == 0\",\n \"def test_svm_vs_vm_count():\\n assert environments.svms() >= environments.vm_count()\",\n \"def test_pressure_count(self):\\n self.assertEqual(self.Pcount, 7)\",\n \"def test_residue_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for residue in mol_res_spin.residue_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_count_ways_null():\\n assert f.count_ways(0) == 1\",\n \"def testPipeFound(self):\\n safeFoundHelper(self)\\n self.assertCurrentState(safe.Seeking)\",\n \"def test_count_0(self):\\n self.assertEqual(count(0), 0, 'Between 0 and 0, there is 0 lucky numbers.')\",\n \"def test_vm_count():\\n assert templates.vm_count() > 0\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def getNumRings(self, nPins, silent=False):\\n numPositions = 0\\n for nRings in itertools.count(0):\\n numPositions += self.getNumPosInRing(nRings)\\n if not silent and numPositions > nPins:\\n runLog.warning(\\n \\\"{0} does not fit exactly into a cartisian grid of any number of rings. \\\"\\n \\\"Rounding up to {1} rings which can hold {2} pins)\\\"\\n \\\"\\\".format(nPins, nRings, numPositions),\\n single=True,\\n label=\\\"Non-exact number of positions in cartesian lattice\\\",\\n )\\n if numPositions >= nPins:\\n return nRings\",\n \"def test_molecule_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for molecule in mol_res_spin.molecule_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def nspins(self):\\n return len(self)\",\n \"def test_spin_loop(self):\\n\\n # Spin data.\\n select = [1, 0]\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, 'N5')\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 2)\",\n \"def _n_spin_states(self) -> int:\\n if self.spin is None:\\n raise Exception(\\n \\\"cannot request number of spin states for spinless fermions\\\"\\n )\\n return round(2 * self.spin + 1)\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_return_residue_pipe_fail(self):\\n\\n # Try to get a residue from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')\",\n \"def test_return_molecule_pipe_fail(self):\\n\\n # Try to get a molecule from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')\",\n \"def test_amount_of_listings_no_listings(self):\\n listings = steam_market.get_total_amount_of_listings(soup=get_soup_from_path(TEST_FILE_NO_RESULTS))\\n self.assertEqual(0, listings)\",\n \"def test_svm_count():\\n assert environments.svms() > 0\\n count = 0\\n for l in list(environments.data):\\n e = environments[l]\\n count += e.svms\\n msg = ('SVM count mismatch. Environments says: ' +\\n str(environments.svms()) +\\n ', actual count: ' + str(count))\\n assert count == environments.svms(), msg\",\n \"def test_solvation_potassium_control(self):\\n waters = np.random.randint(1000, 10000)\\n log.debug('Trying {} waters with potassium...'.format(waters))\\n solvate(tleapfile='./cb6-but/tleap.in', pdbfile='cb6-but.pdb',\\n bufferwater=waters, counter_cation='K+')\\n potassium = sp.check_output([\\\"grep -oh 'K+' ./cb6-but/solvated.prmtop | wc -w\\\"],\\n shell=True)\\n self.assertEqual(int(potassium), 0)\",\n \"def test_spin_loop_no_selection(self):\\n\\n # Spin data.\\n select = [0, 1, 0, 0, 1, 1, 0, 1]\\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 8)\",\n \"def test_data_source_soaps_count_get(self):\\n pass\",\n \"def test_test(self):\\n\\n # The following should do nothing as the pipes exist.\\n pipes.check_pipe()\\n pipes.check_pipe('orig')\\n pipes.check_pipe('empty')\\n\\n # Assert that a RelaxNoPipeError occurs when the pipe doesn't exist.\\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe, 'x')\\n\\n # Reset relax.\\n reset()\\n\\n # Now none of the following pipes exist, hence errors should be thrown.\\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe)\\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe, 'orig')\\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe, 'empty')\",\n \"def get_spitfp_error_count(self):\\n return GetSPITFPErrorCount(*self.ipcon.send_request(self, BrickletBarometerV2.FUNCTION_GET_SPITFP_ERROR_COUNT, (), '', 'I I I I'))\",\n \"def test_count(self):\\n self._test_count_func(count)\",\n \"def Test_NumSegments(Daten):\\n N_Leitungen = len(Daten.PipeSegments)\\n\\n return N_Leitungen\",\n \"def test_own_count(self):\\n self._test_count_func(it_count)\",\n \"def test_count_roll_fail():\\n expected = np.array([3, 0, 1, 5, 0, 0])\\n result = analyze_roll.count_roll(np.array([1, 1, 3, 1, 4, 4]))\\n assert np.array_equal(expected, result) is False\",\n \"def test_count_when_data_is_not_present(self):\\n\\n temp_data = []\\n\\n tt = TemperatureTracker()\\n result = tt.count_from(temp_data)\\n self.assertEqual(result, 0)\",\n \"def test_vm_count():\\n assert environments.vm_count() > 0, 'Total VM count should be over 1.'\\n count = 0\\n for l in list(environments.data):\\n e = environments[l]\\n count += e.vm_count\\n msg = ('VM count mismatch. Environments says: ' +\\n str(environments.vm_count()) +\\n ', actual count: ' + str(count))\\n assert count == environments.vm_count(), msg\",\n \"def test_empty_system_error():\\n system = vermouth.system.System()\\n sequence = \\\"not empty\\\"\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n with pytest.raises(ValueError):\\n processor.run_system(system)\",\n \"def test_count_ways_wrong_value_raise(inputs, outputs):\\n with pytest.raises(outputs):\\n f.count_ways(inputs)\",\n \"def test_count_ways_positive(inputs, outputs):\\n assert f.count_ways(inputs) == outputs\",\n \"def test_count_10(self):\\n value: int = 10\\n result: int = 2\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"async def test_txn_list_with_zero_count(self):\\n response = await self.get_assert_status('/transactions?count=0', 400)\\n\\n self.assert_has_valid_error(response, 53)\",\n \"def count() -> int:\\n pass\",\n \"def count():\",\n \"def get_spitfp_error_count(self):\\n self.check_validity()\\n\\n return GetSPITFPErrorCount(*self.ipcon.send_request(self, BrickletIndustrialDualAnalogInV2.FUNCTION_GET_SPITFP_ERROR_COUNT, (), '', 24, 'I I I I'))\",\n \"def test_returns_zero_for_empty_grid(self):\\n grid = []\\n result = num_islands(grid)\\n self.assertEqual(result, 0)\",\n \"def test_getSampleCount(self):\\r\\n self.assertEqual(self.res1.getSampleCount(), 0)\\r\\n\\r\\n self.res1.addSample('S1', 42)\\r\\n self.assertEqual(self.res1.getSampleCount(), 1)\\r\\n\\r\\n self.res1.addSample('S2', 43)\\r\\n self.assertEqual(self.res1.getSampleCount(), 2)\",\n \"def getnumbarablocktriplets(self): # 3\\n res,resargs = self.__obj.getnumbarablocktriplets()\\n if res != 0:\\n result,msg = self.__getlasterror(res)\\n raise Error(rescode(res),msg)\\n _num_return_value = resargs\\n return _num_return_value\",\n \"def test_get_resource_license_resource_count_list(self):\\n pass\",\n \"def test_count_9(self):\\n value: int = 9\\n result: int = 2\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def getNumRings(self, nPins, silent=False):\\n nRings = hexagon.numRingsToHoldNumCells(nPins)\\n if not silent:\\n nPinsFullRings = self.getNumPositions(rings=nRings)\\n if nPins != nPinsFullRings:\\n runLog.warning(\\n \\\"{0} does not fit exactly into a hex grid of any number of rings. \\\"\\n \\\"Rounding up to {1} rings which can hold {2} pins)\\\"\\n \\\"\\\".format(nPins, nRings, nPinsFullRings),\\n single=True,\\n label=\\\"Non-exact number of positions in hex lattice\\\",\\n )\\n return nRings\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_counter(self):\\n self.assertEqual(self._n_registered, 1)\",\n \"def test_count_173(self):\\n value: int = 173\\n result: int = 55\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_simulator_0_shots():\\n dev = _aws_device(wires=2, device_type=AwsDeviceType.SIMULATOR, shots=0)\\n assert dev.shots == 1\\n assert dev.analytic\",\n \"def spine_switch_count(self):\\n spines = GetSwitchDetails().get_spine_switch_ip()\\n totalSpines = len(spines)\\n return totalSpines\",\n \"def test_count_increments():\\n\\n # Signals and interface etc.\\n clk = Clock()\\n reset = Reset(async=True)\\n count = Signal(intbv()[8:])\\n\\n def _bench():\\n dut = Cosimulation('vvp -m ./myhdl.vpi ./bin/example_module/example_module', \\n clk=clk, \\n reset=reset,\\n count=count)\\n\\n @instance\\n def stimulus():\\n yield delay(255 * 2 + 4)\\n print(count)\\n assert count == 0xff\\n raise StopSimulation\\n\\n return dut, clk.gen(), reset.pulse(), stimulus\\n\\n # = traceSignals(_bench)\\n Simulation(_bench()).run()\",\n \"def test_count_35(self):\\n value: int = 35\\n result: int = 6\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_invoke_pipe_not_found():\\n\\n testapp = holocron.Application()\\n\\n with pytest.raises(ValueError) as excinfo:\\n next(testapp.invoke(\\\"test\\\"))\\n\\n assert str(excinfo.value) == \\\"no such pipe: 'test'\\\"\",\n \"def test_getSampleCount(self):\\r\\n self.assertEqual(self.estimator1.getSampleCount(), 1)\",\n \"def test_specific_qubit_pauli_error_gate_100percent(self):\\n qr = QuantumRegister(2, 'qr')\\n cr = ClassicalRegister(2, 'cr')\\n circuit = QuantumCircuit(qr, cr)\\n circuit.iden(qr)\\n circuit.barrier(qr)\\n circuit.measure(qr, cr)\\n backend = QasmSimulator()\\n shots = 100\\n # test noise model\\n error = pauli_error([('X', 1)])\\n noise_model = NoiseModel()\\n noise_model.add_quantum_error(error, 'id', [1])\\n # Execute\\n target = {'0x2': shots}\\n circuit = transpile(circuit, basis_gates=noise_model.basis_gates)\\n qobj = assemble([circuit], backend, shots=shots)\\n result = backend.run(qobj, noise_model=noise_model).result()\\n self.is_completed(result)\\n self.compare_counts(result, [circuit], [target], delta=0)\",\n \"def test_getReferenceIndividualCount(self):\\r\\n with self.assertRaises(ValueError):\\r\\n self.res1.getReferenceIndividualCount('S1')\\r\\n\\r\\n self.res1.addSample('S1', 42)\\r\\n self.assertEqual(self.res1.getReferenceIndividualCount('S1'), 42)\",\n \"def test_count_459(self):\\n value: int = 459\\n result: int = 148\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_get_spawning_profile_list():\\n center = Coordinates(1 , 1)\\n radius = 10\\n speed_limit = 20\\n default_driver = DriverProfile(\\\"Default\\\", 8, 2, 2, 0, 30, 3, 1)\\n default_vehicle = VehicleProfile(\\\"Default\\\", 5, 15, 2, 2, 1000, 65)\\n default_spawn = SpawningProfile(\\\"Default\\\", default_driver, default_vehicle)\\n\\n i = Intersection(center, radius, speed_limit)\\n\\n l = i.get_spawning_profile_list()\\n\\n assert not l\\n\\n i.add_spawning_profile(default_spawn)\\n\\n assert l\\n\\n assert len(l) == 1\\n\\n i.remove_spawning_profile(default_spawn)\\n\\n assert len(l) == 0\\n assert not l\",\n \"def test_song_counts(self):\\n self.assertEqual(self.show.total_song_count, None)\",\n \"def get_nrof_pumps(self):\\n pumps = 0\\n for p in self.pump_array:\\n if p:\\n pumps += 1\\n return pumps\",\n \"def testSectionCount(self):\\n\\n self.sectionCount(3640)\",\n \"def test_all_qubit_pauli_error_gate_100percent(self):\\n qr = QuantumRegister(2, 'qr')\\n cr = ClassicalRegister(2, 'cr')\\n circuit = QuantumCircuit(qr, cr)\\n circuit.iden(qr)\\n circuit.barrier(qr)\\n circuit.measure(qr, cr)\\n backend = QasmSimulator()\\n shots = 100\\n # test noise model\\n error = pauli_error([('X', 1)])\\n noise_model = NoiseModel()\\n noise_model.add_all_qubit_quantum_error(error, 'id')\\n # Execute\\n target = {'0x3': shots}\\n circuit = transpile(circuit, basis_gates=noise_model.basis_gates)\\n qobj = assemble([circuit], backend, shots=shots)\\n result = backend.run(qobj, noise_model=noise_model).result()\\n self.is_completed(result)\\n self.compare_counts(result, [circuit], [target], delta=0)\",\n \"def _error_count(cls, samples: Samples) -> int:\\n return cls.__sample_count(samples, \\\"false\\\")\",\n \"def test_retry_count_query():\\n error_list = [OperationalError, OperationalError, OperationalError, SystemError, RuntimeError]\\n with mock.patch(\\\"snowshu.adapters.source_adapters.SnowflakeAdapter._count_query\\\", side_effect=error_list):\\n sf = SnowflakeAdapter()\\n with pytest.raises(SystemError) as exc:\\n sf.check_count_and_query(\\\"select * from unknown_table\\\", 10, False)\\n \\n # assert that the 4th error was raised\\n assert exc.errisinstance(SystemError)\\n assert sf.check_count_and_query.retry.statistics[\\\"attempt_number\\\"] == 4\",\n \"def test_count_reads_per_cluster(self):\\n \\n bedtool = pybedtools.BedTool(clipper.test_file(\\\"clip_analysis_test_peak_results.bed\\\"))\\n \\n total_reads, reads_per_cluster = count_reads_per_cluster(bedtool, None)\\n \\n self.assertListEqual([147,52, 239, 85, 47, 119, 58, 588, 92, 59, 196, 36], reads_per_cluster)\\n self.assertEqual(sum([147,52, 239, 85, 47, 119, 58, 588, 92, 59, 196, 36]), total_reads)\",\n \"def test_step_count(self):\\n inp = [(0, 0), (1, 1), (1, 2)]\\n expected = 2\\n actual = get_num_steps(inp)\\n self.assertEqual(expected, actual)\",\n \"def test_count_1719(self):\\n value: int = 2645\\n result: int = 1113\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def __init__(self, pins_nbr=10, throws_nbr=2, throws=None):\\n self.pins_nbr = pins_nbr\\n self.throws_nbr = throws_nbr\\n\\n if throws is None:\\n self.throws = []\\n else:\\n self.throws = throws\\n if len(self.throws):\\n self.sanity_check() # runs sanity_check\\n assert self.complete() # assert completeness\",\n \"def test_error_num_entries(self, state_vector, wires):\\n\\n with pytest.raises(ValueError, match=\\\"'state_vector' must be of shape\\\"):\\n MottonenStatePreparation(state_vector, wires)\",\n \"def test_mount_status_nas_share_by_pool(self):\\n pass\",\n \"def test_specific_qubit_pauli_error_gate_25percent(self):\\n qr = QuantumRegister(2, 'qr')\\n cr = ClassicalRegister(2, 'cr')\\n circuit = QuantumCircuit(qr, cr)\\n circuit.iden(qr)\\n circuit.barrier(qr)\\n circuit.measure(qr, cr)\\n backend = QasmSimulator()\\n shots = 2000\\n # test noise model\\n error = pauli_error([('X', 0.25), ('I', 0.75)])\\n noise_model = NoiseModel()\\n noise_model.add_quantum_error(error, 'id', [0])\\n # Execute\\n target = {'0x0': 3 * shots / 4, '0x1': shots / 4}\\n circuit = transpile(circuit, basis_gates=noise_model.basis_gates)\\n qobj = assemble([circuit], backend, shots=shots)\\n result = backend.run(qobj, noise_model=noise_model).result()\\n self.is_completed(result)\\n self.compare_counts(result, [circuit], [target], delta=0.05 * shots)\",\n \"def test_get_resource_license_resource_count_by_moid(self):\\n pass\",\n \"def test_count_2645(self):\\n value: int = 1719\\n result: int = 723\\n self.assertEqual(count(value), result, f'Between 0 and {value}, there are {result} lucky numbers.')\",\n \"def test_results_length(spheroid_convex_fixture):\\n assert(len(spheroid_convex_fixture.pairs) == 1000)\\n assert(len(spheroid_convex_fixture.combinations) == 1000)\\n assert(len(spheroid_convex_fixture.deltas) == 1000)\",\n \"def test_count_bad(self):\\n with self.assertRaises(KeyError):\\n models.storage.count(\\\"2\\\")\",\n \"def test_bababc():\\n assert part_01.count_for('bababc', 2) == 1\\n assert part_01.count_for('bababc', 3) == 1\",\n \"def test_cell_list_limit_0_success(self, mock_list):\\n self.shell('cell-list -r 1 --limit 0')\\n mock_list.assert_called_once_with(limit=0)\",\n \"def test_triangle_count_04(self):\\n body = {\\\"direction\\\": \\\"OUT\\\"}\\n code, res = Algorithm().post_triangle_count(body, auth=auth)\\n id = res[\\\"task_id\\\"]\\n if id > 0:\\n result = get_task_res(id, 120, auth=auth)\\n print(result)\\n assert result == {'edges_out': 13, 'vertices_out': 7, 'triangles': 2}\\n else:\\n assert 0\",\n \"def test_cell_list_limit_positive_num_success(self, mock_list):\\n self.shell('cell-list -r 1 --limit 1')\\n mock_list.assert_called_once_with(limit=1)\",\n \"def countObjects(inputImb, inputIma):\\n\\n lb = label(inputImb)\\n obefore = len(regionprops(lb))\\n lbc = label(1 - inputImb, connectivity=1)\\n ocbefore = len(regionprops(lbc))\\n la = label(inputIma)\\n oafter = len(regionprops(la))\\n lac = label(1 - inputIma, connectivity=1)\\n ocafter = len(regionprops(lac))\\n\\n if obefore == oafter and ocbefore == ocafter:\\n deletableTemp = 1\\n else:\\n deletableTemp = 0\\n\\n return deletableTemp\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def get_num_slots(self):\\n # Your code here\\n return len(self.data)\",\n \"def _check_n_results(self, n_results, sub):\\n \\n if sub[1].upper() != \\\"S\\\":\\n try:\\n int(n_results)\\n if int(n_results) == 0:\\n raise ValueError\\n except ValueError:\\n raise ValueError\",\n \"def test_fixture_available_results(tmp_sample_project):\\n config_dir = tmp_sample_project\\n output = subprocess.run([\\\"smif\\\", \\\"available_results\\\", \\\"energy_central\\\", \\\"-d\\\", config_dir],\\n stdout=subprocess.PIPE)\\n\\n out_str = str(output.stdout)\\n assert(out_str.count('model run: energy_central') == 1)\\n assert(out_str.count('sos model: energy') == 1)\\n assert(out_str.count('sector model:') == 1)\\n assert(out_str.count('output:') == 2)\\n assert(out_str.count('output: cost') == 1)\\n assert(out_str.count('output: water_demand') == 1)\\n assert(out_str.count('no results') == 2)\\n assert(out_str.count('decision') == 0)\\n\\n # Run energy_central and re-check output with optional flag for completed results\\n subprocess.run([\\\"smif\\\", \\\"run\\\", \\\"energy_central\\\", \\\"-d\\\", config_dir], stdout=subprocess.PIPE)\\n output = subprocess.run([\\\"smif\\\", \\\"available_results\\\", \\\"energy_central\\\", \\\"-d\\\", config_dir],\\n stdout=subprocess.PIPE)\\n\\n out_str = str(output.stdout)\\n assert(out_str.count('model run: energy_central') == 1)\\n assert(out_str.count('sos model: energy') == 1)\\n assert(out_str.count('sector model:') == 1)\\n assert(out_str.count('output:') == 2)\\n assert(out_str.count('output: cost') == 1)\\n assert(out_str.count('output: water_demand') == 1)\\n assert(out_str.count('no results') == 0)\\n assert(out_str.count('decision') == 8)\\n assert(out_str.count('decision 1') == 2)\\n assert(out_str.count('decision 2') == 2)\\n assert(out_str.count('decision 3') == 2)\\n assert(out_str.count('decision 4') == 2)\\n assert(out_str.count(': 2010') == 4)\\n assert(out_str.count(': 2015') == 2)\\n assert(out_str.count(': 2020') == 2)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.8297968","0.7812048","0.67697406","0.61876446","0.6167623","0.6036055","0.58979064","0.58179224","0.5769859","0.57561326","0.5715153","0.5708538","0.5594331","0.5509007","0.54806995","0.5468505","0.54357624","0.54193336","0.5419145","0.5415963","0.5369951","0.5368415","0.5362159","0.53567004","0.5347017","0.5342309","0.5308356","0.5300264","0.5290868","0.52851397","0.526936","0.5260823","0.52557546","0.5218017","0.5183577","0.51613784","0.5139416","0.51385707","0.51303065","0.5106504","0.50970554","0.5077713","0.5061986","0.5057638","0.50448155","0.5036136","0.5012559","0.5012125","0.50023025","0.4998806","0.49967253","0.49915546","0.49883598","0.4987899","0.49830267","0.49555027","0.49544767","0.49524966","0.49495772","0.49322143","0.49250495","0.4924959","0.4921494","0.4913995","0.49093235","0.49081147","0.490147","0.49008536","0.4879159","0.48769414","0.4872942","0.48657027","0.48546252","0.48543438","0.48524702","0.48522857","0.48499957","0.4843921","0.48431456","0.4839602","0.48391297","0.4831956","0.4827933","0.48218554","0.48163095","0.48141143","0.48099524","0.48034948","0.47969764","0.4789686","0.47818974","0.4781248","0.4779218","0.4763236","0.47546247","0.475461","0.47522384","0.47521362","0.4750842","0.474984"],"string":"[\n \"0.8297968\",\n \"0.7812048\",\n \"0.67697406\",\n \"0.61876446\",\n \"0.6167623\",\n \"0.6036055\",\n \"0.58979064\",\n \"0.58179224\",\n \"0.5769859\",\n \"0.57561326\",\n \"0.5715153\",\n \"0.5708538\",\n \"0.5594331\",\n \"0.5509007\",\n \"0.54806995\",\n \"0.5468505\",\n \"0.54357624\",\n \"0.54193336\",\n \"0.5419145\",\n \"0.5415963\",\n \"0.5369951\",\n \"0.5368415\",\n \"0.5362159\",\n \"0.53567004\",\n \"0.5347017\",\n \"0.5342309\",\n \"0.5308356\",\n \"0.5300264\",\n \"0.5290868\",\n \"0.52851397\",\n \"0.526936\",\n \"0.5260823\",\n \"0.52557546\",\n \"0.5218017\",\n \"0.5183577\",\n \"0.51613784\",\n \"0.5139416\",\n \"0.51385707\",\n \"0.51303065\",\n \"0.5106504\",\n \"0.50970554\",\n \"0.5077713\",\n \"0.5061986\",\n \"0.5057638\",\n \"0.50448155\",\n \"0.5036136\",\n \"0.5012559\",\n \"0.5012125\",\n \"0.50023025\",\n \"0.4998806\",\n \"0.49967253\",\n \"0.49915546\",\n \"0.49883598\",\n \"0.4987899\",\n \"0.49830267\",\n \"0.49555027\",\n \"0.49544767\",\n \"0.49524966\",\n \"0.49495772\",\n \"0.49322143\",\n \"0.49250495\",\n \"0.4924959\",\n \"0.4921494\",\n \"0.4913995\",\n \"0.49093235\",\n \"0.49081147\",\n \"0.490147\",\n \"0.49008536\",\n \"0.4879159\",\n \"0.48769414\",\n \"0.4872942\",\n \"0.48657027\",\n \"0.48546252\",\n \"0.48543438\",\n \"0.48524702\",\n \"0.48522857\",\n \"0.48499957\",\n \"0.4843921\",\n \"0.48431456\",\n \"0.4839602\",\n \"0.48391297\",\n \"0.4831956\",\n \"0.4827933\",\n \"0.48218554\",\n \"0.48163095\",\n \"0.48141143\",\n \"0.48099524\",\n \"0.48034948\",\n \"0.47969764\",\n \"0.4789686\",\n \"0.47818974\",\n \"0.4781248\",\n \"0.4779218\",\n \"0.4763236\",\n \"0.47546247\",\n \"0.475461\",\n \"0.47522384\",\n \"0.47521362\",\n \"0.4750842\",\n \"0.474984\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.88973"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81474,"cells":{"query":{"kind":"string","value":"Test the function for determining if moleculeresiduespin data exists. The function tested is pipe_control.mol_res_spin.exists_mol_res_spin_data()."},"document":{"kind":"string","value":"def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def isExist(data):\n return True/False","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_count_no_spins(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 0)","def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def exists(self, datadir):\n return False","def check_for_data():\n if not (os.path.exists(ep.get_test_data_path()) or os.path.exists(ep.get_dbn_weight_path())):\n return False\n return True","def is_version_data_existed(self):\n # if exists, skip\n # return \n\n return True","def CheckForExistence(requested_data, available_data):\n if requested_data is not None:\n return 1 # The requested data exists.\n elif available_data:\n return -1 # The requested data does not exist.\n else:\n return 0 # No data exists at all.","def testExists(self, mock_exists):\n mock_exists.return_value = True\n\n self.assertTrue(\n self.mr.exists\n )\n\n mock_exists.assert_called_once_with(\n os.path.join(self.directory, self.filename)\n )\n\n mock_exists.return_value = False\n\n self.assertFalse(\n self.mr.exists\n )","def datafolderexist(name):\n folderpath = os.path.join(pathtofolder(), name)\n return os.path.exists(folderpath)","def file_exists(msl_data_path, filename):\n return os.path.isfile(msl_data_path + filename)","def exists():\n check50.include(\"data\")\n check50.exists(\"adventure.py\")\n check50.exists(\"room.py\")","def check_data_struct():\n if not os.path.exists(PROJECT_ROOT+'/data'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data')\n\n if not os.path.exists(PROJECT_ROOT+'/data/CUB_200_2011'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/CUB_200_2011')\n\n if not os.path.exists(PROJECT_ROOT+'/data/segmentations'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/segmentations')\n\n if not os.path.exists(PROJECT_ROOT+'/data/attributes.txt'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/attributes.txt')","def check_model_exists(ckpt):\n expected_data = ckpt + \".data-00000-of-00001\"\n return os.path.exists(expected_data)","def test_return_single_residue_info(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_single_residue_info('1')\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\n res5 = mol_res_spin.return_single_residue_info('-5')\n\n # Test the data of residue 1.\n self.assertEqual(res1, (1, None))\n\n # Test the data of residue 2.\n self.assertEqual(res2, (2, 'Glu'))\n\n # Test the data of residue 4.\n self.assertEqual(res4, (4, 'Pro'))\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5, (-5, None))","def checkfolderdata(folder = 'datas'):\n if datafolderexist(folder):\n return True\n else:\n createdatafolder(folder)\n checkfolderdata(folder)","def exist(self):","def test_exists_false(self):\n self.assertFalse(PrepSample.exists('Not_a_Sample', self.prep_template))","def check_file_existing(k_out, sphere_radius,full_path):\n cwd = full_path\n file_names = ['/T_ns_', '/Energy_', '/Distance-e-to-e_',\n '/chain_on_iterations_']\n\n kout = f'{k_out:.3f}'\n spr_rad = f'{sphere_radius:.3f}'\n\n current = \"kout_\" + kout + \"_\" + \"spr_rad_\" + spr_rad\n for file_name in file_names:\n #print (cwd + file_name + current + \".pkl\")\n if not os.path.exists(cwd + file_name + current + \".pkl\"):\n return False\n return True","def check_exist(self):\n helper.RbdImageOperator._check_rbd_image(self.real_path)","def data_available(dataset_name=None):\r\n for file_list in data_resources[dataset_name]['files']:\r\n for file in file_list:\r\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\r\n return False\r\n return True","def test_narrative_data_missing(self, config_handler):\n spec = Spec.from_dict(\n {\"name\": \"homogeneity_coefficient\", \"unit\": \"percentage\", \"dtype\": \"float\"}\n )\n with raises(SmifDataNotFoundError):\n config_handler.read_narrative_variant_data(\"does not exist\", spec)","def test_exists(self):\n self.assertTrue(bool(self.photo))","def find_null(data, sub_reg):\r\n subreg_sqkm_data = data.loc[pd.IndexSlice[:, sub_reg, :], pd.IndexSlice['Sq Km']]\r\n if subreg_sqkm_data.isnull().values.any() == True:\r\n print(\"\\nSq km measurements are missing for:\")\r\n print(subreg_sqkm_data[subreg_sqkm_data.isnull()])\r\n else:\r\n print(\"\\nThere are no missing sq km values for this sub-region.\")","def test_get_all_rides_if_exists_success(self):\n res = self.client().get('api/v1/rides')\n self.assertEqual(res.status_code, 200)\n self.assertIn('Kutus', str(res.data))","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def exists(self):\n\t\tif self.hasUdim:\n\t\t\treturn len( self.udimPaths ) != 0\n\t\treturn super( textureFile, self ).exists","def test_return_molecule(self):\n\n # Ask for a few molecules.\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\n\n # Test the data of molecule 1.\n self.assertEqual(mol1.name, 'Ap4Aase')\n\n # Test the data of molecule 2.\n self.assertEqual(mol2.name, 'RNA')","def data_ready(self) -> bool:\n data_ready = ctypes.c_uint8()\n Utils.check(VL53L1X_C_LIBRARY.VL53L1_GetMeasurementDataReady(self.dev, byref(data_ready)))\n return data_ready.value != 0","def check_dataset_exists(dataset):\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\n return result == 0","def test_exists_false(self):\n self.assertFalse(Sample.exists('Not_a_Sample', self.sample_template))","def check_data_exist(data):\n if data is not None:\n if data.text is not None:\n return True\n return False","def test_exists_true(self):\n self.assertTrue(PrepSample.exists(self.sample_id, self.prep_template))","def check_resource_exists(test_cma_creds, test_rma_url, path):\n creds = test_cma_creds.split(\":\")\n response = requests.get(\n f\"{test_rma_url}/{path}\",\n headers={\"Accept\": \"application/json\"},\n auth=HTTPDigestAuth(creds[0], creds[1]),\n )\n return response.status_code == 200","def datafileexist(filename):\n filePath = os.path.join(pathtofolder(), \"datas\", filename)\n fileFormat = '.csv'\n return os.path.exists(f'{filePath+fileFormat}')","def test_molecule_loop(self):\n\n # Loop over the molecules.\n for mol in mol_res_spin.molecule_loop('#RNA'):\n # Test the molecule name.\n self.assertEqual(mol.name, 'RNA')\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)","def check_data_exist(hdir):\n cmd = 'ls ' + hdir + '*/* > ' + zspace\n os.system(cmd)\n with open(zspace, 'r') as f:\n out = f.read()\n mcf.rm_files(zspace)\n\n for name in ['dtf1', 'fov', 'bpix1', 'evt1', 'msk1', 'mtl1', 'std_dtfstat1', 'std_flt1', 'asol']:\n mc = re.search(name, out)\n if mc is None:\n line = 'Some data files are missing and the re-process is terminated. Check: ' + hdir + '\\n'\n with open(zspace, 'w') as fo:\n fo.write(line)\n\n cmd = 'cat ' + zspace + ' | mailx -s \"Subject: hrc re-process failed\" tisobe@cfa.harvard.edu'\n os.system(cmd)\n\n return False\n\n return True","def has_data(self) -> bool:\n raise NotImplementedError","def test_get_available_file_path_exists(self, mock_uuid4):\n mock_uuid4.side_effect = ['Voltaire', 'Franklin']\n\n directory = Path(__file__, '..').resolve()\n taken_file = directory / 'Voltaire'\n\n taken_file.write_text('Common sense is not so common.')\n\n self.assertEqual(\n self.mikla.get_available_file_path(directory),\n str(directory / 'Franklin'),\n )\n\n taken_file.unlink()","def test_return_single_residue_info_fail(self):\n\n # Ask for a few residues.\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')","def test_return_residue(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_residue(':1')\n res2 = mol_res_spin.return_residue(selection=':2')\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\n\n # Test the data of residue 1.\n self.assertEqual(res1.num, 1)\n self.assertEqual(res1.name, None)\n\n # Test the data of residue 2.\n self.assertEqual(res2.num, 2)\n self.assertEqual(res2.name, 'Glu')\n\n # Test the data of residue 4.\n self.assertEqual(res4.num, 4)\n self.assertEqual(res4.name, 'Pro')\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5.num, -5)\n self.assertEqual(res5.name, None)\n self.assertEqual(res5.spin[1].name, 'N5')","def testForExistence(self):\n self.assertTrue(cached_list_logic.isCachedListExists('cached_list'))\n self.assertFalse(cached_list_logic.isCachedListExists('none_existent'))","def particleExists(*args, **kwargs)->bool:\n pass","def exists(sim):\n return (sim['N'] > 0)","def _check_data_valid(self):\n\n is_valid = (sum(~np.isnan(self.data).flatten()) > 0 and self.data.flatten().sum() != 0)\n if not is_valid:\n raise FITSException(f\"No data in {self.survey}\")","def test_existence_checking(self):\n params = [f'2010-{num:0>2}' for num in range(1, 13)] # all month of 2010\n for month in params:\n with self.assertRaises(ValueError) as cm: # ValueError should be raised with proper message\n download_data(month)\n self.assertEqual(f'Dataset from {month} cannot be found on lichess.org', cm.exception.args[0], msg=month)\n # check if error message was as expected","def test_exists_true(self):\n self.assertTrue(Sample.exists(self.sample_id, self.sample_template))","def object_exists(self, fname):\n return False","def check_path(data_pointer, log, msg):\n if not os.path.exists(data_pointer):\n log.debug(msg)\n return False\n else:\n return data_pointer","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.data_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.data_dir))\n if not osp.exists(self.raw_mat_path):\n raise RuntimeError(\"'{}' is not available\".format(self.raw_mat_path))\n if not osp.exists(self.split_new_det_mat_path):\n raise RuntimeError(\"'{}' is not available\".format(self.split_new_det_mat_path))\n if not osp.exists(self.split_new_lab_mat_path):\n raise RuntimeError(\"'{}' is not available\".format(self.split_new_lab_mat_path))","def check_helpers(self):\n paths = self.get_helper_out_paths()\n\n for p in paths:\n full_path = p + \".data-00000-of-00001\"\n file = Path(full_path)\n if not file.exists():\n return False\n\n return True","def _exists(cursor, table, data):\n cursor.execute('SELECT 1 FROM {} WHERE ({}) = ({})'.format(table, *_query_fields(data)), data)\n return bool(cursor.fetchone())","def object_exists(self, fname):\n return True","def test_return_spin_pipe_fail(self):\n\n # Try to get a spin from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')","def exists(self):\n return os.path.exists(self.sensorpath)","def hasImageData(self,volumeNode):\n if not volumeNode:\n logging.debug('hasImageData failed: no volume node')\n return False\n if volumeNode.GetImageData() is None:\n logging.debug('hasImageData failed: no image data in volume node')\n return False\n return True","def test_molecule_loop_no_selection(self):\n\n # Molecule data.\n name = ['Ap4Aase', 'RNA']\n\n # Loop over the molecules.\n i = 0\n for mol in mol_res_spin.molecule_loop():\n # Test the molecule names.\n self.assertEqual(mol.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)","def exists():\n\treturn os.path.exists('data/strmr.db')","def resultExist(probName,algoName,fitName,inst,s,c,n,k,q,w,m,t,e):\n if probName == 'NKQ':\n nameOfF = './result/'+probName+'-'+algoName+'-F'+fitName+'-M'+m+'-I'+str(inst)+'-S'+str(s)+'-W'+str(w)+'-N'+str(n)+'-K'+str(k)+'-C'+str(c)+'-Q'+str(q)+'-T'+str(t)+'-E'+str(e)+'.txt'\n elif probName == 'NK' or probName == 'NonNK':\n nameOfF = './result/'+probName+'-'+algoName+'-F'+fitName+'-C'+str(c)+'-I'+str(inst)+'-S'+str(s)+'-W'+str(w)+'-N'+str(n)+'-K'+str(k)+'-E'+str(e)+'.txt'\n\n if os.path.isfile(nameOfF)==True:\n print nameOfF, 'exists!!!'\n return os.path.isfile(nameOfF)","def id_exists(test_name):\n result_json = None\n try:\n with open(robot_dir + \"/output/results/{}.json\".format(test_name.replace(' ', ''))) as result_file:\n result_json = json.load(result_file)\n except:\n print(\"Failed to open the result json\")\n return False\n #look for values NEW_ASSOC, NEW_PROP1, NEW_PROP2\n print(result_json)\n if 6 == 6:\n return True\n return \"Length is not 6\"","def test_exists(self):\n self.assertTrue(os.path.exists(__file__) == self._system.exists(__file__))","def is_empty(self):\n for key, dataset in self.datasets.items():\n try:\n has_data = dataset.has_data()\n except MFDataException as mfde:\n raise MFDataException(\n mfdata_except=mfde,\n model=self._container_package.model_name,\n package=self._container_package._get_pname(),\n message=\"Error occurred while verifying\"\n ' data of dataset \"{}\" in block '\n '\"{}\"'.format(dataset.structure.name, self.structure.name),\n )\n\n if has_data is not None and has_data:\n return False\n return True","def test_exists(self):\n d = self._examineOrSelect()\n self._response(b'* 3 EXISTS')\n self.assertEqual(\n self.successResultOf(d),\n {'READ-WRITE': False, 'EXISTS': 3})","def _check_data_point(cube, metadata):\n point_index = []\n\n for dim_length in cube.shape:\n point_index.append(int(random.random() * dim_length))\n\n point_index = tuple(point_index)\n\n try:\n point_cube = cube[point_index]\n _data_point = point_cube.data\n except Exception:\n msg = 'Unable to extract data point {} from file: {}'.format(\n point_index, metadata['basename'])\n raise FileValidationError(msg)\n else:\n return True","def test_data_source_soaps_id_exists_get(self):\n pass","def object_exists(self, fname):\n return self.object_exists","def test_find(self):\r\n input_dir = None\r\n try:\r\n input_dir = tempfile.mkdtemp()\r\n input_file = 'conpot/tests/data/VOGON-POEM-MIB.mib'\r\n shutil.copy(input_file, input_dir)\r\n available_mibs = find_mibs([input_dir])\r\n self.assertIn('VOGON-POEM-MIB', available_mibs)\r\n finally:\r\n shutil.rmtree(input_dir)","def exists(dtype, name, rootdir=None):\n return FreezableAPI.to_slug(dtype,name) in FreezableAPI.datasets(rootdir=rootdir)","def check_file_exist(self):\n return False","def hasImageData(self,volumeNode):\n if not volumeNode:\n logging.debug('hasImageData failed: no volume node')\n return False\n return True","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.data_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.data_dir))\n if not osp.exists(self.split_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.split_dir))","def _CheckFileExistsWithData(self, logs, graph):\n self.assertTrue(graph in logs, 'File %s was not output.' % graph)\n self.assertTrue(logs[graph], 'File %s did not contain data.' % graph)","def assert_data_fragments_correct(self) -> bool:\n read_path = Path(os.environ[\"DATA_PATH\"]) / \"fragments\"\n if not read_path.exists():\n return False\n bin_images = [img for img in read_path.iterdir() if \"binarized\" in img.name]\n if len(bin_images) == 0:\n return False\n return True","def hasImageData(self,volumeNode):\n if not volumeNode:\n print('no volume node')\n return False\n if volumeNode.GetImageData() == None:\n print('no image data')\n return False\n return True","def __check_array__(self):\n if self.data_array is None:\n mess = 'No data array is present, please load before attempting to create XYZ array.'\n if isinstance(self.mess_inst, MessagesGUI):\n self.mess_inst.message(mess)\n else:\n print(mess)\n return False\n else:\n return True","def has_error(self):\r\n return self._arm.has_error","def is_file_exists(self):\n pass","def exists(self):\r\n return os.path.exists(self.full_path)","def test_output_exists():\n global out_dir, cor_dir\n assert(path.exists(path.join(out_dir, 'oshea_similarity.json')))","def test_full_function(self):\n\t\t# Import the rubric\n\t\ttemplate_data = pd.read_csv('tests/statcast_spin/live_Darvish_July2019_test.csv').round(SIG_DIG)\n\n\t\t# Run the method in question\n\t\tdf = spin.statcast_pitcher_spin(start_dt='2019-07-01', end_dt='2019-07-31', player_id=506433)\n\n\t\t# Columns needed to be checked\n\t\ttarget_columns = ['Mx', 'Mz', 'phi', 'theta']\n\n\t\tfor column in target_columns:\n\t\t\tlogging.info(\"Begin testing on {}\".format(column))\n\n\n\t\t\tif column in ['Mz']:\n\t\t\t# Almost equal assertion is necessary for small differences that arise after consecutive calculations\n\t\t\t\tself.assertTrue(self.compare_almost_equal(df, template_data, column))\n\n\t\t\telse:\n\t\t\t\tself.assertTrue(self.compare_columns(df, template_data, column))\n\n\t\t\tlogging.info(\"{} passed\".format(df, template_data, column))\n\n\n\t\tlogging.info(\"All tests completed\")","def check_for_residue_existance(self):\n if not self.pose.total_residue():\n print \"No pose Loaded.\"\n return False\n\n if not self.current_chain.get() or not self.current_residue.get():\n print \"Chain or residue not set\"\n return False\n\n current_region = self.current_residue.get().split(\":\")\n if len(current_region)>1:\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\n\n\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\n print \"Region not found in pose\"\n return False\n else:\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\n\n print \"Residue not found in pose\"\n return False\n\n #If everythig is good then:\n return True","def pvExistTest(self, context, addr, fullname):\n if fullname in self.pcas_manager.pvf:\n return pcaspy.pverExistsHere\n else:\n return pcaspy.pverDoesNotExistHere","def _loaded_data(self):\n try:\n dsize = [int(d) for d\n in self.run('fits size', via='get').split()]\n except (ValueError, TypeError, AttributeError) as err:\n log.debug(f' FITS size error: {err}')\n return False\n else:\n if 0 in dsize:\n return False\n else:\n return True","def has_data(self):\n return len(self.data) > 0","def test_postrun_nodata(self):\n\n from scripts.create_pointer_file import postrun\n\n with self.assertRaises(RuntimeError) as raised_excep:\n postrun(projectFile=\"/tmp/myproject.prproj\",projectFileExtension=\".prproj\",\n dataCache={'invalidkey':\"/path/to/my/assets\"})\n self.assertEqual(str(raised_excep.exception),\"No created_asset_folder in data cache. This postrun must depend on make_asset_folder\")","def test_exists_false(self):\n self.assertFalse(PrepTemplate.exists(2))","def task_validate_rawdata_file(pk):\n\n # init and checks\n valid = False\n logger = Logger.get_logger(StringIO())\n try:\n df = Data.objects.get(id=pk)\n assert df.kind == 'rd_file'\n tr = df.content_object\n except:\n logger.log('ERROR')\n return valid\n\n try:\n logger.log('looking at raw data file with pk: %s' % pk)\n rd, sr = read_hdf5_arc(df.file.path)\n logger.log('found rd_file: %s' % df.name)\n len_rd_sec = rd.shape[0] / sr\n logger.log('found data in %d channels, for %d sec' % (\n rd.shape[1], len_rd_sec))\n\n # TODO: more checks?\n\n logger.log('rd_file passed all checks')\n valid = True\n except Exception, ex:\n logger.log('ERROR: rawdata file check: %s' % str(ex))\n finally:\n df.save()\n tr.valid_rd_log = logger.get_content()\n tr.save()\n return valid","def check_if_file_exists(self, sensor_id:str, name:str)->str:\n ret_value = \"\"\n file_name = '%s/%s.*.%s.json' % (self.generate_data_prep, sensor_id, name)\n try: \n ret_value = glob.glob(file_name)\n except Exception as e:\n print(\"OSError - Failed top get file (%s) - %s\" % (file_name, e))\n ret_value = False \n \n if ret_value != False and len(ret_value) > 0: \n ret_value = ret_value[0]\n\n return ret_value","def test_no_track_data_error():\n try:\n bad_arm = survey.get_spiral_slice(track = \"fakeSpiral\")\n except KeyError:\n assert True\n else:\n assert False","def test_exists_true(self):\n self.assertTrue(SampleTemplate.exists(self.test_study.id))","def hasImageData(self,volumeNode):\n if not volumeNode:\n logging.debug('no volume node')\n return False\n if volumeNode.GetImageData() is None:\n logging.debug('no image data')\n return False\n return True"],"string":"[\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def isExist(data):\\n return True/False\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_count_no_spins(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Test the number of spins counted.\\n self.assertEqual(mol_res_spin.count_spins(), 0)\",\n \"def test_molecule_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the molecules.\\n i = 0\\n for molecule in mol_res_spin.molecule_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def exists(self, datadir):\\n return False\",\n \"def check_for_data():\\n if not (os.path.exists(ep.get_test_data_path()) or os.path.exists(ep.get_dbn_weight_path())):\\n return False\\n return True\",\n \"def is_version_data_existed(self):\\n # if exists, skip\\n # return \\n\\n return True\",\n \"def CheckForExistence(requested_data, available_data):\\n if requested_data is not None:\\n return 1 # The requested data exists.\\n elif available_data:\\n return -1 # The requested data does not exist.\\n else:\\n return 0 # No data exists at all.\",\n \"def testExists(self, mock_exists):\\n mock_exists.return_value = True\\n\\n self.assertTrue(\\n self.mr.exists\\n )\\n\\n mock_exists.assert_called_once_with(\\n os.path.join(self.directory, self.filename)\\n )\\n\\n mock_exists.return_value = False\\n\\n self.assertFalse(\\n self.mr.exists\\n )\",\n \"def datafolderexist(name):\\n folderpath = os.path.join(pathtofolder(), name)\\n return os.path.exists(folderpath)\",\n \"def file_exists(msl_data_path, filename):\\n return os.path.isfile(msl_data_path + filename)\",\n \"def exists():\\n check50.include(\\\"data\\\")\\n check50.exists(\\\"adventure.py\\\")\\n check50.exists(\\\"room.py\\\")\",\n \"def check_data_struct():\\n if not os.path.exists(PROJECT_ROOT+'/data'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data')\\n\\n if not os.path.exists(PROJECT_ROOT+'/data/CUB_200_2011'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/CUB_200_2011')\\n\\n if not os.path.exists(PROJECT_ROOT+'/data/segmentations'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/segmentations')\\n\\n if not os.path.exists(PROJECT_ROOT+'/data/attributes.txt'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/attributes.txt')\",\n \"def check_model_exists(ckpt):\\n expected_data = ckpt + \\\".data-00000-of-00001\\\"\\n return os.path.exists(expected_data)\",\n \"def test_return_single_residue_info(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_single_residue_info('1')\\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\\n res5 = mol_res_spin.return_single_residue_info('-5')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1, (1, None))\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2, (2, 'Glu'))\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4, (4, 'Pro'))\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5, (-5, None))\",\n \"def checkfolderdata(folder = 'datas'):\\n if datafolderexist(folder):\\n return True\\n else:\\n createdatafolder(folder)\\n checkfolderdata(folder)\",\n \"def exist(self):\",\n \"def test_exists_false(self):\\n self.assertFalse(PrepSample.exists('Not_a_Sample', self.prep_template))\",\n \"def check_file_existing(k_out, sphere_radius,full_path):\\n cwd = full_path\\n file_names = ['/T_ns_', '/Energy_', '/Distance-e-to-e_',\\n '/chain_on_iterations_']\\n\\n kout = f'{k_out:.3f}'\\n spr_rad = f'{sphere_radius:.3f}'\\n\\n current = \\\"kout_\\\" + kout + \\\"_\\\" + \\\"spr_rad_\\\" + spr_rad\\n for file_name in file_names:\\n #print (cwd + file_name + current + \\\".pkl\\\")\\n if not os.path.exists(cwd + file_name + current + \\\".pkl\\\"):\\n return False\\n return True\",\n \"def check_exist(self):\\n helper.RbdImageOperator._check_rbd_image(self.real_path)\",\n \"def data_available(dataset_name=None):\\r\\n for file_list in data_resources[dataset_name]['files']:\\r\\n for file in file_list:\\r\\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\\r\\n return False\\r\\n return True\",\n \"def test_narrative_data_missing(self, config_handler):\\n spec = Spec.from_dict(\\n {\\\"name\\\": \\\"homogeneity_coefficient\\\", \\\"unit\\\": \\\"percentage\\\", \\\"dtype\\\": \\\"float\\\"}\\n )\\n with raises(SmifDataNotFoundError):\\n config_handler.read_narrative_variant_data(\\\"does not exist\\\", spec)\",\n \"def test_exists(self):\\n self.assertTrue(bool(self.photo))\",\n \"def find_null(data, sub_reg):\\r\\n subreg_sqkm_data = data.loc[pd.IndexSlice[:, sub_reg, :], pd.IndexSlice['Sq Km']]\\r\\n if subreg_sqkm_data.isnull().values.any() == True:\\r\\n print(\\\"\\\\nSq km measurements are missing for:\\\")\\r\\n print(subreg_sqkm_data[subreg_sqkm_data.isnull()])\\r\\n else:\\r\\n print(\\\"\\\\nThere are no missing sq km values for this sub-region.\\\")\",\n \"def test_get_all_rides_if_exists_success(self):\\n res = self.client().get('api/v1/rides')\\n self.assertEqual(res.status_code, 200)\\n self.assertIn('Kutus', str(res.data))\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def exists(self):\\n\\t\\tif self.hasUdim:\\n\\t\\t\\treturn len( self.udimPaths ) != 0\\n\\t\\treturn super( textureFile, self ).exists\",\n \"def test_return_molecule(self):\\n\\n # Ask for a few molecules.\\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\\n\\n # Test the data of molecule 1.\\n self.assertEqual(mol1.name, 'Ap4Aase')\\n\\n # Test the data of molecule 2.\\n self.assertEqual(mol2.name, 'RNA')\",\n \"def data_ready(self) -> bool:\\n data_ready = ctypes.c_uint8()\\n Utils.check(VL53L1X_C_LIBRARY.VL53L1_GetMeasurementDataReady(self.dev, byref(data_ready)))\\n return data_ready.value != 0\",\n \"def check_dataset_exists(dataset):\\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\\n return result == 0\",\n \"def test_exists_false(self):\\n self.assertFalse(Sample.exists('Not_a_Sample', self.sample_template))\",\n \"def check_data_exist(data):\\n if data is not None:\\n if data.text is not None:\\n return True\\n return False\",\n \"def test_exists_true(self):\\n self.assertTrue(PrepSample.exists(self.sample_id, self.prep_template))\",\n \"def check_resource_exists(test_cma_creds, test_rma_url, path):\\n creds = test_cma_creds.split(\\\":\\\")\\n response = requests.get(\\n f\\\"{test_rma_url}/{path}\\\",\\n headers={\\\"Accept\\\": \\\"application/json\\\"},\\n auth=HTTPDigestAuth(creds[0], creds[1]),\\n )\\n return response.status_code == 200\",\n \"def datafileexist(filename):\\n filePath = os.path.join(pathtofolder(), \\\"datas\\\", filename)\\n fileFormat = '.csv'\\n return os.path.exists(f'{filePath+fileFormat}')\",\n \"def test_molecule_loop(self):\\n\\n # Loop over the molecules.\\n for mol in mol_res_spin.molecule_loop('#RNA'):\\n # Test the molecule name.\\n self.assertEqual(mol.name, 'RNA')\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)\",\n \"def check_data_exist(hdir):\\n cmd = 'ls ' + hdir + '*/* > ' + zspace\\n os.system(cmd)\\n with open(zspace, 'r') as f:\\n out = f.read()\\n mcf.rm_files(zspace)\\n\\n for name in ['dtf1', 'fov', 'bpix1', 'evt1', 'msk1', 'mtl1', 'std_dtfstat1', 'std_flt1', 'asol']:\\n mc = re.search(name, out)\\n if mc is None:\\n line = 'Some data files are missing and the re-process is terminated. Check: ' + hdir + '\\\\n'\\n with open(zspace, 'w') as fo:\\n fo.write(line)\\n\\n cmd = 'cat ' + zspace + ' | mailx -s \\\"Subject: hrc re-process failed\\\" tisobe@cfa.harvard.edu'\\n os.system(cmd)\\n\\n return False\\n\\n return True\",\n \"def has_data(self) -> bool:\\n raise NotImplementedError\",\n \"def test_get_available_file_path_exists(self, mock_uuid4):\\n mock_uuid4.side_effect = ['Voltaire', 'Franklin']\\n\\n directory = Path(__file__, '..').resolve()\\n taken_file = directory / 'Voltaire'\\n\\n taken_file.write_text('Common sense is not so common.')\\n\\n self.assertEqual(\\n self.mikla.get_available_file_path(directory),\\n str(directory / 'Franklin'),\\n )\\n\\n taken_file.unlink()\",\n \"def test_return_single_residue_info_fail(self):\\n\\n # Ask for a few residues.\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')\",\n \"def test_return_residue(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_residue(':1')\\n res2 = mol_res_spin.return_residue(selection=':2')\\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1.num, 1)\\n self.assertEqual(res1.name, None)\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2.num, 2)\\n self.assertEqual(res2.name, 'Glu')\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4.num, 4)\\n self.assertEqual(res4.name, 'Pro')\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5.num, -5)\\n self.assertEqual(res5.name, None)\\n self.assertEqual(res5.spin[1].name, 'N5')\",\n \"def testForExistence(self):\\n self.assertTrue(cached_list_logic.isCachedListExists('cached_list'))\\n self.assertFalse(cached_list_logic.isCachedListExists('none_existent'))\",\n \"def particleExists(*args, **kwargs)->bool:\\n pass\",\n \"def exists(sim):\\n return (sim['N'] > 0)\",\n \"def _check_data_valid(self):\\n\\n is_valid = (sum(~np.isnan(self.data).flatten()) > 0 and self.data.flatten().sum() != 0)\\n if not is_valid:\\n raise FITSException(f\\\"No data in {self.survey}\\\")\",\n \"def test_existence_checking(self):\\n params = [f'2010-{num:0>2}' for num in range(1, 13)] # all month of 2010\\n for month in params:\\n with self.assertRaises(ValueError) as cm: # ValueError should be raised with proper message\\n download_data(month)\\n self.assertEqual(f'Dataset from {month} cannot be found on lichess.org', cm.exception.args[0], msg=month)\\n # check if error message was as expected\",\n \"def test_exists_true(self):\\n self.assertTrue(Sample.exists(self.sample_id, self.sample_template))\",\n \"def object_exists(self, fname):\\n return False\",\n \"def check_path(data_pointer, log, msg):\\n if not os.path.exists(data_pointer):\\n log.debug(msg)\\n return False\\n else:\\n return data_pointer\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.data_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.data_dir))\\n if not osp.exists(self.raw_mat_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.raw_mat_path))\\n if not osp.exists(self.split_new_det_mat_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.split_new_det_mat_path))\\n if not osp.exists(self.split_new_lab_mat_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.split_new_lab_mat_path))\",\n \"def check_helpers(self):\\n paths = self.get_helper_out_paths()\\n\\n for p in paths:\\n full_path = p + \\\".data-00000-of-00001\\\"\\n file = Path(full_path)\\n if not file.exists():\\n return False\\n\\n return True\",\n \"def _exists(cursor, table, data):\\n cursor.execute('SELECT 1 FROM {} WHERE ({}) = ({})'.format(table, *_query_fields(data)), data)\\n return bool(cursor.fetchone())\",\n \"def object_exists(self, fname):\\n return True\",\n \"def test_return_spin_pipe_fail(self):\\n\\n # Try to get a spin from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')\",\n \"def exists(self):\\n return os.path.exists(self.sensorpath)\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n logging.debug('hasImageData failed: no volume node')\\n return False\\n if volumeNode.GetImageData() is None:\\n logging.debug('hasImageData failed: no image data in volume node')\\n return False\\n return True\",\n \"def test_molecule_loop_no_selection(self):\\n\\n # Molecule data.\\n name = ['Ap4Aase', 'RNA']\\n\\n # Loop over the molecules.\\n i = 0\\n for mol in mol_res_spin.molecule_loop():\\n # Test the molecule names.\\n self.assertEqual(mol.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)\",\n \"def exists():\\n\\treturn os.path.exists('data/strmr.db')\",\n \"def resultExist(probName,algoName,fitName,inst,s,c,n,k,q,w,m,t,e):\\n if probName == 'NKQ':\\n nameOfF = './result/'+probName+'-'+algoName+'-F'+fitName+'-M'+m+'-I'+str(inst)+'-S'+str(s)+'-W'+str(w)+'-N'+str(n)+'-K'+str(k)+'-C'+str(c)+'-Q'+str(q)+'-T'+str(t)+'-E'+str(e)+'.txt'\\n elif probName == 'NK' or probName == 'NonNK':\\n nameOfF = './result/'+probName+'-'+algoName+'-F'+fitName+'-C'+str(c)+'-I'+str(inst)+'-S'+str(s)+'-W'+str(w)+'-N'+str(n)+'-K'+str(k)+'-E'+str(e)+'.txt'\\n\\n if os.path.isfile(nameOfF)==True:\\n print nameOfF, 'exists!!!'\\n return os.path.isfile(nameOfF)\",\n \"def id_exists(test_name):\\n result_json = None\\n try:\\n with open(robot_dir + \\\"/output/results/{}.json\\\".format(test_name.replace(' ', ''))) as result_file:\\n result_json = json.load(result_file)\\n except:\\n print(\\\"Failed to open the result json\\\")\\n return False\\n #look for values NEW_ASSOC, NEW_PROP1, NEW_PROP2\\n print(result_json)\\n if 6 == 6:\\n return True\\n return \\\"Length is not 6\\\"\",\n \"def test_exists(self):\\n self.assertTrue(os.path.exists(__file__) == self._system.exists(__file__))\",\n \"def is_empty(self):\\n for key, dataset in self.datasets.items():\\n try:\\n has_data = dataset.has_data()\\n except MFDataException as mfde:\\n raise MFDataException(\\n mfdata_except=mfde,\\n model=self._container_package.model_name,\\n package=self._container_package._get_pname(),\\n message=\\\"Error occurred while verifying\\\"\\n ' data of dataset \\\"{}\\\" in block '\\n '\\\"{}\\\"'.format(dataset.structure.name, self.structure.name),\\n )\\n\\n if has_data is not None and has_data:\\n return False\\n return True\",\n \"def test_exists(self):\\n d = self._examineOrSelect()\\n self._response(b'* 3 EXISTS')\\n self.assertEqual(\\n self.successResultOf(d),\\n {'READ-WRITE': False, 'EXISTS': 3})\",\n \"def _check_data_point(cube, metadata):\\n point_index = []\\n\\n for dim_length in cube.shape:\\n point_index.append(int(random.random() * dim_length))\\n\\n point_index = tuple(point_index)\\n\\n try:\\n point_cube = cube[point_index]\\n _data_point = point_cube.data\\n except Exception:\\n msg = 'Unable to extract data point {} from file: {}'.format(\\n point_index, metadata['basename'])\\n raise FileValidationError(msg)\\n else:\\n return True\",\n \"def test_data_source_soaps_id_exists_get(self):\\n pass\",\n \"def object_exists(self, fname):\\n return self.object_exists\",\n \"def test_find(self):\\r\\n input_dir = None\\r\\n try:\\r\\n input_dir = tempfile.mkdtemp()\\r\\n input_file = 'conpot/tests/data/VOGON-POEM-MIB.mib'\\r\\n shutil.copy(input_file, input_dir)\\r\\n available_mibs = find_mibs([input_dir])\\r\\n self.assertIn('VOGON-POEM-MIB', available_mibs)\\r\\n finally:\\r\\n shutil.rmtree(input_dir)\",\n \"def exists(dtype, name, rootdir=None):\\n return FreezableAPI.to_slug(dtype,name) in FreezableAPI.datasets(rootdir=rootdir)\",\n \"def check_file_exist(self):\\n return False\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n logging.debug('hasImageData failed: no volume node')\\n return False\\n return True\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.data_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.data_dir))\\n if not osp.exists(self.split_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.split_dir))\",\n \"def _CheckFileExistsWithData(self, logs, graph):\\n self.assertTrue(graph in logs, 'File %s was not output.' % graph)\\n self.assertTrue(logs[graph], 'File %s did not contain data.' % graph)\",\n \"def assert_data_fragments_correct(self) -> bool:\\n read_path = Path(os.environ[\\\"DATA_PATH\\\"]) / \\\"fragments\\\"\\n if not read_path.exists():\\n return False\\n bin_images = [img for img in read_path.iterdir() if \\\"binarized\\\" in img.name]\\n if len(bin_images) == 0:\\n return False\\n return True\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n print('no volume node')\\n return False\\n if volumeNode.GetImageData() == None:\\n print('no image data')\\n return False\\n return True\",\n \"def __check_array__(self):\\n if self.data_array is None:\\n mess = 'No data array is present, please load before attempting to create XYZ array.'\\n if isinstance(self.mess_inst, MessagesGUI):\\n self.mess_inst.message(mess)\\n else:\\n print(mess)\\n return False\\n else:\\n return True\",\n \"def has_error(self):\\r\\n return self._arm.has_error\",\n \"def is_file_exists(self):\\n pass\",\n \"def exists(self):\\r\\n return os.path.exists(self.full_path)\",\n \"def test_output_exists():\\n global out_dir, cor_dir\\n assert(path.exists(path.join(out_dir, 'oshea_similarity.json')))\",\n \"def test_full_function(self):\\n\\t\\t# Import the rubric\\n\\t\\ttemplate_data = pd.read_csv('tests/statcast_spin/live_Darvish_July2019_test.csv').round(SIG_DIG)\\n\\n\\t\\t# Run the method in question\\n\\t\\tdf = spin.statcast_pitcher_spin(start_dt='2019-07-01', end_dt='2019-07-31', player_id=506433)\\n\\n\\t\\t# Columns needed to be checked\\n\\t\\ttarget_columns = ['Mx', 'Mz', 'phi', 'theta']\\n\\n\\t\\tfor column in target_columns:\\n\\t\\t\\tlogging.info(\\\"Begin testing on {}\\\".format(column))\\n\\n\\n\\t\\t\\tif column in ['Mz']:\\n\\t\\t\\t# Almost equal assertion is necessary for small differences that arise after consecutive calculations\\n\\t\\t\\t\\tself.assertTrue(self.compare_almost_equal(df, template_data, column))\\n\\n\\t\\t\\telse:\\n\\t\\t\\t\\tself.assertTrue(self.compare_columns(df, template_data, column))\\n\\n\\t\\t\\tlogging.info(\\\"{} passed\\\".format(df, template_data, column))\\n\\n\\n\\t\\tlogging.info(\\\"All tests completed\\\")\",\n \"def check_for_residue_existance(self):\\n if not self.pose.total_residue():\\n print \\\"No pose Loaded.\\\"\\n return False\\n\\n if not self.current_chain.get() or not self.current_residue.get():\\n print \\\"Chain or residue not set\\\"\\n return False\\n\\n current_region = self.current_residue.get().split(\\\":\\\")\\n if len(current_region)>1:\\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\\n\\n\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\\n print \\\"Region not found in pose\\\"\\n return False\\n else:\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\\n\\n print \\\"Residue not found in pose\\\"\\n return False\\n\\n #If everythig is good then:\\n return True\",\n \"def pvExistTest(self, context, addr, fullname):\\n if fullname in self.pcas_manager.pvf:\\n return pcaspy.pverExistsHere\\n else:\\n return pcaspy.pverDoesNotExistHere\",\n \"def _loaded_data(self):\\n try:\\n dsize = [int(d) for d\\n in self.run('fits size', via='get').split()]\\n except (ValueError, TypeError, AttributeError) as err:\\n log.debug(f' FITS size error: {err}')\\n return False\\n else:\\n if 0 in dsize:\\n return False\\n else:\\n return True\",\n \"def has_data(self):\\n return len(self.data) > 0\",\n \"def test_postrun_nodata(self):\\n\\n from scripts.create_pointer_file import postrun\\n\\n with self.assertRaises(RuntimeError) as raised_excep:\\n postrun(projectFile=\\\"/tmp/myproject.prproj\\\",projectFileExtension=\\\".prproj\\\",\\n dataCache={'invalidkey':\\\"/path/to/my/assets\\\"})\\n self.assertEqual(str(raised_excep.exception),\\\"No created_asset_folder in data cache. This postrun must depend on make_asset_folder\\\")\",\n \"def test_exists_false(self):\\n self.assertFalse(PrepTemplate.exists(2))\",\n \"def task_validate_rawdata_file(pk):\\n\\n # init and checks\\n valid = False\\n logger = Logger.get_logger(StringIO())\\n try:\\n df = Data.objects.get(id=pk)\\n assert df.kind == 'rd_file'\\n tr = df.content_object\\n except:\\n logger.log('ERROR')\\n return valid\\n\\n try:\\n logger.log('looking at raw data file with pk: %s' % pk)\\n rd, sr = read_hdf5_arc(df.file.path)\\n logger.log('found rd_file: %s' % df.name)\\n len_rd_sec = rd.shape[0] / sr\\n logger.log('found data in %d channels, for %d sec' % (\\n rd.shape[1], len_rd_sec))\\n\\n # TODO: more checks?\\n\\n logger.log('rd_file passed all checks')\\n valid = True\\n except Exception, ex:\\n logger.log('ERROR: rawdata file check: %s' % str(ex))\\n finally:\\n df.save()\\n tr.valid_rd_log = logger.get_content()\\n tr.save()\\n return valid\",\n \"def check_if_file_exists(self, sensor_id:str, name:str)->str:\\n ret_value = \\\"\\\"\\n file_name = '%s/%s.*.%s.json' % (self.generate_data_prep, sensor_id, name)\\n try: \\n ret_value = glob.glob(file_name)\\n except Exception as e:\\n print(\\\"OSError - Failed top get file (%s) - %s\\\" % (file_name, e))\\n ret_value = False \\n \\n if ret_value != False and len(ret_value) > 0: \\n ret_value = ret_value[0]\\n\\n return ret_value\",\n \"def test_no_track_data_error():\\n try:\\n bad_arm = survey.get_spiral_slice(track = \\\"fakeSpiral\\\")\\n except KeyError:\\n assert True\\n else:\\n assert False\",\n \"def test_exists_true(self):\\n self.assertTrue(SampleTemplate.exists(self.test_study.id))\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n logging.debug('no volume node')\\n return False\\n if volumeNode.GetImageData() is None:\\n logging.debug('no image data')\\n return False\\n return True\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.86498624","0.8171099","0.8008126","0.7832109","0.7612232","0.74061805","0.7374406","0.64998114","0.6273386","0.6179472","0.5896734","0.58264905","0.5745269","0.57218933","0.57177144","0.5715544","0.5627069","0.56219554","0.56199694","0.55988914","0.54542","0.5446139","0.5423683","0.5387568","0.53835005","0.5351986","0.5350013","0.5349692","0.53491414","0.5343103","0.5305887","0.52817917","0.5281655","0.5277142","0.5261368","0.5231536","0.5229751","0.5221484","0.52202","0.5211619","0.52114695","0.51899457","0.518197","0.51725423","0.51655143","0.51630193","0.5161288","0.5157089","0.5152774","0.5151078","0.5150458","0.5141715","0.51397574","0.5136175","0.5111072","0.5102071","0.50992095","0.50977916","0.50967735","0.5091617","0.5083925","0.5080936","0.50720173","0.5058063","0.505798","0.5056147","0.5052945","0.504826","0.50395226","0.5038068","0.5037259","0.50264335","0.5021877","0.5020524","0.50157404","0.5010806","0.50059164","0.50032103","0.4995873","0.49920627","0.49812838","0.4979854","0.4977381","0.49689433","0.49654397","0.49617773","0.49544418","0.49530897","0.4952389","0.49511164","0.49510756","0.49466133","0.49372226","0.49356672","0.492861","0.49282396","0.4926251","0.4925436","0.49179542","0.4916656"],"string":"[\n \"0.86498624\",\n \"0.8171099\",\n \"0.8008126\",\n \"0.7832109\",\n \"0.7612232\",\n \"0.74061805\",\n \"0.7374406\",\n \"0.64998114\",\n \"0.6273386\",\n \"0.6179472\",\n \"0.5896734\",\n \"0.58264905\",\n \"0.5745269\",\n \"0.57218933\",\n \"0.57177144\",\n \"0.5715544\",\n \"0.5627069\",\n \"0.56219554\",\n \"0.56199694\",\n \"0.55988914\",\n \"0.54542\",\n \"0.5446139\",\n \"0.5423683\",\n \"0.5387568\",\n \"0.53835005\",\n \"0.5351986\",\n \"0.5350013\",\n \"0.5349692\",\n \"0.53491414\",\n \"0.5343103\",\n \"0.5305887\",\n \"0.52817917\",\n \"0.5281655\",\n \"0.5277142\",\n \"0.5261368\",\n \"0.5231536\",\n \"0.5229751\",\n \"0.5221484\",\n \"0.52202\",\n \"0.5211619\",\n \"0.52114695\",\n \"0.51899457\",\n \"0.518197\",\n \"0.51725423\",\n \"0.51655143\",\n \"0.51630193\",\n \"0.5161288\",\n \"0.5157089\",\n \"0.5152774\",\n \"0.5151078\",\n \"0.5150458\",\n \"0.5141715\",\n \"0.51397574\",\n \"0.5136175\",\n \"0.5111072\",\n \"0.5102071\",\n \"0.50992095\",\n \"0.50977916\",\n \"0.50967735\",\n \"0.5091617\",\n \"0.5083925\",\n \"0.5080936\",\n \"0.50720173\",\n \"0.5058063\",\n \"0.505798\",\n \"0.5056147\",\n \"0.5052945\",\n \"0.504826\",\n \"0.50395226\",\n \"0.5038068\",\n \"0.5037259\",\n \"0.50264335\",\n \"0.5021877\",\n \"0.5020524\",\n \"0.50157404\",\n \"0.5010806\",\n \"0.50059164\",\n \"0.50032103\",\n \"0.4995873\",\n \"0.49920627\",\n \"0.49812838\",\n \"0.4979854\",\n \"0.4977381\",\n \"0.49689433\",\n \"0.49654397\",\n \"0.49617773\",\n \"0.49544418\",\n \"0.49530897\",\n \"0.4952389\",\n \"0.49511164\",\n \"0.49510756\",\n \"0.49466133\",\n \"0.49372226\",\n \"0.49356672\",\n \"0.492861\",\n \"0.49282396\",\n \"0.4926251\",\n \"0.4925436\",\n \"0.49179542\",\n \"0.4916656\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.91275215"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81475,"cells":{"query":{"kind":"string","value":"Determine if moleculeresiduespin data exists (with data for a single molecule). The function tested is pipe_control.mol_res_spin.exists_mol_res_spin_data()."},"document":{"kind":"string","value":"def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def isExist(data):\n return True/False","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def CheckForExistence(requested_data, available_data):\n if requested_data is not None:\n return 1 # The requested data exists.\n elif available_data:\n return -1 # The requested data does not exist.\n else:\n return 0 # No data exists at all.","def datafolderexist(name):\n folderpath = os.path.join(pathtofolder(), name)\n return os.path.exists(folderpath)","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def exists(self, datadir):\n return False","def hasResidue(self, resname):\n if resname in self.map:\n return 1\n else:\n return 0","def has_data(self, fragment, number):\n if fragment in self.mdv:\n if number in self.mdv[fragment]:\n return True\n return False","def has_data(self) -> bool:\n raise NotImplementedError","def test_return_single_residue_info(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_single_residue_info('1')\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\n res5 = mol_res_spin.return_single_residue_info('-5')\n\n # Test the data of residue 1.\n self.assertEqual(res1, (1, None))\n\n # Test the data of residue 2.\n self.assertEqual(res2, (2, 'Glu'))\n\n # Test the data of residue 4.\n self.assertEqual(res4, (4, 'Pro'))\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5, (-5, None))","def check_for_residue_existance(self):\n if not self.pose.total_residue():\n print \"No pose Loaded.\"\n return False\n\n if not self.current_chain.get() or not self.current_residue.get():\n print \"Chain or residue not set\"\n return False\n\n current_region = self.current_residue.get().split(\":\")\n if len(current_region)>1:\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\n\n\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\n print \"Region not found in pose\"\n return False\n else:\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\n\n print \"Residue not found in pose\"\n return False\n\n #If everythig is good then:\n return True","def file_exists(msl_data_path, filename):\n return os.path.isfile(msl_data_path + filename)","def is_version_data_existed(self):\n # if exists, skip\n # return \n\n return True","def has_data(self):\n return self._data is not None","def has_data(self, time, fragment, number):\n if time in self.mdvtc.keys():\n if fragment in self.mdvtc[time].mdv.keys():\n if number in self.mdvtc[time].mdv[fragment].keys():\n return True\n return False","def has_data(self) -> bool:\n return bool(self.data)","def has_data(self):\n return len(self.data) > 0","def has_data(self):\n\n return self._data is not None","def has_data(self):\n\n return self._data is not None","def exists(self):\n\t\tif self.hasUdim:\n\t\t\treturn len( self.udimPaths ) != 0\n\t\treturn super( textureFile, self ).exists","def checkExistence(idMeta):\n # XXX add for diaries\n sqlq = \"\"\"\n SELECT dt\n FROM Electricity_10min\n WHERE `Meta_idMeta` = {}\n LIMIT 1;\n \"\"\".format(idMeta)\n try:\n result = mdb.getSQL(sqlq)[0]\n if (result):\n return True\n except:\n return False","def _exists(cursor, table, data):\n cursor.execute('SELECT 1 FROM {} WHERE ({}) = ({})'.format(table, *_query_fields(data)), data)\n return bool(cursor.fetchone())","def test_count_no_spins(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 0)","def data_ready(self) -> bool:\n data_ready = ctypes.c_uint8()\n Utils.check(VL53L1X_C_LIBRARY.VL53L1_GetMeasurementDataReady(self.dev, byref(data_ready)))\n return data_ready.value != 0","def check_data_exist(data):\n if data is not None:\n if data.text is not None:\n return True\n return False","def datafileexist(filename):\n filePath = os.path.join(pathtofolder(), \"datas\", filename)\n fileFormat = '.csv'\n return os.path.exists(f'{filePath+fileFormat}')","def exists(self, number):\n\t\tslotIDList = [s.id for s in self.slotList]\n\t\ttry:\n\t\t\tindex = slotIDList.index(number)\n\t\t\treturn True\n\t\texcept ValueError:\n\t\t\treturn False\n\t\treturn False","def data_available(dataset_name=None):\r\n for file_list in data_resources[dataset_name]['files']:\r\n for file in file_list:\r\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\r\n return False\r\n return True","def object_exists(self, name: str):\n file_path = self.__get_file_path(name)\n return os.path.exists(file_path)","def test_return_molecule(self):\n\n # Ask for a few molecules.\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\n\n # Test the data of molecule 1.\n self.assertEqual(mol1.name, 'Ap4Aase')\n\n # Test the data of molecule 2.\n self.assertEqual(mol2.name, 'RNA')","def check_dataset_exists(dataset):\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\n return result == 0","def exists(dtype, name, rootdir=None):\n return FreezableAPI.to_slug(dtype,name) in FreezableAPI.datasets(rootdir=rootdir)","def exists(self):\n return os.path.exists(self.sensorpath)","def check_for_data():\n if not (os.path.exists(ep.get_test_data_path()) or os.path.exists(ep.get_dbn_weight_path())):\n return False\n return True","def test_molecule_loop(self):\n\n # Loop over the molecules.\n for mol in mol_res_spin.molecule_loop('#RNA'):\n # Test the molecule name.\n self.assertEqual(mol.name, 'RNA')\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)","def exists(sim):\n return (sim['N'] > 0)","def exists(self) -> bool:\n try:\n result = self.get()\n except KeyError:\n return False\n return True","def hasImageData(self,volumeNode):\n if not volumeNode:\n logging.debug('hasImageData failed: no volume node')\n return False\n if volumeNode.GetImageData() is None:\n logging.debug('hasImageData failed: no image data in volume node')\n return False\n return True","def is_empty(self):\n for key, dataset in self.datasets.items():\n try:\n has_data = dataset.has_data()\n except MFDataException as mfde:\n raise MFDataException(\n mfdata_except=mfde,\n model=self._container_package.model_name,\n package=self._container_package._get_pname(),\n message=\"Error occurred while verifying\"\n ' data of dataset \"{}\" in block '\n '\"{}\"'.format(dataset.structure.name, self.structure.name),\n )\n\n if has_data is not None and has_data:\n return False\n return True","def exists(self, name):\n assert name, \"Must input a valid dataset name.\"\n return name in self.manager.data[\"dataset\"]","def is_data_run(info, runinfo):\n this_run_in_runinfo = runinfo[\n (runinfo.fNight==info[\"night_int\"])&\n (runinfo.fRunID==info[\"run\"])\n ]\n return len(this_run_in_runinfo) > 0 and this_run_in_runinfo.iloc[0].fRunTypeKey == 1","def is_data_present(self, cycle: int, bus_item: BusItem) -> bool:\n buffer = self.get_cycle_buffer(cycle)\n if self.component_subtype == \"PEGB\":\n return False\n #print(buffer)\n # for pe_id in buffer:\n # pe_buffer = buffer[pe_id]\n # # # TODO ad-hoc\n # # if isinstance(pe_buffer, deque):\n # # return False\n # #print(pe_buffer)\n #\n # pe_read_buffer = pe_buffer[\"read\"]\n # #print(pe_read_buffer)\n # for data in pe_read_buffer:\n # if data == bus_item:\n # return True\n elif self.component_subtype == \"PENB\":\n read_buffer = buffer[\"read\"]\n for entry in read_buffer:\n if entry == bus_item:\n return True\n else:\n for data in buffer:\n if data == bus_item:\n return True\n return False","def exists(self):\n try:\n self.world.find(self.ehandle)\n except KeyError:\n return False\n else:\n return True","def has_mask(mask_name, path=None, data=None):\n if path is None and data is None:\n raise ValueError(\"Mask file not provided.\")\n if path:\n with open(path, 'r') as file:\n data = json.load(file)\n \n for inx, obj in enumerate(data[\"objects\"]):\n if obj['classTitle'] == mask_name:\n return inx\n \n return False","def check_exist(self):\n helper.RbdImageOperator._check_rbd_image(self.real_path)","def check_data_struct():\n if not os.path.exists(PROJECT_ROOT+'/data'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data')\n\n if not os.path.exists(PROJECT_ROOT+'/data/CUB_200_2011'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/CUB_200_2011')\n\n if not os.path.exists(PROJECT_ROOT+'/data/segmentations'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/segmentations')\n\n if not os.path.exists(PROJECT_ROOT+'/data/attributes.txt'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/attributes.txt')","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def is_present(self):\n try:\n self.read_binary(0, 2)\n return True\n except:\n return False","def has_data(self, fit_id, species_id, start=None, stop=None):\n if not (fit_id in self.raw_results and species_id in\\\n self.raw_results[fit_id]):\n return False\n if all([isinstance(x, datetime) for x in [start, stop]]):\n ts = self.raw_results[fit_id][\"start\"]\n if not any([start < x < stop for x in ts]):\n return False\n return True","def particleExists(*args, **kwargs)->bool:\n pass","def is_section_exist(self, section_name: str) -> bool:\n success = False\n try:\n self._vault_api.read_secret(path=section_name.upper(), mount_point=self.mount_point)\n success = True\n except InvalidPath:\n pass\n return success","def hasImageData(self,volumeNode):\n if not volumeNode:\n logging.debug('hasImageData failed: no volume node')\n return False\n return True","def check_model_exists(ckpt):\n expected_data = ckpt + \".data-00000-of-00001\"\n return os.path.exists(expected_data)","def find_null(data, sub_reg):\r\n subreg_sqkm_data = data.loc[pd.IndexSlice[:, sub_reg, :], pd.IndexSlice['Sq Km']]\r\n if subreg_sqkm_data.isnull().values.any() == True:\r\n print(\"\\nSq km measurements are missing for:\")\r\n print(subreg_sqkm_data[subreg_sqkm_data.isnull()])\r\n else:\r\n print(\"\\nThere are no missing sq km values for this sub-region.\")","def object_exists(self, fname):\n return self.object_exists","def checkfolderdata(folder = 'datas'):\n if datafolderexist(folder):\n return True\n else:\n createdatafolder(folder)\n checkfolderdata(folder)","def hasImageData(self,volumeNode):\n if not volumeNode:\n logging.debug('no volume node')\n return False\n if volumeNode.GetImageData() is None:\n logging.debug('no image data')\n return False\n return True","def data(self):\n file_name = join(PARENT_BASE_DIR, '.files', 'data.data.json')\n if isfile(file_name):\n debug(f'{file_name} file is exist.')\n debug(f'try for load {file_name} file ->->->->->->->->->->')\n start_load_file = time()\n with open(file_name, 'r', encoding='utf-8')as file:\n data = file.read()\n data = loads(data)\n debug(f'load file - [runtime: {time() - start_load_file}] <-<-<-<-<-<-<-<-<-<-')\n return data, 'data exist.'\n else:\n debug(f'{file_name} file is not exist.')\n return None, 'data not exist in \"base directory/.files/data.data.json\"'","def exists():\n\treturn os.path.exists('data/strmr.db')","def IndexExists(self, arg0: 'unsigned long long') -> \"bool\":\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF3GQEULLULLBBT_IndexExists(self, arg0)","def hasImageData(self,volumeNode):\n if not volumeNode:\n print('no volume node')\n return False\n if volumeNode.GetImageData() == None:\n print('no image data')\n return False\n return True","def verify_object(self, data):\n rv = self.get(data[self.id_field])\n result = not is_404(rv)\n if result:\n for key, value in data:\n if not in_response(rv, value):\n return False\n return result","def check_name_in_file(name_to_check, data):\r\n if name_to_check in data:\r\n return True\r\n return False","def check_file_existing(k_out, sphere_radius,full_path):\n cwd = full_path\n file_names = ['/T_ns_', '/Energy_', '/Distance-e-to-e_',\n '/chain_on_iterations_']\n\n kout = f'{k_out:.3f}'\n spr_rad = f'{sphere_radius:.3f}'\n\n current = \"kout_\" + kout + \"_\" + \"spr_rad_\" + spr_rad\n for file_name in file_names:\n #print (cwd + file_name + current + \".pkl\")\n if not os.path.exists(cwd + file_name + current + \".pkl\"):\n return False\n return True","def exists(self):\n f = os.path.join(pth, '..', 'static/data', self.filename)\n return os.path.isfile(f)","def exist(self):","def has_error(self):\r\n return self._arm.has_error","def exists(self):\r\n return os.path.exists(self.full_path)","def hasImageData(self,volumeNode):\n if not volumeNode:\n logging.debug('hasImageData failed: no volume node')\n return False\n if volumeNode.GetImageData() is None:\n logging.debug('hasImageData failed: no image data in volume node')\n return False\n return True","def exists (self, uuid):\n return self.read (uuid) is not None","def test_molecule_loop_no_selection(self):\n\n # Molecule data.\n name = ['Ap4Aase', 'RNA']\n\n # Loop over the molecules.\n i = 0\n for mol in mol_res_spin.molecule_loop():\n # Test the molecule names.\n self.assertEqual(mol.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)","def _check_data_point(cube, metadata):\n point_index = []\n\n for dim_length in cube.shape:\n point_index.append(int(random.random() * dim_length))\n\n point_index = tuple(point_index)\n\n try:\n point_cube = cube[point_index]\n _data_point = point_cube.data\n except Exception:\n msg = 'Unable to extract data point {} from file: {}'.format(\n point_index, metadata['basename'])\n raise FileValidationError(msg)\n else:\n return True","def user_exists(self,unique_ID):\n\t\ttry:\n\t\t\tself.data[unique_ID]\n\t\texcept KeyError:\n\t\t\treturn False\n\t\telse:\n\t\t\treturn True","def object_exists(self, fname):\n return False","def test_is_in_ring(self):\n molecule = Molecule.from_smiles(\"c1ccccc1\")\n\n for atom in molecule.atoms:\n if atom.atomic_number == 6:\n assert atom.is_in_ring()\n\n for bond in molecule.bonds:\n if 1 in (bond.atom1.atomic_number, bond.atom2.atomic_number):\n continue\n assert bond.is_in_ring()","def isRenderable(data):\n return data.find(\"<molecule\") != -1 and data.find(\"<atom\") != -1","def check_if_file_exists(self, sensor_id:str, name:str)->str:\n ret_value = \"\"\n file_name = '%s/%s.*.%s.json' % (self.generate_data_prep, sensor_id, name)\n try: \n ret_value = glob.glob(file_name)\n except Exception as e:\n print(\"OSError - Failed top get file (%s) - %s\" % (file_name, e))\n ret_value = False \n \n if ret_value != False and len(ret_value) > 0: \n ret_value = ret_value[0]\n\n return ret_value","def IndexExists(self, arg0: 'unsigned long long') -> \"bool\":\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF2GQEULLULLBBT_IndexExists(self, arg0)","def object_exists(self, fname):\n return True","def has_data(self, *args, **kwargs):\n return False","def exists(self, data):\n return data in self.__stack","def contains(self, seq_nr: str) -> bool:\n return bool(self.__data.get(seq_nr))","def exists(self):\r\n return bool(self.bucket.lookup(self.name))","def exists(self, name):\n full_path = self.path(name)\n return self.__volume.exists(full_path)","def exists():\n check50.include(\"data\")\n check50.exists(\"adventure.py\")\n check50.exists(\"room.py\")","def assert_data_fragments_correct(self) -> bool:\n read_path = Path(os.environ[\"DATA_PATH\"]) / \"fragments\"\n if not read_path.exists():\n return False\n bin_images = [img for img in read_path.iterdir() if \"binarized\" in img.name]\n if len(bin_images) == 0:\n return False\n return True","def exist(self):\n return self.file_path.exists()","def test_return_residue(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_residue(':1')\n res2 = mol_res_spin.return_residue(selection=':2')\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\n\n # Test the data of residue 1.\n self.assertEqual(res1.num, 1)\n self.assertEqual(res1.name, None)\n\n # Test the data of residue 2.\n self.assertEqual(res2.num, 2)\n self.assertEqual(res2.name, 'Glu')\n\n # Test the data of residue 4.\n self.assertEqual(res4.num, 4)\n self.assertEqual(res4.name, 'Pro')\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5.num, -5)\n self.assertEqual(res5.name, None)\n self.assertEqual(res5.spin[1].name, 'N5')","def check_wheel_integrity(data, re_encoding='X1', enc_res=None, **_):\n if isinstance(re_encoding, str):\n re_encoding = int(re_encoding[-1])\n # The expected difference between samples in the extracted units\n resolution = 1 / (enc_res or ephys_fpga.WHEEL_TICKS\n ) * np.pi * 2 * ephys_fpga.WHEEL_RADIUS_CM / re_encoding\n # We expect the difference of neighbouring positions to be close to the resolution\n pos_check = np.abs(np.diff(data['wheel_position']))\n # Timestamps should be strictly increasing\n ts_check = np.diff(data['wheel_timestamps']) <= 0.\n metric = pos_check + ts_check.astype(float) # all values should be close to zero\n passed = metric < 1.5 * resolution\n return metric, passed","def _loaded_data(self):\n try:\n dsize = [int(d) for d\n in self.run('fits size', via='get').split()]\n except (ValueError, TypeError, AttributeError) as err:\n log.debug(f' FITS size error: {err}')\n return False\n else:\n if 0 in dsize:\n return False\n else:\n return True","def _check_cell_measure_point(cfreader, metadata):\n cell_measure = None\n\n for cf_group in cfreader.cf_group.values():\n if cf_group.cf_name == metadata['cmor_name']:\n cell_measure = cf_group\n break\n\n if not cell_measure:\n msg = ('Unable to find cell measure in cfreader for variable {}'.\n format(metadata['cmor_name']))\n raise FileValidationError(msg)\n\n point_index = []\n for dim_length in cell_measure.cf_data.shape:\n point_index.append(random.randint(0, dim_length - 1))\n\n try:\n _data_point = cell_measure.cf_data[tuple(point_index)]\n except Exception:\n msg = 'Unable to extract data point {} from file: {}'.format(\n point_index, metadata['basename'])\n raise FileValidationError(msg)\n else:\n return True"],"string":"[\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def isExist(data):\\n return True/False\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_molecule_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the molecules.\\n i = 0\\n for molecule in mol_res_spin.molecule_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def CheckForExistence(requested_data, available_data):\\n if requested_data is not None:\\n return 1 # The requested data exists.\\n elif available_data:\\n return -1 # The requested data does not exist.\\n else:\\n return 0 # No data exists at all.\",\n \"def datafolderexist(name):\\n folderpath = os.path.join(pathtofolder(), name)\\n return os.path.exists(folderpath)\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def exists(self, datadir):\\n return False\",\n \"def hasResidue(self, resname):\\n if resname in self.map:\\n return 1\\n else:\\n return 0\",\n \"def has_data(self, fragment, number):\\n if fragment in self.mdv:\\n if number in self.mdv[fragment]:\\n return True\\n return False\",\n \"def has_data(self) -> bool:\\n raise NotImplementedError\",\n \"def test_return_single_residue_info(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_single_residue_info('1')\\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\\n res5 = mol_res_spin.return_single_residue_info('-5')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1, (1, None))\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2, (2, 'Glu'))\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4, (4, 'Pro'))\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5, (-5, None))\",\n \"def check_for_residue_existance(self):\\n if not self.pose.total_residue():\\n print \\\"No pose Loaded.\\\"\\n return False\\n\\n if not self.current_chain.get() or not self.current_residue.get():\\n print \\\"Chain or residue not set\\\"\\n return False\\n\\n current_region = self.current_residue.get().split(\\\":\\\")\\n if len(current_region)>1:\\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\\n\\n\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\\n print \\\"Region not found in pose\\\"\\n return False\\n else:\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\\n\\n print \\\"Residue not found in pose\\\"\\n return False\\n\\n #If everythig is good then:\\n return True\",\n \"def file_exists(msl_data_path, filename):\\n return os.path.isfile(msl_data_path + filename)\",\n \"def is_version_data_existed(self):\\n # if exists, skip\\n # return \\n\\n return True\",\n \"def has_data(self):\\n return self._data is not None\",\n \"def has_data(self, time, fragment, number):\\n if time in self.mdvtc.keys():\\n if fragment in self.mdvtc[time].mdv.keys():\\n if number in self.mdvtc[time].mdv[fragment].keys():\\n return True\\n return False\",\n \"def has_data(self) -> bool:\\n return bool(self.data)\",\n \"def has_data(self):\\n return len(self.data) > 0\",\n \"def has_data(self):\\n\\n return self._data is not None\",\n \"def has_data(self):\\n\\n return self._data is not None\",\n \"def exists(self):\\n\\t\\tif self.hasUdim:\\n\\t\\t\\treturn len( self.udimPaths ) != 0\\n\\t\\treturn super( textureFile, self ).exists\",\n \"def checkExistence(idMeta):\\n # XXX add for diaries\\n sqlq = \\\"\\\"\\\"\\n SELECT dt\\n FROM Electricity_10min\\n WHERE `Meta_idMeta` = {}\\n LIMIT 1;\\n \\\"\\\"\\\".format(idMeta)\\n try:\\n result = mdb.getSQL(sqlq)[0]\\n if (result):\\n return True\\n except:\\n return False\",\n \"def _exists(cursor, table, data):\\n cursor.execute('SELECT 1 FROM {} WHERE ({}) = ({})'.format(table, *_query_fields(data)), data)\\n return bool(cursor.fetchone())\",\n \"def test_count_no_spins(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Test the number of spins counted.\\n self.assertEqual(mol_res_spin.count_spins(), 0)\",\n \"def data_ready(self) -> bool:\\n data_ready = ctypes.c_uint8()\\n Utils.check(VL53L1X_C_LIBRARY.VL53L1_GetMeasurementDataReady(self.dev, byref(data_ready)))\\n return data_ready.value != 0\",\n \"def check_data_exist(data):\\n if data is not None:\\n if data.text is not None:\\n return True\\n return False\",\n \"def datafileexist(filename):\\n filePath = os.path.join(pathtofolder(), \\\"datas\\\", filename)\\n fileFormat = '.csv'\\n return os.path.exists(f'{filePath+fileFormat}')\",\n \"def exists(self, number):\\n\\t\\tslotIDList = [s.id for s in self.slotList]\\n\\t\\ttry:\\n\\t\\t\\tindex = slotIDList.index(number)\\n\\t\\t\\treturn True\\n\\t\\texcept ValueError:\\n\\t\\t\\treturn False\\n\\t\\treturn False\",\n \"def data_available(dataset_name=None):\\r\\n for file_list in data_resources[dataset_name]['files']:\\r\\n for file in file_list:\\r\\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\\r\\n return False\\r\\n return True\",\n \"def object_exists(self, name: str):\\n file_path = self.__get_file_path(name)\\n return os.path.exists(file_path)\",\n \"def test_return_molecule(self):\\n\\n # Ask for a few molecules.\\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\\n\\n # Test the data of molecule 1.\\n self.assertEqual(mol1.name, 'Ap4Aase')\\n\\n # Test the data of molecule 2.\\n self.assertEqual(mol2.name, 'RNA')\",\n \"def check_dataset_exists(dataset):\\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\\n return result == 0\",\n \"def exists(dtype, name, rootdir=None):\\n return FreezableAPI.to_slug(dtype,name) in FreezableAPI.datasets(rootdir=rootdir)\",\n \"def exists(self):\\n return os.path.exists(self.sensorpath)\",\n \"def check_for_data():\\n if not (os.path.exists(ep.get_test_data_path()) or os.path.exists(ep.get_dbn_weight_path())):\\n return False\\n return True\",\n \"def test_molecule_loop(self):\\n\\n # Loop over the molecules.\\n for mol in mol_res_spin.molecule_loop('#RNA'):\\n # Test the molecule name.\\n self.assertEqual(mol.name, 'RNA')\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)\",\n \"def exists(sim):\\n return (sim['N'] > 0)\",\n \"def exists(self) -> bool:\\n try:\\n result = self.get()\\n except KeyError:\\n return False\\n return True\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n logging.debug('hasImageData failed: no volume node')\\n return False\\n if volumeNode.GetImageData() is None:\\n logging.debug('hasImageData failed: no image data in volume node')\\n return False\\n return True\",\n \"def is_empty(self):\\n for key, dataset in self.datasets.items():\\n try:\\n has_data = dataset.has_data()\\n except MFDataException as mfde:\\n raise MFDataException(\\n mfdata_except=mfde,\\n model=self._container_package.model_name,\\n package=self._container_package._get_pname(),\\n message=\\\"Error occurred while verifying\\\"\\n ' data of dataset \\\"{}\\\" in block '\\n '\\\"{}\\\"'.format(dataset.structure.name, self.structure.name),\\n )\\n\\n if has_data is not None and has_data:\\n return False\\n return True\",\n \"def exists(self, name):\\n assert name, \\\"Must input a valid dataset name.\\\"\\n return name in self.manager.data[\\\"dataset\\\"]\",\n \"def is_data_run(info, runinfo):\\n this_run_in_runinfo = runinfo[\\n (runinfo.fNight==info[\\\"night_int\\\"])&\\n (runinfo.fRunID==info[\\\"run\\\"])\\n ]\\n return len(this_run_in_runinfo) > 0 and this_run_in_runinfo.iloc[0].fRunTypeKey == 1\",\n \"def is_data_present(self, cycle: int, bus_item: BusItem) -> bool:\\n buffer = self.get_cycle_buffer(cycle)\\n if self.component_subtype == \\\"PEGB\\\":\\n return False\\n #print(buffer)\\n # for pe_id in buffer:\\n # pe_buffer = buffer[pe_id]\\n # # # TODO ad-hoc\\n # # if isinstance(pe_buffer, deque):\\n # # return False\\n # #print(pe_buffer)\\n #\\n # pe_read_buffer = pe_buffer[\\\"read\\\"]\\n # #print(pe_read_buffer)\\n # for data in pe_read_buffer:\\n # if data == bus_item:\\n # return True\\n elif self.component_subtype == \\\"PENB\\\":\\n read_buffer = buffer[\\\"read\\\"]\\n for entry in read_buffer:\\n if entry == bus_item:\\n return True\\n else:\\n for data in buffer:\\n if data == bus_item:\\n return True\\n return False\",\n \"def exists(self):\\n try:\\n self.world.find(self.ehandle)\\n except KeyError:\\n return False\\n else:\\n return True\",\n \"def has_mask(mask_name, path=None, data=None):\\n if path is None and data is None:\\n raise ValueError(\\\"Mask file not provided.\\\")\\n if path:\\n with open(path, 'r') as file:\\n data = json.load(file)\\n \\n for inx, obj in enumerate(data[\\\"objects\\\"]):\\n if obj['classTitle'] == mask_name:\\n return inx\\n \\n return False\",\n \"def check_exist(self):\\n helper.RbdImageOperator._check_rbd_image(self.real_path)\",\n \"def check_data_struct():\\n if not os.path.exists(PROJECT_ROOT+'/data'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data')\\n\\n if not os.path.exists(PROJECT_ROOT+'/data/CUB_200_2011'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/CUB_200_2011')\\n\\n if not os.path.exists(PROJECT_ROOT+'/data/segmentations'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/segmentations')\\n\\n if not os.path.exists(PROJECT_ROOT+'/data/attributes.txt'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/attributes.txt')\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def is_present(self):\\n try:\\n self.read_binary(0, 2)\\n return True\\n except:\\n return False\",\n \"def has_data(self, fit_id, species_id, start=None, stop=None):\\n if not (fit_id in self.raw_results and species_id in\\\\\\n self.raw_results[fit_id]):\\n return False\\n if all([isinstance(x, datetime) for x in [start, stop]]):\\n ts = self.raw_results[fit_id][\\\"start\\\"]\\n if not any([start < x < stop for x in ts]):\\n return False\\n return True\",\n \"def particleExists(*args, **kwargs)->bool:\\n pass\",\n \"def is_section_exist(self, section_name: str) -> bool:\\n success = False\\n try:\\n self._vault_api.read_secret(path=section_name.upper(), mount_point=self.mount_point)\\n success = True\\n except InvalidPath:\\n pass\\n return success\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n logging.debug('hasImageData failed: no volume node')\\n return False\\n return True\",\n \"def check_model_exists(ckpt):\\n expected_data = ckpt + \\\".data-00000-of-00001\\\"\\n return os.path.exists(expected_data)\",\n \"def find_null(data, sub_reg):\\r\\n subreg_sqkm_data = data.loc[pd.IndexSlice[:, sub_reg, :], pd.IndexSlice['Sq Km']]\\r\\n if subreg_sqkm_data.isnull().values.any() == True:\\r\\n print(\\\"\\\\nSq km measurements are missing for:\\\")\\r\\n print(subreg_sqkm_data[subreg_sqkm_data.isnull()])\\r\\n else:\\r\\n print(\\\"\\\\nThere are no missing sq km values for this sub-region.\\\")\",\n \"def object_exists(self, fname):\\n return self.object_exists\",\n \"def checkfolderdata(folder = 'datas'):\\n if datafolderexist(folder):\\n return True\\n else:\\n createdatafolder(folder)\\n checkfolderdata(folder)\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n logging.debug('no volume node')\\n return False\\n if volumeNode.GetImageData() is None:\\n logging.debug('no image data')\\n return False\\n return True\",\n \"def data(self):\\n file_name = join(PARENT_BASE_DIR, '.files', 'data.data.json')\\n if isfile(file_name):\\n debug(f'{file_name} file is exist.')\\n debug(f'try for load {file_name} file ->->->->->->->->->->')\\n start_load_file = time()\\n with open(file_name, 'r', encoding='utf-8')as file:\\n data = file.read()\\n data = loads(data)\\n debug(f'load file - [runtime: {time() - start_load_file}] <-<-<-<-<-<-<-<-<-<-')\\n return data, 'data exist.'\\n else:\\n debug(f'{file_name} file is not exist.')\\n return None, 'data not exist in \\\"base directory/.files/data.data.json\\\"'\",\n \"def exists():\\n\\treturn os.path.exists('data/strmr.db')\",\n \"def IndexExists(self, arg0: 'unsigned long long') -> \\\"bool\\\":\\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF3GQEULLULLBBT_IndexExists(self, arg0)\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n print('no volume node')\\n return False\\n if volumeNode.GetImageData() == None:\\n print('no image data')\\n return False\\n return True\",\n \"def verify_object(self, data):\\n rv = self.get(data[self.id_field])\\n result = not is_404(rv)\\n if result:\\n for key, value in data:\\n if not in_response(rv, value):\\n return False\\n return result\",\n \"def check_name_in_file(name_to_check, data):\\r\\n if name_to_check in data:\\r\\n return True\\r\\n return False\",\n \"def check_file_existing(k_out, sphere_radius,full_path):\\n cwd = full_path\\n file_names = ['/T_ns_', '/Energy_', '/Distance-e-to-e_',\\n '/chain_on_iterations_']\\n\\n kout = f'{k_out:.3f}'\\n spr_rad = f'{sphere_radius:.3f}'\\n\\n current = \\\"kout_\\\" + kout + \\\"_\\\" + \\\"spr_rad_\\\" + spr_rad\\n for file_name in file_names:\\n #print (cwd + file_name + current + \\\".pkl\\\")\\n if not os.path.exists(cwd + file_name + current + \\\".pkl\\\"):\\n return False\\n return True\",\n \"def exists(self):\\n f = os.path.join(pth, '..', 'static/data', self.filename)\\n return os.path.isfile(f)\",\n \"def exist(self):\",\n \"def has_error(self):\\r\\n return self._arm.has_error\",\n \"def exists(self):\\r\\n return os.path.exists(self.full_path)\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n logging.debug('hasImageData failed: no volume node')\\n return False\\n if volumeNode.GetImageData() is None:\\n logging.debug('hasImageData failed: no image data in volume node')\\n return False\\n return True\",\n \"def exists (self, uuid):\\n return self.read (uuid) is not None\",\n \"def test_molecule_loop_no_selection(self):\\n\\n # Molecule data.\\n name = ['Ap4Aase', 'RNA']\\n\\n # Loop over the molecules.\\n i = 0\\n for mol in mol_res_spin.molecule_loop():\\n # Test the molecule names.\\n self.assertEqual(mol.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)\",\n \"def _check_data_point(cube, metadata):\\n point_index = []\\n\\n for dim_length in cube.shape:\\n point_index.append(int(random.random() * dim_length))\\n\\n point_index = tuple(point_index)\\n\\n try:\\n point_cube = cube[point_index]\\n _data_point = point_cube.data\\n except Exception:\\n msg = 'Unable to extract data point {} from file: {}'.format(\\n point_index, metadata['basename'])\\n raise FileValidationError(msg)\\n else:\\n return True\",\n \"def user_exists(self,unique_ID):\\n\\t\\ttry:\\n\\t\\t\\tself.data[unique_ID]\\n\\t\\texcept KeyError:\\n\\t\\t\\treturn False\\n\\t\\telse:\\n\\t\\t\\treturn True\",\n \"def object_exists(self, fname):\\n return False\",\n \"def test_is_in_ring(self):\\n molecule = Molecule.from_smiles(\\\"c1ccccc1\\\")\\n\\n for atom in molecule.atoms:\\n if atom.atomic_number == 6:\\n assert atom.is_in_ring()\\n\\n for bond in molecule.bonds:\\n if 1 in (bond.atom1.atomic_number, bond.atom2.atomic_number):\\n continue\\n assert bond.is_in_ring()\",\n \"def isRenderable(data):\\n return data.find(\\\"<molecule\\\") != -1 and data.find(\\\"<atom\\\") != -1\",\n \"def check_if_file_exists(self, sensor_id:str, name:str)->str:\\n ret_value = \\\"\\\"\\n file_name = '%s/%s.*.%s.json' % (self.generate_data_prep, sensor_id, name)\\n try: \\n ret_value = glob.glob(file_name)\\n except Exception as e:\\n print(\\\"OSError - Failed top get file (%s) - %s\\\" % (file_name, e))\\n ret_value = False \\n \\n if ret_value != False and len(ret_value) > 0: \\n ret_value = ret_value[0]\\n\\n return ret_value\",\n \"def IndexExists(self, arg0: 'unsigned long long') -> \\\"bool\\\":\\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF2GQEULLULLBBT_IndexExists(self, arg0)\",\n \"def object_exists(self, fname):\\n return True\",\n \"def has_data(self, *args, **kwargs):\\n return False\",\n \"def exists(self, data):\\n return data in self.__stack\",\n \"def contains(self, seq_nr: str) -> bool:\\n return bool(self.__data.get(seq_nr))\",\n \"def exists(self):\\r\\n return bool(self.bucket.lookup(self.name))\",\n \"def exists(self, name):\\n full_path = self.path(name)\\n return self.__volume.exists(full_path)\",\n \"def exists():\\n check50.include(\\\"data\\\")\\n check50.exists(\\\"adventure.py\\\")\\n check50.exists(\\\"room.py\\\")\",\n \"def assert_data_fragments_correct(self) -> bool:\\n read_path = Path(os.environ[\\\"DATA_PATH\\\"]) / \\\"fragments\\\"\\n if not read_path.exists():\\n return False\\n bin_images = [img for img in read_path.iterdir() if \\\"binarized\\\" in img.name]\\n if len(bin_images) == 0:\\n return False\\n return True\",\n \"def exist(self):\\n return self.file_path.exists()\",\n \"def test_return_residue(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_residue(':1')\\n res2 = mol_res_spin.return_residue(selection=':2')\\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1.num, 1)\\n self.assertEqual(res1.name, None)\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2.num, 2)\\n self.assertEqual(res2.name, 'Glu')\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4.num, 4)\\n self.assertEqual(res4.name, 'Pro')\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5.num, -5)\\n self.assertEqual(res5.name, None)\\n self.assertEqual(res5.spin[1].name, 'N5')\",\n \"def check_wheel_integrity(data, re_encoding='X1', enc_res=None, **_):\\n if isinstance(re_encoding, str):\\n re_encoding = int(re_encoding[-1])\\n # The expected difference between samples in the extracted units\\n resolution = 1 / (enc_res or ephys_fpga.WHEEL_TICKS\\n ) * np.pi * 2 * ephys_fpga.WHEEL_RADIUS_CM / re_encoding\\n # We expect the difference of neighbouring positions to be close to the resolution\\n pos_check = np.abs(np.diff(data['wheel_position']))\\n # Timestamps should be strictly increasing\\n ts_check = np.diff(data['wheel_timestamps']) <= 0.\\n metric = pos_check + ts_check.astype(float) # all values should be close to zero\\n passed = metric < 1.5 * resolution\\n return metric, passed\",\n \"def _loaded_data(self):\\n try:\\n dsize = [int(d) for d\\n in self.run('fits size', via='get').split()]\\n except (ValueError, TypeError, AttributeError) as err:\\n log.debug(f' FITS size error: {err}')\\n return False\\n else:\\n if 0 in dsize:\\n return False\\n else:\\n return True\",\n \"def _check_cell_measure_point(cfreader, metadata):\\n cell_measure = None\\n\\n for cf_group in cfreader.cf_group.values():\\n if cf_group.cf_name == metadata['cmor_name']:\\n cell_measure = cf_group\\n break\\n\\n if not cell_measure:\\n msg = ('Unable to find cell measure in cfreader for variable {}'.\\n format(metadata['cmor_name']))\\n raise FileValidationError(msg)\\n\\n point_index = []\\n for dim_length in cell_measure.cf_data.shape:\\n point_index.append(random.randint(0, dim_length - 1))\\n\\n try:\\n _data_point = cell_measure.cf_data[tuple(point_index)]\\n except Exception:\\n msg = 'Unable to extract data point {} from file: {}'.format(\\n point_index, metadata['basename'])\\n raise FileValidationError(msg)\\n else:\\n return True\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.84925765","0.8205755","0.81849754","0.7938019","0.78887266","0.75465906","0.6573173","0.63930625","0.56609166","0.5556357","0.5478604","0.53835493","0.5380998","0.53788584","0.53724927","0.5332502","0.5311545","0.52456486","0.52142644","0.52067447","0.52019215","0.5196566","0.5186528","0.51859933","0.5131939","0.51190865","0.51184976","0.51184976","0.50985634","0.5080594","0.5073501","0.50731343","0.50540185","0.5021005","0.50077015","0.49966064","0.49902868","0.4959969","0.49522027","0.49395013","0.49129793","0.49118412","0.49000916","0.48981947","0.48945946","0.4887719","0.4885243","0.48747268","0.4870395","0.4869586","0.48606858","0.4858","0.48564428","0.4850647","0.48436937","0.4842796","0.48384935","0.4834993","0.48335233","0.4832508","0.48299763","0.48272815","0.48251426","0.48238972","0.48122218","0.48096263","0.4803101","0.48000658","0.4788999","0.47848547","0.47835723","0.47807178","0.47761518","0.47746462","0.4774614","0.4772288","0.47689885","0.47658432","0.47645482","0.47597915","0.4758656","0.4758609","0.4755362","0.4754671","0.4752731","0.4750092","0.4743148","0.4741852","0.47395965","0.4733897","0.473375","0.47291785","0.47233665","0.47219932","0.47042054","0.47015336","0.47013766","0.47004434","0.46964145","0.46906155"],"string":"[\n \"0.84925765\",\n \"0.8205755\",\n \"0.81849754\",\n \"0.7938019\",\n \"0.78887266\",\n \"0.75465906\",\n \"0.6573173\",\n \"0.63930625\",\n \"0.56609166\",\n \"0.5556357\",\n \"0.5478604\",\n \"0.53835493\",\n \"0.5380998\",\n \"0.53788584\",\n \"0.53724927\",\n \"0.5332502\",\n \"0.5311545\",\n \"0.52456486\",\n \"0.52142644\",\n \"0.52067447\",\n \"0.52019215\",\n \"0.5196566\",\n \"0.5186528\",\n \"0.51859933\",\n \"0.5131939\",\n \"0.51190865\",\n \"0.51184976\",\n \"0.51184976\",\n \"0.50985634\",\n \"0.5080594\",\n \"0.5073501\",\n \"0.50731343\",\n \"0.50540185\",\n \"0.5021005\",\n \"0.50077015\",\n \"0.49966064\",\n \"0.49902868\",\n \"0.4959969\",\n \"0.49522027\",\n \"0.49395013\",\n \"0.49129793\",\n \"0.49118412\",\n \"0.49000916\",\n \"0.48981947\",\n \"0.48945946\",\n \"0.4887719\",\n \"0.4885243\",\n \"0.48747268\",\n \"0.4870395\",\n \"0.4869586\",\n \"0.48606858\",\n \"0.4858\",\n \"0.48564428\",\n \"0.4850647\",\n \"0.48436937\",\n \"0.4842796\",\n \"0.48384935\",\n \"0.4834993\",\n \"0.48335233\",\n \"0.4832508\",\n \"0.48299763\",\n \"0.48272815\",\n \"0.48251426\",\n \"0.48238972\",\n \"0.48122218\",\n \"0.48096263\",\n \"0.4803101\",\n \"0.48000658\",\n \"0.4788999\",\n \"0.47848547\",\n \"0.47835723\",\n \"0.47807178\",\n \"0.47761518\",\n \"0.47746462\",\n \"0.4774614\",\n \"0.4772288\",\n \"0.47689885\",\n \"0.47658432\",\n \"0.47645482\",\n \"0.47597915\",\n \"0.4758656\",\n \"0.4758609\",\n \"0.4755362\",\n \"0.4754671\",\n \"0.4752731\",\n \"0.4750092\",\n \"0.4743148\",\n \"0.4741852\",\n \"0.47395965\",\n \"0.4733897\",\n \"0.473375\",\n \"0.47291785\",\n \"0.47233665\",\n \"0.47219932\",\n \"0.47042054\",\n \"0.47015336\",\n \"0.47013766\",\n \"0.47004434\",\n \"0.46964145\",\n \"0.46906155\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8367752"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":81476,"cells":{"query":{"kind":"string","value":"Determine if moleculeresiduespin data exists (when a single residue is named). The function tested is pipe_control.mol_res_spin.exists_mol_res_spin_data()."},"document":{"kind":"string","value":"def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def isExist(data):\n return True/False","def hasResidue(self, resname):\n if resname in self.map:\n return 1\n else:\n return 0","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def check_residue(self, chain_id, resid, resname):\n if resname in PTM_lookup.keys():\n return\n else:\n try:\n ref_resname = PTM_reverse_lookup[resname]\n except KeyError:\n # print \"skipping unrecognized residue\", resname\n return\n ptm_dict = PTM_lookup[ref_resname][resname]\n return (chain_id, resid, ref_resname, ptm_dict[\"goto_atom\"], ptm_dict[\"name\"])","def test_return_single_residue_info(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_single_residue_info('1')\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\n res5 = mol_res_spin.return_single_residue_info('-5')\n\n # Test the data of residue 1.\n self.assertEqual(res1, (1, None))\n\n # Test the data of residue 2.\n self.assertEqual(res2, (2, 'Glu'))\n\n # Test the data of residue 4.\n self.assertEqual(res4, (4, 'Pro'))\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5, (-5, None))","def check_for_residue_existance(self):\n if not self.pose.total_residue():\n print \"No pose Loaded.\"\n return False\n\n if not self.current_chain.get() or not self.current_residue.get():\n print \"Chain or residue not set\"\n return False\n\n current_region = self.current_residue.get().split(\":\")\n if len(current_region)>1:\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\n\n\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\n print \"Region not found in pose\"\n return False\n else:\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\n\n print \"Residue not found in pose\"\n return False\n\n #If everythig is good then:\n return True","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def object_exists(self, name: str):\n file_path = self.__get_file_path(name)\n return os.path.exists(file_path)","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def datafolderexist(name):\n folderpath = os.path.join(pathtofolder(), name)\n return os.path.exists(folderpath)","def file_exists(msl_data_path, filename):\n return os.path.isfile(msl_data_path + filename)","def exists(self, datadir):\n return False","def test_return_residue(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_residue(':1')\n res2 = mol_res_spin.return_residue(selection=':2')\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\n\n # Test the data of residue 1.\n self.assertEqual(res1.num, 1)\n self.assertEqual(res1.name, None)\n\n # Test the data of residue 2.\n self.assertEqual(res2.num, 2)\n self.assertEqual(res2.name, 'Glu')\n\n # Test the data of residue 4.\n self.assertEqual(res4.num, 4)\n self.assertEqual(res4.name, 'Pro')\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5.num, -5)\n self.assertEqual(res5.name, None)\n self.assertEqual(res5.spin[1].name, 'N5')","def exists(self):\n\t\tif self.hasUdim:\n\t\t\treturn len( self.udimPaths ) != 0\n\t\treturn super( textureFile, self ).exists","def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def isResidueAssigned(residue):\n\n for atom in residue.atoms:\n if atom.atomSet:\n if atom.atomSet.resonanceSets:\n return True\n \n return False","def exists(self, number):\n\t\tslotIDList = [s.id for s in self.slotList]\n\t\ttry:\n\t\t\tindex = slotIDList.index(number)\n\t\t\treturn True\n\t\texcept ValueError:\n\t\t\treturn False\n\t\treturn False","def exists(self, name):\n assert name, \"Must input a valid dataset name.\"\n return name in self.manager.data[\"dataset\"]","def _object_exists(name):\n conn = sqlite3.connect('/dev/input')\n try:\n cur = conn.cursor()\n sql = 'SELECT ROWID FROM object WHERE name=? AND deleted=0'\n cur.execute(sql, (name, ))\n result = cur.fetchall()\n return len(result) > 0\n finally:\n conn.close()","def CheckForExistence(requested_data, available_data):\n if requested_data is not None:\n return 1 # The requested data exists.\n elif available_data:\n return -1 # The requested data does not exist.\n else:\n return 0 # No data exists at all.","def check_name_in_file(name_to_check, data):\r\n if name_to_check in data:\r\n return True\r\n return False","async def exists(self, tag_name):\n try:\n if await self.get_id(tag_name):\n return True\n except RtbDoesntExists:\n return False","def exists(self, name):\n full_path = self.path(name)\n return self.__volume.exists(full_path)","def has_mask(mask_name, path=None, data=None):\n if path is None and data is None:\n raise ValueError(\"Mask file not provided.\")\n if path:\n with open(path, 'r') as file:\n data = json.load(file)\n \n for inx, obj in enumerate(data[\"objects\"]):\n if obj['classTitle'] == mask_name:\n return inx\n \n return False","def pickleExists(name):\n fileNames = [f for f in os.listdir(PICKLE_DIR) if name in f]\n return not len(fileNames) == 0","def is_section_exist(self, section_name: str) -> bool:\n success = False\n try:\n self._vault_api.read_secret(path=section_name.upper(), mount_point=self.mount_point)\n success = True\n except InvalidPath:\n pass\n return success","def has_data(self, fragment, number):\n if fragment in self.mdv:\n if number in self.mdv[fragment]:\n return True\n return False","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def hasAtom(self, atomname):\n if atomname in self.atoms:\n return 1\n else:\n return 0","def has_name(self):\n return self.unpack_word(0x2) != 0","def __in_delete_serial_name(self, name):\n # Open the delete .csv file\n # Initialize the reader\n # For a row in the reader,\n # If the checking name is in the row, \n # return True\n # Return False if the name is not found\n input_filename = \"HobowareDeleteSerial.csv\"\n input_file = open(os.path.join('Hobowarebin',input_filename), \"r\")\n reader = csv.reader(input_file, delimiter = \",\")\n \n for input_row in reader:\n if name in input_row:\n return True\n \n input_file.close()\n \n return False","def exists(self):\n try:\n self.world.find(self.ehandle)\n except KeyError:\n return False\n else:\n return True","def exists(dtype, name, rootdir=None):\n return FreezableAPI.to_slug(dtype,name) in FreezableAPI.datasets(rootdir=rootdir)","def contains(self, seq_nr: str) -> bool:\n return bool(self.__data.get(seq_nr))","def has_material(obj, name):\n return name in obj.data.materials.keys()","def is_data_by_filename(fname):\n return \"Run2017\" in fname","def object_exists(self, fname):\n return self.object_exists","def object_exists(self, fname):\n return False","def exists(self, name):\n self.connect()\n self._write('EXISTS %s\\r\\n' % name)\n return self._get_numeric_response()","def object_exists(self, fname):\n return True","def is_version_data_existed(self):\n # if exists, skip\n # return \n\n return True","def exists():\n\treturn os.path.exists('data/strmr.db')","def datafileexist(filename):\n filePath = os.path.join(pathtofolder(), \"datas\", filename)\n fileFormat = '.csv'\n return os.path.exists(f'{filePath+fileFormat}')","def test_molecule_loop_no_selection(self):\n\n # Molecule data.\n name = ['Ap4Aase', 'RNA']\n\n # Loop over the molecules.\n i = 0\n for mol in mol_res_spin.molecule_loop():\n # Test the molecule names.\n self.assertEqual(mol.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)","def test_residue_loop(self):\n\n # Loop over the residues.\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\n # Test the selection.\n self.assertEqual(res.num, 2)\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)","def check_residue_callback(self):\n\n if not self.check_for_residue_existance():\n return\n\n self.listbox_current_designs.delete(0, END)\n self.current_residueFull = self.current_residue.get().split(\":\")\n\n if len(self.current_residueFull) > 1:\n self.listbox_restypes.delete(9)\n self.listbox_restypes.insert(9, \"Conserved\")\n else:\n res = self.current_residueFull[0] +\":\"+self.current_chain.get()\n #print res\n if not self.pose.total_residue():\n return\n\n resType = self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get()))\n try:\n resName = self.pose.residue(resType).name()\n except PyRosettaException:\n print \"Residue does not exist in PDB...\"\n return\n\n\n self.current_residue_name_full.set(resName)\n three_letter_name = resName.split(\"_\")[0]; #Fix for Rosetta designated chain endings, His_d\n self.current_residue_name.set(resName)\n\n #Fix for not having data for certain residue types:\n try:\n self.design_accessible_sa.set(self.residue_definitions.resinfo[three_letter_name][0])\n self.design_relative_mutability.set(self.residue_definitions.resinfo[three_letter_name][1])\n self.design_surface_probability.set(self.residue_definitions.resinfo[three_letter_name][2])\n except KeyError:\n print \"No Data for restype\"\n self.design_accessible_sa.set(\"\")\n self.design_relative_mutability.set(\"\")\n self.design_surface_probability.set(\"\")\n\n con = \"Conserved:\" +three_letter_name\n self.listbox_restypes.delete(9)\n self.listbox_restypes.insert(9, con)\n if self.DesignDic.has_key(res):\n for residues in self.DesignDic[res]:\n self.listbox_current_designs.insert(END, residues)","def check_if_file_exists(self, sensor_id:str, name:str)->str:\n ret_value = \"\"\n file_name = '%s/%s.*.%s.json' % (self.generate_data_prep, sensor_id, name)\n try: \n ret_value = glob.glob(file_name)\n except Exception as e:\n print(\"OSError - Failed top get file (%s) - %s\" % (file_name, e))\n ret_value = False \n \n if ret_value != False and len(ret_value) > 0: \n ret_value = ret_value[0]\n\n return ret_value","def race_entry_exists(self, race_id):\n try:\n self.consolidated_db.data.loc[race_id] # Throws a KeyError if no entry is in the dataframe.\n return True\n except KeyError:\n return False","def is_standard_residue(self):\n return False","def exists(sim):\n return (sim['N'] > 0)","def test_return_molecule(self):\n\n # Ask for a few molecules.\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\n\n # Test the data of molecule 1.\n self.assertEqual(mol1.name, 'Ap4Aase')\n\n # Test the data of molecule 2.\n self.assertEqual(mol2.name, 'RNA')","def exists(self, name):\n try:\n self.container.get_object(name)\n return True\n except NoSuchObject:\n return False","def test_count_no_spins(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 0)","def test_molecule_loop(self):\n\n # Loop over the molecules.\n for mol in mol_res_spin.molecule_loop('#RNA'):\n # Test the molecule name.\n self.assertEqual(mol.name, 'RNA')\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)","def exists(self):\n\n return os.path.exists(self[\"~filename\"])","def checkExistence(idMeta):\n # XXX add for diaries\n sqlq = \"\"\"\n SELECT dt\n FROM Electricity_10min\n WHERE `Meta_idMeta` = {}\n LIMIT 1;\n \"\"\".format(idMeta)\n try:\n result = mdb.getSQL(sqlq)[0]\n if (result):\n return True\n except:\n return False","def check_id_existence(self, id:str):\n\n oc_prefix = id[:(id.index(':')+1)]\n\n if oc_prefix == 'doi:':\n vldt = doi.DOIManager() # you can use removeprefix(oc_prefix) from Python 3.9+\n return vldt.exists(id.replace(oc_prefix, '', 1)) # todo: use id.replace(oc_prefix, '', 1) for Python < v.3.9\n if oc_prefix == 'isbn:':\n vldt = isbn.ISBNManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'issn:':\n vldt = issn.ISSNManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'orcid:':\n vldt = orcid.ORCIDManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'pmcid:':\n vldt = pmcid.PMCIDManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'pmid:':\n vldt = pmid.PMIDManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'ror:':\n vldt = ror.RORManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'url:':\n vldt = url.URLManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'viaf:':\n vldt = viaf.ViafManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'wikidata:':\n vldt = wikidata.WikidataManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'wikipedia:':\n vldt = wikipedia.WikipediaManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))","def pl_exists(self, name):\n for i, d in enumerate(self.ui.leftwin.data):\n if d.data.name == name:\n return i\n\n return -1","def check_file_existing(k_out, sphere_radius,full_path):\n cwd = full_path\n file_names = ['/T_ns_', '/Energy_', '/Distance-e-to-e_',\n '/chain_on_iterations_']\n\n kout = f'{k_out:.3f}'\n spr_rad = f'{sphere_radius:.3f}'\n\n current = \"kout_\" + kout + \"_\" + \"spr_rad_\" + spr_rad\n for file_name in file_names:\n #print (cwd + file_name + current + \".pkl\")\n if not os.path.exists(cwd + file_name + current + \".pkl\"):\n return False\n return True","def has_data(self, time, fragment, number):\n if time in self.mdvtc.keys():\n if fragment in self.mdvtc[time].mdv.keys():\n if number in self.mdvtc[time].mdv[fragment].keys():\n return True\n return False","def exists(name):\n\n return get_component(CachingPackage.COMPONENT_NAME).exists(name)","def notebook_exists(self, name, path=''):\n\n\t\tos_path = self._get_os_path(name, path=path)\n\t\treturn key_exists(self.bucket, os_path)","def test_return_single_residue_info_fail(self):\n\n # Ask for a few residues.\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')","def exists(self):\r\n return os.path.exists(self.full_path)","def id_exists(test_name):\n result_json = None\n try:\n with open(robot_dir + \"/output/results/{}.json\".format(test_name.replace(' ', ''))) as result_file:\n result_json = json.load(result_file)\n except:\n print(\"Failed to open the result json\")\n return False\n #look for values NEW_ASSOC, NEW_PROP1, NEW_PROP2\n print(result_json)\n if 6 == 6:\n return True\n return \"Length is not 6\"","def volume_exists(vil, vol_name):\n\n exists = False\n try:\n if not vil:\n vil, err = get_basic_volume_info_all()\n if err:\n raise Exception(err)\n if vil:\n for v in vil:\n if v[\"name\"] == vol_name:\n exists = True\n except Exception, e:\n return False, 'Error checking for volume existance : %s' % str(e)\n else:\n return exists, None","def IndexExists(self, arg0: 'unsigned long long') -> \"bool\":\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF3GQEULLULLBBT_IndexExists(self, arg0)","def particleExists(*args, **kwargs)->bool:\n pass","def _exists(cursor, table, data):\n cursor.execute('SELECT 1 FROM {} WHERE ({}) = ({})'.format(table, *_query_fields(data)), data)\n return bool(cursor.fetchone())","def data_available(dataset_name=None):\r\n for file_list in data_resources[dataset_name]['files']:\r\n for file in file_list:\r\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\r\n return False\r\n return True","def has(resname):\n # check HOME directory first\n if os.path.exists(os.path.join(os.getenv(\"HOME\"), \".aphla\", resname)):\n return True\n else:\n return resource_exists(__name__, resname)","def test_run_molecule_not_selected(self, single_mol_system):\n sequence = \"ABCDE\"\n processor = dssp.AnnotateResidues(\n \"test\", sequence, molecule_selector=lambda mol: False\n )\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert vermouth.utils.are_all_equal(found)\n assert found[0] is None","def exists(self) -> bool:\n try:\n result = self.get()\n except KeyError:\n return False\n return True","def has_data(self) -> bool:\n raise NotImplementedError","def valid_resfile(listname):\r\n global results_file, directory_res\r\n try:\r\n results_file = open(directory_res+listname+\".output\", \"r\")\r\n return True\r\n except:\r\n return False","def resultExist(probName,algoName,fitName,inst,s,c,n,k,q,w,m,t,e):\n if probName == 'NKQ':\n nameOfF = './result/'+probName+'-'+algoName+'-F'+fitName+'-M'+m+'-I'+str(inst)+'-S'+str(s)+'-W'+str(w)+'-N'+str(n)+'-K'+str(k)+'-C'+str(c)+'-Q'+str(q)+'-T'+str(t)+'-E'+str(e)+'.txt'\n elif probName == 'NK' or probName == 'NonNK':\n nameOfF = './result/'+probName+'-'+algoName+'-F'+fitName+'-C'+str(c)+'-I'+str(inst)+'-S'+str(s)+'-W'+str(w)+'-N'+str(n)+'-K'+str(k)+'-E'+str(e)+'.txt'\n\n if os.path.isfile(nameOfF)==True:\n print nameOfF, 'exists!!!'\n return os.path.isfile(nameOfF)","def _validate_duplicate_names(res_data, name, _id=None):\n if _id:\n for data in res_data:\n if data.get(\"name\") == name and data.get(\"id\") != _id:\n return False\n return True\n else:\n for data in res_data:\n if data.get(\"name\") == name:\n return False\n return True","def IndexExists(self, arg0: 'unsigned long long') -> \"bool\":\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF2GQEULLULLBBT_IndexExists(self, arg0)","def exists(self):\r\n return bool(self.bucket.lookup(self.name))","def is_standard_residue(self):\n return True","def is_standard_residue(self):\n return True","def check_model_exists(ckpt):\n expected_data = ckpt + \".data-00000-of-00001\"\n return os.path.exists(expected_data)","def exists(self, name):\n raise NotImplementedError()","def exists(identifier, network):\n foo = next(load(identifier, network), None)\n return foo is not None","def user_exists(self,unique_ID):\n\t\ttry:\n\t\t\tself.data[unique_ID]\n\t\texcept KeyError:\n\t\t\treturn False\n\t\telse:\n\t\t\treturn True","def ResourceExists(resource_name, search_user_paths=True):\n try:\n ResourcePath(resource_name, search_user_paths)\n return True\n except ResourceNotFound:\n return False","def in_results(compound):\n name = decode(compound)\n return (name in results_bank)","def locateSlotData(self, name):\n if self._slotData:\n data = self._slotData.get(name, _marker)\n if data is not _marker:\n return data\n if self.parent is None:\n raise KeyError, \"Slot named '%s' was not filled.\" % name\n return self.parent.locateSlotData(name)","def is_section_exist(self, section_name: str) -> bool:\n pass","def ResourceExists(self, name):\n pass","def is_present(self):\n try:\n self.read_binary(0, 2)\n return True\n except:\n return False","def exists(name, runas=None):\n vm_info = list_vms(name, info=True, runas=runas).splitlines()\n for info_line in vm_info:\n if \"Name: {}\".format(name) in info_line:\n return True\n return False","def player_exists_in_db(name: str):\n with open('db.json') as fo:\n data = loads(fo.read())\n return name in data"],"string":"[\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def isExist(data):\\n return True/False\",\n \"def hasResidue(self, resname):\\n if resname in self.map:\\n return 1\\n else:\\n return 0\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def check_residue(self, chain_id, resid, resname):\\n if resname in PTM_lookup.keys():\\n return\\n else:\\n try:\\n ref_resname = PTM_reverse_lookup[resname]\\n except KeyError:\\n # print \\\"skipping unrecognized residue\\\", resname\\n return\\n ptm_dict = PTM_lookup[ref_resname][resname]\\n return (chain_id, resid, ref_resname, ptm_dict[\\\"goto_atom\\\"], ptm_dict[\\\"name\\\"])\",\n \"def test_return_single_residue_info(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_single_residue_info('1')\\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\\n res5 = mol_res_spin.return_single_residue_info('-5')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1, (1, None))\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2, (2, 'Glu'))\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4, (4, 'Pro'))\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5, (-5, None))\",\n \"def check_for_residue_existance(self):\\n if not self.pose.total_residue():\\n print \\\"No pose Loaded.\\\"\\n return False\\n\\n if not self.current_chain.get() or not self.current_residue.get():\\n print \\\"Chain or residue not set\\\"\\n return False\\n\\n current_region = self.current_residue.get().split(\\\":\\\")\\n if len(current_region)>1:\\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\\n\\n\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\\n print \\\"Region not found in pose\\\"\\n return False\\n else:\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\\n\\n print \\\"Residue not found in pose\\\"\\n return False\\n\\n #If everythig is good then:\\n return True\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def object_exists(self, name: str):\\n file_path = self.__get_file_path(name)\\n return os.path.exists(file_path)\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def datafolderexist(name):\\n folderpath = os.path.join(pathtofolder(), name)\\n return os.path.exists(folderpath)\",\n \"def file_exists(msl_data_path, filename):\\n return os.path.isfile(msl_data_path + filename)\",\n \"def exists(self, datadir):\\n return False\",\n \"def test_return_residue(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_residue(':1')\\n res2 = mol_res_spin.return_residue(selection=':2')\\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1.num, 1)\\n self.assertEqual(res1.name, None)\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2.num, 2)\\n self.assertEqual(res2.name, 'Glu')\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4.num, 4)\\n self.assertEqual(res4.name, 'Pro')\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5.num, -5)\\n self.assertEqual(res5.name, None)\\n self.assertEqual(res5.spin[1].name, 'N5')\",\n \"def exists(self):\\n\\t\\tif self.hasUdim:\\n\\t\\t\\treturn len( self.udimPaths ) != 0\\n\\t\\treturn super( textureFile, self ).exists\",\n \"def test_molecule_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the molecules.\\n i = 0\\n for molecule in mol_res_spin.molecule_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def isResidueAssigned(residue):\\n\\n for atom in residue.atoms:\\n if atom.atomSet:\\n if atom.atomSet.resonanceSets:\\n return True\\n \\n return False\",\n \"def exists(self, number):\\n\\t\\tslotIDList = [s.id for s in self.slotList]\\n\\t\\ttry:\\n\\t\\t\\tindex = slotIDList.index(number)\\n\\t\\t\\treturn True\\n\\t\\texcept ValueError:\\n\\t\\t\\treturn False\\n\\t\\treturn False\",\n \"def exists(self, name):\\n assert name, \\\"Must input a valid dataset name.\\\"\\n return name in self.manager.data[\\\"dataset\\\"]\",\n \"def _object_exists(name):\\n conn = sqlite3.connect('/dev/input')\\n try:\\n cur = conn.cursor()\\n sql = 'SELECT ROWID FROM object WHERE name=? AND deleted=0'\\n cur.execute(sql, (name, ))\\n result = cur.fetchall()\\n return len(result) > 0\\n finally:\\n conn.close()\",\n \"def CheckForExistence(requested_data, available_data):\\n if requested_data is not None:\\n return 1 # The requested data exists.\\n elif available_data:\\n return -1 # The requested data does not exist.\\n else:\\n return 0 # No data exists at all.\",\n \"def check_name_in_file(name_to_check, data):\\r\\n if name_to_check in data:\\r\\n return True\\r\\n return False\",\n \"async def exists(self, tag_name):\\n try:\\n if await self.get_id(tag_name):\\n return True\\n except RtbDoesntExists:\\n return False\",\n \"def exists(self, name):\\n full_path = self.path(name)\\n return self.__volume.exists(full_path)\",\n \"def has_mask(mask_name, path=None, data=None):\\n if path is None and data is None:\\n raise ValueError(\\\"Mask file not provided.\\\")\\n if path:\\n with open(path, 'r') as file:\\n data = json.load(file)\\n \\n for inx, obj in enumerate(data[\\\"objects\\\"]):\\n if obj['classTitle'] == mask_name:\\n return inx\\n \\n return False\",\n \"def pickleExists(name):\\n fileNames = [f for f in os.listdir(PICKLE_DIR) if name in f]\\n return not len(fileNames) == 0\",\n \"def is_section_exist(self, section_name: str) -> bool:\\n success = False\\n try:\\n self._vault_api.read_secret(path=section_name.upper(), mount_point=self.mount_point)\\n success = True\\n except InvalidPath:\\n pass\\n return success\",\n \"def has_data(self, fragment, number):\\n if fragment in self.mdv:\\n if number in self.mdv[fragment]:\\n return True\\n return False\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def hasAtom(self, atomname):\\n if atomname in self.atoms:\\n return 1\\n else:\\n return 0\",\n \"def has_name(self):\\n return self.unpack_word(0x2) != 0\",\n \"def __in_delete_serial_name(self, name):\\n # Open the delete .csv file\\n # Initialize the reader\\n # For a row in the reader,\\n # If the checking name is in the row, \\n # return True\\n # Return False if the name is not found\\n input_filename = \\\"HobowareDeleteSerial.csv\\\"\\n input_file = open(os.path.join('Hobowarebin',input_filename), \\\"r\\\")\\n reader = csv.reader(input_file, delimiter = \\\",\\\")\\n \\n for input_row in reader:\\n if name in input_row:\\n return True\\n \\n input_file.close()\\n \\n return False\",\n \"def exists(self):\\n try:\\n self.world.find(self.ehandle)\\n except KeyError:\\n return False\\n else:\\n return True\",\n \"def exists(dtype, name, rootdir=None):\\n return FreezableAPI.to_slug(dtype,name) in FreezableAPI.datasets(rootdir=rootdir)\",\n \"def contains(self, seq_nr: str) -> bool:\\n return bool(self.__data.get(seq_nr))\",\n \"def has_material(obj, name):\\n return name in obj.data.materials.keys()\",\n \"def is_data_by_filename(fname):\\n return \\\"Run2017\\\" in fname\",\n \"def object_exists(self, fname):\\n return self.object_exists\",\n \"def object_exists(self, fname):\\n return False\",\n \"def exists(self, name):\\n self.connect()\\n self._write('EXISTS %s\\\\r\\\\n' % name)\\n return self._get_numeric_response()\",\n \"def object_exists(self, fname):\\n return True\",\n \"def is_version_data_existed(self):\\n # if exists, skip\\n # return \\n\\n return True\",\n \"def exists():\\n\\treturn os.path.exists('data/strmr.db')\",\n \"def datafileexist(filename):\\n filePath = os.path.join(pathtofolder(), \\\"datas\\\", filename)\\n fileFormat = '.csv'\\n return os.path.exists(f'{filePath+fileFormat}')\",\n \"def test_molecule_loop_no_selection(self):\\n\\n # Molecule data.\\n name = ['Ap4Aase', 'RNA']\\n\\n # Loop over the molecules.\\n i = 0\\n for mol in mol_res_spin.molecule_loop():\\n # Test the molecule names.\\n self.assertEqual(mol.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)\",\n \"def test_residue_loop(self):\\n\\n # Loop over the residues.\\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\\n # Test the selection.\\n self.assertEqual(res.num, 2)\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)\",\n \"def check_residue_callback(self):\\n\\n if not self.check_for_residue_existance():\\n return\\n\\n self.listbox_current_designs.delete(0, END)\\n self.current_residueFull = self.current_residue.get().split(\\\":\\\")\\n\\n if len(self.current_residueFull) > 1:\\n self.listbox_restypes.delete(9)\\n self.listbox_restypes.insert(9, \\\"Conserved\\\")\\n else:\\n res = self.current_residueFull[0] +\\\":\\\"+self.current_chain.get()\\n #print res\\n if not self.pose.total_residue():\\n return\\n\\n resType = self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get()))\\n try:\\n resName = self.pose.residue(resType).name()\\n except PyRosettaException:\\n print \\\"Residue does not exist in PDB...\\\"\\n return\\n\\n\\n self.current_residue_name_full.set(resName)\\n three_letter_name = resName.split(\\\"_\\\")[0]; #Fix for Rosetta designated chain endings, His_d\\n self.current_residue_name.set(resName)\\n\\n #Fix for not having data for certain residue types:\\n try:\\n self.design_accessible_sa.set(self.residue_definitions.resinfo[three_letter_name][0])\\n self.design_relative_mutability.set(self.residue_definitions.resinfo[three_letter_name][1])\\n self.design_surface_probability.set(self.residue_definitions.resinfo[three_letter_name][2])\\n except KeyError:\\n print \\\"No Data for restype\\\"\\n self.design_accessible_sa.set(\\\"\\\")\\n self.design_relative_mutability.set(\\\"\\\")\\n self.design_surface_probability.set(\\\"\\\")\\n\\n con = \\\"Conserved:\\\" +three_letter_name\\n self.listbox_restypes.delete(9)\\n self.listbox_restypes.insert(9, con)\\n if self.DesignDic.has_key(res):\\n for residues in self.DesignDic[res]:\\n self.listbox_current_designs.insert(END, residues)\",\n \"def check_if_file_exists(self, sensor_id:str, name:str)->str:\\n ret_value = \\\"\\\"\\n file_name = '%s/%s.*.%s.json' % (self.generate_data_prep, sensor_id, name)\\n try: \\n ret_value = glob.glob(file_name)\\n except Exception as e:\\n print(\\\"OSError - Failed top get file (%s) - %s\\\" % (file_name, e))\\n ret_value = False \\n \\n if ret_value != False and len(ret_value) > 0: \\n ret_value = ret_value[0]\\n\\n return ret_value\",\n \"def race_entry_exists(self, race_id):\\n try:\\n self.consolidated_db.data.loc[race_id] # Throws a KeyError if no entry is in the dataframe.\\n return True\\n except KeyError:\\n return False\",\n \"def is_standard_residue(self):\\n return False\",\n \"def exists(sim):\\n return (sim['N'] > 0)\",\n \"def test_return_molecule(self):\\n\\n # Ask for a few molecules.\\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\\n\\n # Test the data of molecule 1.\\n self.assertEqual(mol1.name, 'Ap4Aase')\\n\\n # Test the data of molecule 2.\\n self.assertEqual(mol2.name, 'RNA')\",\n \"def exists(self, name):\\n try:\\n self.container.get_object(name)\\n return True\\n except NoSuchObject:\\n return False\",\n \"def test_count_no_spins(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Test the number of spins counted.\\n self.assertEqual(mol_res_spin.count_spins(), 0)\",\n \"def test_molecule_loop(self):\\n\\n # Loop over the molecules.\\n for mol in mol_res_spin.molecule_loop('#RNA'):\\n # Test the molecule name.\\n self.assertEqual(mol.name, 'RNA')\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)\",\n \"def exists(self):\\n\\n return os.path.exists(self[\\\"~filename\\\"])\",\n \"def checkExistence(idMeta):\\n # XXX add for diaries\\n sqlq = \\\"\\\"\\\"\\n SELECT dt\\n FROM Electricity_10min\\n WHERE `Meta_idMeta` = {}\\n LIMIT 1;\\n \\\"\\\"\\\".format(idMeta)\\n try:\\n result = mdb.getSQL(sqlq)[0]\\n if (result):\\n return True\\n except:\\n return False\",\n \"def check_id_existence(self, id:str):\\n\\n oc_prefix = id[:(id.index(':')+1)]\\n\\n if oc_prefix == 'doi:':\\n vldt = doi.DOIManager() # you can use removeprefix(oc_prefix) from Python 3.9+\\n return vldt.exists(id.replace(oc_prefix, '', 1)) # todo: use id.replace(oc_prefix, '', 1) for Python < v.3.9\\n if oc_prefix == 'isbn:':\\n vldt = isbn.ISBNManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'issn:':\\n vldt = issn.ISSNManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'orcid:':\\n vldt = orcid.ORCIDManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'pmcid:':\\n vldt = pmcid.PMCIDManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'pmid:':\\n vldt = pmid.PMIDManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'ror:':\\n vldt = ror.RORManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'url:':\\n vldt = url.URLManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'viaf:':\\n vldt = viaf.ViafManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'wikidata:':\\n vldt = wikidata.WikidataManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'wikipedia:':\\n vldt = wikipedia.WikipediaManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\",\n \"def pl_exists(self, name):\\n for i, d in enumerate(self.ui.leftwin.data):\\n if d.data.name == name:\\n return i\\n\\n return -1\",\n \"def check_file_existing(k_out, sphere_radius,full_path):\\n cwd = full_path\\n file_names = ['/T_ns_', '/Energy_', '/Distance-e-to-e_',\\n '/chain_on_iterations_']\\n\\n kout = f'{k_out:.3f}'\\n spr_rad = f'{sphere_radius:.3f}'\\n\\n current = \\\"kout_\\\" + kout + \\\"_\\\" + \\\"spr_rad_\\\" + spr_rad\\n for file_name in file_names:\\n #print (cwd + file_name + current + \\\".pkl\\\")\\n if not os.path.exists(cwd + file_name + current + \\\".pkl\\\"):\\n return False\\n return True\",\n \"def has_data(self, time, fragment, number):\\n if time in self.mdvtc.keys():\\n if fragment in self.mdvtc[time].mdv.keys():\\n if number in self.mdvtc[time].mdv[fragment].keys():\\n return True\\n return False\",\n \"def exists(name):\\n\\n return get_component(CachingPackage.COMPONENT_NAME).exists(name)\",\n \"def notebook_exists(self, name, path=''):\\n\\n\\t\\tos_path = self._get_os_path(name, path=path)\\n\\t\\treturn key_exists(self.bucket, os_path)\",\n \"def test_return_single_residue_info_fail(self):\\n\\n # Ask for a few residues.\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')\",\n \"def exists(self):\\r\\n return os.path.exists(self.full_path)\",\n \"def id_exists(test_name):\\n result_json = None\\n try:\\n with open(robot_dir + \\\"/output/results/{}.json\\\".format(test_name.replace(' ', ''))) as result_file:\\n result_json = json.load(result_file)\\n except:\\n print(\\\"Failed to open the result json\\\")\\n return False\\n #look for values NEW_ASSOC, NEW_PROP1, NEW_PROP2\\n print(result_json)\\n if 6 == 6:\\n return True\\n return \\\"Length is not 6\\\"\",\n \"def volume_exists(vil, vol_name):\\n\\n exists = False\\n try:\\n if not vil:\\n vil, err = get_basic_volume_info_all()\\n if err:\\n raise Exception(err)\\n if vil:\\n for v in vil:\\n if v[\\\"name\\\"] == vol_name:\\n exists = True\\n except Exception, e:\\n return False, 'Error checking for volume existance : %s' % str(e)\\n else:\\n return exists, None\",\n \"def IndexExists(self, arg0: 'unsigned long long') -> \\\"bool\\\":\\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF3GQEULLULLBBT_IndexExists(self, arg0)\",\n \"def particleExists(*args, **kwargs)->bool:\\n pass\",\n \"def _exists(cursor, table, data):\\n cursor.execute('SELECT 1 FROM {} WHERE ({}) = ({})'.format(table, *_query_fields(data)), data)\\n return bool(cursor.fetchone())\",\n \"def data_available(dataset_name=None):\\r\\n for file_list in data_resources[dataset_name]['files']:\\r\\n for file in file_list:\\r\\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\\r\\n return False\\r\\n return True\",\n \"def has(resname):\\n # check HOME directory first\\n if os.path.exists(os.path.join(os.getenv(\\\"HOME\\\"), \\\".aphla\\\", resname)):\\n return True\\n else:\\n return resource_exists(__name__, resname)\",\n \"def test_run_molecule_not_selected(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\", sequence, molecule_selector=lambda mol: False\\n )\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert vermouth.utils.are_all_equal(found)\\n assert found[0] is None\",\n \"def exists(self) -> bool:\\n try:\\n result = self.get()\\n except KeyError:\\n return False\\n return True\",\n \"def has_data(self) -> bool:\\n raise NotImplementedError\",\n \"def valid_resfile(listname):\\r\\n global results_file, directory_res\\r\\n try:\\r\\n results_file = open(directory_res+listname+\\\".output\\\", \\\"r\\\")\\r\\n return True\\r\\n except:\\r\\n return False\",\n \"def resultExist(probName,algoName,fitName,inst,s,c,n,k,q,w,m,t,e):\\n if probName == 'NKQ':\\n nameOfF = './result/'+probName+'-'+algoName+'-F'+fitName+'-M'+m+'-I'+str(inst)+'-S'+str(s)+'-W'+str(w)+'-N'+str(n)+'-K'+str(k)+'-C'+str(c)+'-Q'+str(q)+'-T'+str(t)+'-E'+str(e)+'.txt'\\n elif probName == 'NK' or probName == 'NonNK':\\n nameOfF = './result/'+probName+'-'+algoName+'-F'+fitName+'-C'+str(c)+'-I'+str(inst)+'-S'+str(s)+'-W'+str(w)+'-N'+str(n)+'-K'+str(k)+'-E'+str(e)+'.txt'\\n\\n if os.path.isfile(nameOfF)==True:\\n print nameOfF, 'exists!!!'\\n return os.path.isfile(nameOfF)\",\n \"def _validate_duplicate_names(res_data, name, _id=None):\\n if _id:\\n for data in res_data:\\n if data.get(\\\"name\\\") == name and data.get(\\\"id\\\") != _id:\\n return False\\n return True\\n else:\\n for data in res_data:\\n if data.get(\\\"name\\\") == name:\\n return False\\n return True\",\n \"def IndexExists(self, arg0: 'unsigned long long') -> \\\"bool\\\":\\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF2GQEULLULLBBT_IndexExists(self, arg0)\",\n \"def exists(self):\\r\\n return bool(self.bucket.lookup(self.name))\",\n \"def is_standard_residue(self):\\n return True\",\n \"def is_standard_residue(self):\\n return True\",\n \"def check_model_exists(ckpt):\\n expected_data = ckpt + \\\".data-00000-of-00001\\\"\\n return os.path.exists(expected_data)\",\n \"def exists(self, name):\\n raise NotImplementedError()\",\n \"def exists(identifier, network):\\n foo = next(load(identifier, network), None)\\n return foo is not None\",\n \"def user_exists(self,unique_ID):\\n\\t\\ttry:\\n\\t\\t\\tself.data[unique_ID]\\n\\t\\texcept KeyError:\\n\\t\\t\\treturn False\\n\\t\\telse:\\n\\t\\t\\treturn True\",\n \"def ResourceExists(resource_name, search_user_paths=True):\\n try:\\n ResourcePath(resource_name, search_user_paths)\\n return True\\n except ResourceNotFound:\\n return False\",\n \"def in_results(compound):\\n name = decode(compound)\\n return (name in results_bank)\",\n \"def locateSlotData(self, name):\\n if self._slotData:\\n data = self._slotData.get(name, _marker)\\n if data is not _marker:\\n return data\\n if self.parent is None:\\n raise KeyError, \\\"Slot named '%s' was not filled.\\\" % name\\n return self.parent.locateSlotData(name)\",\n \"def is_section_exist(self, section_name: str) -> bool:\\n pass\",\n \"def ResourceExists(self, name):\\n pass\",\n \"def is_present(self):\\n try:\\n self.read_binary(0, 2)\\n return True\\n except:\\n return False\",\n \"def exists(name, runas=None):\\n vm_info = list_vms(name, info=True, runas=runas).splitlines()\\n for info_line in vm_info:\\n if \\\"Name: {}\\\".format(name) in info_line:\\n return True\\n return False\",\n \"def player_exists_in_db(name: str):\\n with open('db.json') as fo:\\n data = loads(fo.read())\\n return name in data\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.8420557","0.83105195","0.8121444","0.81118304","0.807993","0.7950876","0.6401373","0.6279278","0.6215082","0.591349","0.5806613","0.5639699","0.5575356","0.54308885","0.5376391","0.53730816","0.53661835","0.5356303","0.5276748","0.5268216","0.52539533","0.52291477","0.5216037","0.5209246","0.52086127","0.52016914","0.5188573","0.5175646","0.51668495","0.5119033","0.5113","0.5105967","0.5103067","0.51025796","0.51025283","0.5086553","0.5073717","0.5062327","0.50277174","0.5022582","0.5021044","0.5016521","0.5007665","0.5003199","0.49915677","0.49897763","0.4984195","0.4983569","0.49809757","0.49556604","0.4932597","0.49263826","0.49159458","0.49146143","0.4899274","0.48986414","0.48949984","0.48900065","0.48848072","0.4877035","0.48765653","0.48667982","0.48657286","0.48644012","0.4862329","0.48615405","0.48615298","0.48541513","0.4852577","0.48500937","0.485002","0.48386562","0.48275882","0.48254207","0.48205447","0.48112366","0.48061135","0.48042753","0.47995898","0.4799266","0.47946575","0.47921014","0.47917795","0.4788765","0.47854716","0.4782754","0.478019","0.478019","0.47764185","0.47723618","0.47721428","0.47720838","0.47700143","0.47690904","0.47649857","0.4763742","0.47608736","0.47553214","0.47547445","0.47545776"],"string":"[\n \"0.8420557\",\n \"0.83105195\",\n \"0.8121444\",\n \"0.81118304\",\n \"0.807993\",\n \"0.7950876\",\n \"0.6401373\",\n \"0.6279278\",\n \"0.6215082\",\n \"0.591349\",\n \"0.5806613\",\n \"0.5639699\",\n \"0.5575356\",\n \"0.54308885\",\n \"0.5376391\",\n \"0.53730816\",\n \"0.53661835\",\n \"0.5356303\",\n \"0.5276748\",\n \"0.5268216\",\n \"0.52539533\",\n \"0.52291477\",\n \"0.5216037\",\n \"0.5209246\",\n \"0.52086127\",\n \"0.52016914\",\n \"0.5188573\",\n \"0.5175646\",\n \"0.51668495\",\n \"0.5119033\",\n \"0.5113\",\n \"0.5105967\",\n \"0.5103067\",\n \"0.51025796\",\n \"0.51025283\",\n \"0.5086553\",\n \"0.5073717\",\n \"0.5062327\",\n \"0.50277174\",\n \"0.5022582\",\n \"0.5021044\",\n \"0.5016521\",\n \"0.5007665\",\n \"0.5003199\",\n \"0.49915677\",\n \"0.49897763\",\n \"0.4984195\",\n \"0.4983569\",\n \"0.49809757\",\n \"0.49556604\",\n \"0.4932597\",\n \"0.49263826\",\n \"0.49159458\",\n \"0.49146143\",\n \"0.4899274\",\n \"0.48986414\",\n \"0.48949984\",\n \"0.48900065\",\n \"0.48848072\",\n \"0.4877035\",\n \"0.48765653\",\n \"0.48667982\",\n \"0.48657286\",\n \"0.48644012\",\n \"0.4862329\",\n \"0.48615405\",\n \"0.48615298\",\n \"0.48541513\",\n \"0.4852577\",\n \"0.48500937\",\n \"0.485002\",\n \"0.48386562\",\n \"0.48275882\",\n \"0.48254207\",\n \"0.48205447\",\n \"0.48112366\",\n \"0.48061135\",\n \"0.48042753\",\n \"0.47995898\",\n \"0.4799266\",\n \"0.47946575\",\n \"0.47921014\",\n \"0.47917795\",\n \"0.4788765\",\n \"0.47854716\",\n \"0.4782754\",\n \"0.478019\",\n \"0.478019\",\n \"0.47764185\",\n \"0.47723618\",\n \"0.47721428\",\n \"0.47720838\",\n \"0.47700143\",\n \"0.47690904\",\n \"0.47649857\",\n \"0.4763742\",\n \"0.47608736\",\n \"0.47553214\",\n \"0.47547445\",\n \"0.47545776\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8232994"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":81477,"cells":{"query":{"kind":"string","value":"Determine if moleculeresiduespin data exists (when a single residue is numbered). The function tested is pipe_control.mol_res_spin.exists_mol_res_spin_data()."},"document":{"kind":"string","value":"def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def isExist(data):\n return True/False","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def hasResidue(self, resname):\n if resname in self.map:\n return 1\n else:\n return 0","def exists(self, number):\n\t\tslotIDList = [s.id for s in self.slotList]\n\t\ttry:\n\t\t\tindex = slotIDList.index(number)\n\t\t\treturn True\n\t\texcept ValueError:\n\t\t\treturn False\n\t\treturn False","def test_return_single_residue_info(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_single_residue_info('1')\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\n res5 = mol_res_spin.return_single_residue_info('-5')\n\n # Test the data of residue 1.\n self.assertEqual(res1, (1, None))\n\n # Test the data of residue 2.\n self.assertEqual(res2, (2, 'Glu'))\n\n # Test the data of residue 4.\n self.assertEqual(res4, (4, 'Pro'))\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5, (-5, None))","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def check_for_residue_existance(self):\n if not self.pose.total_residue():\n print \"No pose Loaded.\"\n return False\n\n if not self.current_chain.get() or not self.current_residue.get():\n print \"Chain or residue not set\"\n return False\n\n current_region = self.current_residue.get().split(\":\")\n if len(current_region)>1:\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\n\n\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\n print \"Region not found in pose\"\n return False\n else:\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\n\n print \"Residue not found in pose\"\n return False\n\n #If everythig is good then:\n return True","def has_data(self, fragment, number):\n if fragment in self.mdv:\n if number in self.mdv[fragment]:\n return True\n return False","def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def check_residue(self, chain_id, resid, resname):\n if resname in PTM_lookup.keys():\n return\n else:\n try:\n ref_resname = PTM_reverse_lookup[resname]\n except KeyError:\n # print \"skipping unrecognized residue\", resname\n return\n ptm_dict = PTM_lookup[ref_resname][resname]\n return (chain_id, resid, ref_resname, ptm_dict[\"goto_atom\"], ptm_dict[\"name\"])","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def test_return_residue(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_residue(':1')\n res2 = mol_res_spin.return_residue(selection=':2')\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\n\n # Test the data of residue 1.\n self.assertEqual(res1.num, 1)\n self.assertEqual(res1.name, None)\n\n # Test the data of residue 2.\n self.assertEqual(res2.num, 2)\n self.assertEqual(res2.name, 'Glu')\n\n # Test the data of residue 4.\n self.assertEqual(res4.num, 4)\n self.assertEqual(res4.name, 'Pro')\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5.num, -5)\n self.assertEqual(res5.name, None)\n self.assertEqual(res5.spin[1].name, 'N5')","def contains(self, seq_nr: str) -> bool:\n return bool(self.__data.get(seq_nr))","def has_data(self, time, fragment, number):\n if time in self.mdvtc.keys():\n if fragment in self.mdvtc[time].mdv.keys():\n if number in self.mdvtc[time].mdv[fragment].keys():\n return True\n return False","def test_count_no_spins(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 0)","def exists(sim):\n return (sim['N'] > 0)","def CheckForExistence(requested_data, available_data):\n if requested_data is not None:\n return 1 # The requested data exists.\n elif available_data:\n return -1 # The requested data does not exist.\n else:\n return 0 # No data exists at all.","def exists(self):\n\t\tif self.hasUdim:\n\t\t\treturn len( self.udimPaths ) != 0\n\t\treturn super( textureFile, self ).exists","def exists(self, datadir):\n return False","def file_exists(msl_data_path, filename):\n return os.path.isfile(msl_data_path + filename)","def isResidueAssigned(residue):\n\n for atom in residue.atoms:\n if atom.atomSet:\n if atom.atomSet.resonanceSets:\n return True\n \n return False","def IndexExists(self, arg0: 'unsigned long long') -> \"bool\":\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF3GQEULLULLBBT_IndexExists(self, arg0)","def test_residue_loop(self):\n\n # Loop over the residues.\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\n # Test the selection.\n self.assertEqual(res.num, 2)\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)","def test_molecule_loop(self):\n\n # Loop over the molecules.\n for mol in mol_res_spin.molecule_loop('#RNA'):\n # Test the molecule name.\n self.assertEqual(mol.name, 'RNA')\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)","def is_version_data_existed(self):\n # if exists, skip\n # return \n\n return True","def has_non_standard_residues(self):\n for frag in self.iter_non_standard_residues():\n return True\n return False","def IndexExists(self, arg0: 'unsigned long long') -> \"bool\":\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF2GQEULLULLBBT_IndexExists(self, arg0)","def has_mask(mask_name, path=None, data=None):\n if path is None and data is None:\n raise ValueError(\"Mask file not provided.\")\n if path:\n with open(path, 'r') as file:\n data = json.load(file)\n \n for inx, obj in enumerate(data[\"objects\"]):\n if obj['classTitle'] == mask_name:\n return inx\n \n return False","def is_present(self):\n try:\n self.read_binary(0, 2)\n return True\n except:\n return False","def test_molecule_loop_no_selection(self):\n\n # Molecule data.\n name = ['Ap4Aase', 'RNA']\n\n # Loop over the molecules.\n i = 0\n for mol in mol_res_spin.molecule_loop():\n # Test the molecule names.\n self.assertEqual(mol.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)","def datafolderexist(name):\n folderpath = os.path.join(pathtofolder(), name)\n return os.path.exists(folderpath)","def exists(self):\n try:\n self.world.find(self.ehandle)\n except KeyError:\n return False\n else:\n return True","def checkExistence(idMeta):\n # XXX add for diaries\n sqlq = \"\"\"\n SELECT dt\n FROM Electricity_10min\n WHERE `Meta_idMeta` = {}\n LIMIT 1;\n \"\"\".format(idMeta)\n try:\n result = mdb.getSQL(sqlq)[0]\n if (result):\n return True\n except:\n return False","def hasAtom(self, atomname):\n if atomname in self.atoms:\n return 1\n else:\n return 0","def test_return_single_residue_info_fail(self):\n\n # Ask for a few residues.\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')","def id_exists(test_name):\n result_json = None\n try:\n with open(robot_dir + \"/output/results/{}.json\".format(test_name.replace(' ', ''))) as result_file:\n result_json = json.load(result_file)\n except:\n print(\"Failed to open the result json\")\n return False\n #look for values NEW_ASSOC, NEW_PROP1, NEW_PROP2\n print(result_json)\n if 6 == 6:\n return True\n return \"Length is not 6\"","def test_is_in_ring(self):\n molecule = Molecule.from_smiles(\"c1ccccc1\")\n\n for atom in molecule.atoms:\n if atom.atomic_number == 6:\n assert atom.is_in_ring()\n\n for bond in molecule.bonds:\n if 1 in (bond.atom1.atomic_number, bond.atom2.atomic_number):\n continue\n assert bond.is_in_ring()","def has_standard_residues(self):\n for frag in self.iter_standard_residues():\n return True\n return False","def check_id_existence(self, id:str):\n\n oc_prefix = id[:(id.index(':')+1)]\n\n if oc_prefix == 'doi:':\n vldt = doi.DOIManager() # you can use removeprefix(oc_prefix) from Python 3.9+\n return vldt.exists(id.replace(oc_prefix, '', 1)) # todo: use id.replace(oc_prefix, '', 1) for Python < v.3.9\n if oc_prefix == 'isbn:':\n vldt = isbn.ISBNManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'issn:':\n vldt = issn.ISSNManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'orcid:':\n vldt = orcid.ORCIDManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'pmcid:':\n vldt = pmcid.PMCIDManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'pmid:':\n vldt = pmid.PMIDManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'ror:':\n vldt = ror.RORManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'url:':\n vldt = url.URLManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'viaf:':\n vldt = viaf.ViafManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'wikidata:':\n vldt = wikidata.WikidataManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))\n if oc_prefix == 'wikipedia:':\n vldt = wikipedia.WikipediaManager()\n return vldt.exists(id.replace(oc_prefix, '', 1))","def is_standard_residue(self):\n return False","def race_entry_exists(self, race_id):\n try:\n self.consolidated_db.data.loc[race_id] # Throws a KeyError if no entry is in the dataframe.\n return True\n except KeyError:\n return False","def _object_exists(name):\n conn = sqlite3.connect('/dev/input')\n try:\n cur = conn.cursor()\n sql = 'SELECT ROWID FROM object WHERE name=? AND deleted=0'\n cur.execute(sql, (name, ))\n result = cur.fetchall()\n return len(result) > 0\n finally:\n conn.close()","def test_run_molecule_not_selected(self, single_mol_system):\n sequence = \"ABCDE\"\n processor = dssp.AnnotateResidues(\n \"test\", sequence, molecule_selector=lambda mol: False\n )\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert vermouth.utils.are_all_equal(found)\n assert found[0] is None","def exists():\n\treturn os.path.exists('data/strmr.db')","def has_id(self, data):\n # (Dict[str, Any]) -> bool\n return self.id_column.name in data","def has_data(self):\n return len(self.data) > 0","def has_data(self) -> bool:\n raise NotImplementedError","def lookup_sync(self, flag=0):\n if flag == 1 or self.ser.read() == self.sync[3]:\n if self.ser.read() == self.sync[2]:\n if self.ser.read() == self.sync[1]:\n if self.ser.read() == self.sync[0]:\n return True\n elif self.ser.read() == self.sync[-1]:\n return self.lookup_sync(flag=1)\n else:\n return False\n elif self.ser.read() == self.sync[-1]:\n return self.lookup_sync(flag=1)\n else:\n return False\n elif self.ser.read() == self.sync[-1]:\n return self.lookup_sync(flag=1)\n else:\n return False\n else:\n return False","def contains_ring_idx(self, ring_idx):\n return ring_idx in self.rix","def item_exists(self, call_number):\n return call_number in self.item_list.keys()","def has_data(self):\n return self._data is not None","def object_exists(self, name: str):\n file_path = self.__get_file_path(name)\n return os.path.exists(file_path)","def object_exists(self, fname):\n return self.object_exists","def test_return_molecule(self):\n\n # Ask for a few molecules.\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\n\n # Test the data of molecule 1.\n self.assertEqual(mol1.name, 'Ap4Aase')\n\n # Test the data of molecule 2.\n self.assertEqual(mol2.name, 'RNA')","def particleExists(*args, **kwargs)->bool:\n pass","def checkIfStudyIdExists(self, study_id):\n try:\n con = self.getSFFDatabaseConnection()\n study_id_cnt=0\n db_output=con.cursor().callproc('check_if_study_id_exists',\n [study_id,study_id_cnt])\n if db_output[1]==0:\n return False\n else:\n return True\n except Exception, e:\n print 'Exception caught: %s.\\nThe error is: %s' % (type(e), str(e))\n return False","def check_model_exists(ckpt):\n expected_data = ckpt + \".data-00000-of-00001\"\n return os.path.exists(expected_data)","def hasError(self, pin):\r\n return bool(self.Mask & (0b1 << pin))","async def exists(self, tag_name):\n try:\n if await self.get_id(tag_name):\n return True\n except RtbDoesntExists:\n return False","def exists(identifier, network):\n foo = next(load(identifier, network), None)\n return foo is not None","def find_null(data, sub_reg):\r\n subreg_sqkm_data = data.loc[pd.IndexSlice[:, sub_reg, :], pd.IndexSlice['Sq Km']]\r\n if subreg_sqkm_data.isnull().values.any() == True:\r\n print(\"\\nSq km measurements are missing for:\")\r\n print(subreg_sqkm_data[subreg_sqkm_data.isnull()])\r\n else:\r\n print(\"\\nThere are no missing sq km values for this sub-region.\")","def is_data_present(self, cycle: int, bus_item: BusItem) -> bool:\n buffer = self.get_cycle_buffer(cycle)\n if self.component_subtype == \"PEGB\":\n return False\n #print(buffer)\n # for pe_id in buffer:\n # pe_buffer = buffer[pe_id]\n # # # TODO ad-hoc\n # # if isinstance(pe_buffer, deque):\n # # return False\n # #print(pe_buffer)\n #\n # pe_read_buffer = pe_buffer[\"read\"]\n # #print(pe_read_buffer)\n # for data in pe_read_buffer:\n # if data == bus_item:\n # return True\n elif self.component_subtype == \"PENB\":\n read_buffer = buffer[\"read\"]\n for entry in read_buffer:\n if entry == bus_item:\n return True\n else:\n for data in buffer:\n if data == bus_item:\n return True\n return False","def has_lone_molecule(self) -> bool:\n return self._has_stray_molecules()","def _exists(cursor, table, data):\n cursor.execute('SELECT 1 FROM {} WHERE ({}) = ({})'.format(table, *_query_fields(data)), data)\n return bool(cursor.fetchone())","def has_error(self):\r\n return self._arm.has_error","def test_generate_spin_id_data_array6(self):\n\n # The data.\n data = ['1', 'GLY', None, None]\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')","def pickleExists(name):\n fileNames = [f for f in os.listdir(PICKLE_DIR) if name in f]\n return not len(fileNames) == 0","def verify_object(self, data):\n rv = self.get(data[self.id_field])\n result = not is_404(rv)\n if result:\n for key, value in data:\n if not in_response(rv, value):\n return False\n return result","def _check_row_exists(self, pk):\n session = self.session_factory()\n exists = session.query(PipelineRun).filter_by(id=pk).first()\n session.close()\n if exists:\n return True\n return False","def is_data_by_filename(fname):\n return \"Run2017\" in fname","def isRenderable(data):\n return data.find(\"<molecule\") != -1 and data.find(\"<atom\") != -1","def pidExists(self, pid):\n\n prochash = self.getHash( 'datahash' ) # safely get copy of process dict\n\n try:\n prochash[pid]\n return 1\n except KeyError:\n return 0","def pidExists(self, pid):\n\n prochash = self.getHash( 'datahash' ) # safely get copy of process dict\n\n try:\n prochash[pid]\n return 1\n except KeyError:\n return 0","def test_generate_spin_id_data_array1(self):\n\n # The data.\n data = ['1', 'GLY']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')","def object_exists(self, fname):\n return False","def is_data_run(info, runinfo):\n this_run_in_runinfo = runinfo[\n (runinfo.fNight==info[\"night_int\"])&\n (runinfo.fRunID==info[\"run\"])\n ]\n return len(this_run_in_runinfo) > 0 and this_run_in_runinfo.iloc[0].fRunTypeKey == 1","def is_standard_residue(self):\n return True","def is_standard_residue(self):\n return True","def check_residue_callback(self):\n\n if not self.check_for_residue_existance():\n return\n\n self.listbox_current_designs.delete(0, END)\n self.current_residueFull = self.current_residue.get().split(\":\")\n\n if len(self.current_residueFull) > 1:\n self.listbox_restypes.delete(9)\n self.listbox_restypes.insert(9, \"Conserved\")\n else:\n res = self.current_residueFull[0] +\":\"+self.current_chain.get()\n #print res\n if not self.pose.total_residue():\n return\n\n resType = self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get()))\n try:\n resName = self.pose.residue(resType).name()\n except PyRosettaException:\n print \"Residue does not exist in PDB...\"\n return\n\n\n self.current_residue_name_full.set(resName)\n three_letter_name = resName.split(\"_\")[0]; #Fix for Rosetta designated chain endings, His_d\n self.current_residue_name.set(resName)\n\n #Fix for not having data for certain residue types:\n try:\n self.design_accessible_sa.set(self.residue_definitions.resinfo[three_letter_name][0])\n self.design_relative_mutability.set(self.residue_definitions.resinfo[three_letter_name][1])\n self.design_surface_probability.set(self.residue_definitions.resinfo[three_letter_name][2])\n except KeyError:\n print \"No Data for restype\"\n self.design_accessible_sa.set(\"\")\n self.design_relative_mutability.set(\"\")\n self.design_surface_probability.set(\"\")\n\n con = \"Conserved:\" +three_letter_name\n self.listbox_restypes.delete(9)\n self.listbox_restypes.insert(9, con)\n if self.DesignDic.has_key(res):\n for residues in self.DesignDic[res]:\n self.listbox_current_designs.insert(END, residues)","def is_section_exist(self, section_name: str) -> bool:\n success = False\n try:\n self._vault_api.read_secret(path=section_name.upper(), mount_point=self.mount_point)\n success = True\n except InvalidPath:\n pass\n return success","def validate_perturbed_residues(molecule, perturbed):\n length = len(molecule)\n numPerturbed = len(perturbed)\n #if ","def has_data(self) -> bool:\n return bool(self.data)","def datafileexist(filename):\n filePath = os.path.join(pathtofolder(), \"datas\", filename)\n fileFormat = '.csv'\n return os.path.exists(f'{filePath+fileFormat}')","def has_data(self):\n\n return self._data is not None","def has_data(self):\n\n return self._data is not None","def object_exists(self, fname):\n return True","def check_file_existing(k_out, sphere_radius,full_path):\n cwd = full_path\n file_names = ['/T_ns_', '/Energy_', '/Distance-e-to-e_',\n '/chain_on_iterations_']\n\n kout = f'{k_out:.3f}'\n spr_rad = f'{sphere_radius:.3f}'\n\n current = \"kout_\" + kout + \"_\" + \"spr_rad_\" + spr_rad\n for file_name in file_names:\n #print (cwd + file_name + current + \".pkl\")\n if not os.path.exists(cwd + file_name + current + \".pkl\"):\n return False\n return True","def contains(self, key: int) -> bool:\n return key in self.data[key % self._MOD]","def exists (self, uuid):\n return self.read (uuid) is not None","def exists(self):\r\n return os.path.exists(self.full_path)","def notebook_exists(self, name, path=''):\n\n\t\tos_path = self._get_os_path(name, path=path)\n\t\treturn key_exists(self.bucket, os_path)","def check_pin(self, card_number, pin):\n database_cursor.execute(f\"SELECT pin FROM card WHERE number = {card_number};\")\n result = database_cursor.fetchall()\n print(result)\n return result[0][0] == pin"],"string":"[\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def isExist(data):\\n return True/False\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def hasResidue(self, resname):\\n if resname in self.map:\\n return 1\\n else:\\n return 0\",\n \"def exists(self, number):\\n\\t\\tslotIDList = [s.id for s in self.slotList]\\n\\t\\ttry:\\n\\t\\t\\tindex = slotIDList.index(number)\\n\\t\\t\\treturn True\\n\\t\\texcept ValueError:\\n\\t\\t\\treturn False\\n\\t\\treturn False\",\n \"def test_return_single_residue_info(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_single_residue_info('1')\\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\\n res5 = mol_res_spin.return_single_residue_info('-5')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1, (1, None))\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2, (2, 'Glu'))\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4, (4, 'Pro'))\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5, (-5, None))\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def check_for_residue_existance(self):\\n if not self.pose.total_residue():\\n print \\\"No pose Loaded.\\\"\\n return False\\n\\n if not self.current_chain.get() or not self.current_residue.get():\\n print \\\"Chain or residue not set\\\"\\n return False\\n\\n current_region = self.current_residue.get().split(\\\":\\\")\\n if len(current_region)>1:\\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\\n\\n\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\\n print \\\"Region not found in pose\\\"\\n return False\\n else:\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\\n\\n print \\\"Residue not found in pose\\\"\\n return False\\n\\n #If everythig is good then:\\n return True\",\n \"def has_data(self, fragment, number):\\n if fragment in self.mdv:\\n if number in self.mdv[fragment]:\\n return True\\n return False\",\n \"def test_molecule_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the molecules.\\n i = 0\\n for molecule in mol_res_spin.molecule_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def check_residue(self, chain_id, resid, resname):\\n if resname in PTM_lookup.keys():\\n return\\n else:\\n try:\\n ref_resname = PTM_reverse_lookup[resname]\\n except KeyError:\\n # print \\\"skipping unrecognized residue\\\", resname\\n return\\n ptm_dict = PTM_lookup[ref_resname][resname]\\n return (chain_id, resid, ref_resname, ptm_dict[\\\"goto_atom\\\"], ptm_dict[\\\"name\\\"])\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def test_return_residue(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_residue(':1')\\n res2 = mol_res_spin.return_residue(selection=':2')\\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1.num, 1)\\n self.assertEqual(res1.name, None)\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2.num, 2)\\n self.assertEqual(res2.name, 'Glu')\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4.num, 4)\\n self.assertEqual(res4.name, 'Pro')\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5.num, -5)\\n self.assertEqual(res5.name, None)\\n self.assertEqual(res5.spin[1].name, 'N5')\",\n \"def contains(self, seq_nr: str) -> bool:\\n return bool(self.__data.get(seq_nr))\",\n \"def has_data(self, time, fragment, number):\\n if time in self.mdvtc.keys():\\n if fragment in self.mdvtc[time].mdv.keys():\\n if number in self.mdvtc[time].mdv[fragment].keys():\\n return True\\n return False\",\n \"def test_count_no_spins(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Test the number of spins counted.\\n self.assertEqual(mol_res_spin.count_spins(), 0)\",\n \"def exists(sim):\\n return (sim['N'] > 0)\",\n \"def CheckForExistence(requested_data, available_data):\\n if requested_data is not None:\\n return 1 # The requested data exists.\\n elif available_data:\\n return -1 # The requested data does not exist.\\n else:\\n return 0 # No data exists at all.\",\n \"def exists(self):\\n\\t\\tif self.hasUdim:\\n\\t\\t\\treturn len( self.udimPaths ) != 0\\n\\t\\treturn super( textureFile, self ).exists\",\n \"def exists(self, datadir):\\n return False\",\n \"def file_exists(msl_data_path, filename):\\n return os.path.isfile(msl_data_path + filename)\",\n \"def isResidueAssigned(residue):\\n\\n for atom in residue.atoms:\\n if atom.atomSet:\\n if atom.atomSet.resonanceSets:\\n return True\\n \\n return False\",\n \"def IndexExists(self, arg0: 'unsigned long long') -> \\\"bool\\\":\\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF3GQEULLULLBBT_IndexExists(self, arg0)\",\n \"def test_residue_loop(self):\\n\\n # Loop over the residues.\\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\\n # Test the selection.\\n self.assertEqual(res.num, 2)\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)\",\n \"def test_molecule_loop(self):\\n\\n # Loop over the molecules.\\n for mol in mol_res_spin.molecule_loop('#RNA'):\\n # Test the molecule name.\\n self.assertEqual(mol.name, 'RNA')\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)\",\n \"def is_version_data_existed(self):\\n # if exists, skip\\n # return \\n\\n return True\",\n \"def has_non_standard_residues(self):\\n for frag in self.iter_non_standard_residues():\\n return True\\n return False\",\n \"def IndexExists(self, arg0: 'unsigned long long') -> \\\"bool\\\":\\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF2GQEULLULLBBT_IndexExists(self, arg0)\",\n \"def has_mask(mask_name, path=None, data=None):\\n if path is None and data is None:\\n raise ValueError(\\\"Mask file not provided.\\\")\\n if path:\\n with open(path, 'r') as file:\\n data = json.load(file)\\n \\n for inx, obj in enumerate(data[\\\"objects\\\"]):\\n if obj['classTitle'] == mask_name:\\n return inx\\n \\n return False\",\n \"def is_present(self):\\n try:\\n self.read_binary(0, 2)\\n return True\\n except:\\n return False\",\n \"def test_molecule_loop_no_selection(self):\\n\\n # Molecule data.\\n name = ['Ap4Aase', 'RNA']\\n\\n # Loop over the molecules.\\n i = 0\\n for mol in mol_res_spin.molecule_loop():\\n # Test the molecule names.\\n self.assertEqual(mol.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)\",\n \"def datafolderexist(name):\\n folderpath = os.path.join(pathtofolder(), name)\\n return os.path.exists(folderpath)\",\n \"def exists(self):\\n try:\\n self.world.find(self.ehandle)\\n except KeyError:\\n return False\\n else:\\n return True\",\n \"def checkExistence(idMeta):\\n # XXX add for diaries\\n sqlq = \\\"\\\"\\\"\\n SELECT dt\\n FROM Electricity_10min\\n WHERE `Meta_idMeta` = {}\\n LIMIT 1;\\n \\\"\\\"\\\".format(idMeta)\\n try:\\n result = mdb.getSQL(sqlq)[0]\\n if (result):\\n return True\\n except:\\n return False\",\n \"def hasAtom(self, atomname):\\n if atomname in self.atoms:\\n return 1\\n else:\\n return 0\",\n \"def test_return_single_residue_info_fail(self):\\n\\n # Ask for a few residues.\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')\",\n \"def id_exists(test_name):\\n result_json = None\\n try:\\n with open(robot_dir + \\\"/output/results/{}.json\\\".format(test_name.replace(' ', ''))) as result_file:\\n result_json = json.load(result_file)\\n except:\\n print(\\\"Failed to open the result json\\\")\\n return False\\n #look for values NEW_ASSOC, NEW_PROP1, NEW_PROP2\\n print(result_json)\\n if 6 == 6:\\n return True\\n return \\\"Length is not 6\\\"\",\n \"def test_is_in_ring(self):\\n molecule = Molecule.from_smiles(\\\"c1ccccc1\\\")\\n\\n for atom in molecule.atoms:\\n if atom.atomic_number == 6:\\n assert atom.is_in_ring()\\n\\n for bond in molecule.bonds:\\n if 1 in (bond.atom1.atomic_number, bond.atom2.atomic_number):\\n continue\\n assert bond.is_in_ring()\",\n \"def has_standard_residues(self):\\n for frag in self.iter_standard_residues():\\n return True\\n return False\",\n \"def check_id_existence(self, id:str):\\n\\n oc_prefix = id[:(id.index(':')+1)]\\n\\n if oc_prefix == 'doi:':\\n vldt = doi.DOIManager() # you can use removeprefix(oc_prefix) from Python 3.9+\\n return vldt.exists(id.replace(oc_prefix, '', 1)) # todo: use id.replace(oc_prefix, '', 1) for Python < v.3.9\\n if oc_prefix == 'isbn:':\\n vldt = isbn.ISBNManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'issn:':\\n vldt = issn.ISSNManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'orcid:':\\n vldt = orcid.ORCIDManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'pmcid:':\\n vldt = pmcid.PMCIDManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'pmid:':\\n vldt = pmid.PMIDManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'ror:':\\n vldt = ror.RORManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'url:':\\n vldt = url.URLManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'viaf:':\\n vldt = viaf.ViafManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'wikidata:':\\n vldt = wikidata.WikidataManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\\n if oc_prefix == 'wikipedia:':\\n vldt = wikipedia.WikipediaManager()\\n return vldt.exists(id.replace(oc_prefix, '', 1))\",\n \"def is_standard_residue(self):\\n return False\",\n \"def race_entry_exists(self, race_id):\\n try:\\n self.consolidated_db.data.loc[race_id] # Throws a KeyError if no entry is in the dataframe.\\n return True\\n except KeyError:\\n return False\",\n \"def _object_exists(name):\\n conn = sqlite3.connect('/dev/input')\\n try:\\n cur = conn.cursor()\\n sql = 'SELECT ROWID FROM object WHERE name=? AND deleted=0'\\n cur.execute(sql, (name, ))\\n result = cur.fetchall()\\n return len(result) > 0\\n finally:\\n conn.close()\",\n \"def test_run_molecule_not_selected(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\", sequence, molecule_selector=lambda mol: False\\n )\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert vermouth.utils.are_all_equal(found)\\n assert found[0] is None\",\n \"def exists():\\n\\treturn os.path.exists('data/strmr.db')\",\n \"def has_id(self, data):\\n # (Dict[str, Any]) -> bool\\n return self.id_column.name in data\",\n \"def has_data(self):\\n return len(self.data) > 0\",\n \"def has_data(self) -> bool:\\n raise NotImplementedError\",\n \"def lookup_sync(self, flag=0):\\n if flag == 1 or self.ser.read() == self.sync[3]:\\n if self.ser.read() == self.sync[2]:\\n if self.ser.read() == self.sync[1]:\\n if self.ser.read() == self.sync[0]:\\n return True\\n elif self.ser.read() == self.sync[-1]:\\n return self.lookup_sync(flag=1)\\n else:\\n return False\\n elif self.ser.read() == self.sync[-1]:\\n return self.lookup_sync(flag=1)\\n else:\\n return False\\n elif self.ser.read() == self.sync[-1]:\\n return self.lookup_sync(flag=1)\\n else:\\n return False\\n else:\\n return False\",\n \"def contains_ring_idx(self, ring_idx):\\n return ring_idx in self.rix\",\n \"def item_exists(self, call_number):\\n return call_number in self.item_list.keys()\",\n \"def has_data(self):\\n return self._data is not None\",\n \"def object_exists(self, name: str):\\n file_path = self.__get_file_path(name)\\n return os.path.exists(file_path)\",\n \"def object_exists(self, fname):\\n return self.object_exists\",\n \"def test_return_molecule(self):\\n\\n # Ask for a few molecules.\\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\\n\\n # Test the data of molecule 1.\\n self.assertEqual(mol1.name, 'Ap4Aase')\\n\\n # Test the data of molecule 2.\\n self.assertEqual(mol2.name, 'RNA')\",\n \"def particleExists(*args, **kwargs)->bool:\\n pass\",\n \"def checkIfStudyIdExists(self, study_id):\\n try:\\n con = self.getSFFDatabaseConnection()\\n study_id_cnt=0\\n db_output=con.cursor().callproc('check_if_study_id_exists',\\n [study_id,study_id_cnt])\\n if db_output[1]==0:\\n return False\\n else:\\n return True\\n except Exception, e:\\n print 'Exception caught: %s.\\\\nThe error is: %s' % (type(e), str(e))\\n return False\",\n \"def check_model_exists(ckpt):\\n expected_data = ckpt + \\\".data-00000-of-00001\\\"\\n return os.path.exists(expected_data)\",\n \"def hasError(self, pin):\\r\\n return bool(self.Mask & (0b1 << pin))\",\n \"async def exists(self, tag_name):\\n try:\\n if await self.get_id(tag_name):\\n return True\\n except RtbDoesntExists:\\n return False\",\n \"def exists(identifier, network):\\n foo = next(load(identifier, network), None)\\n return foo is not None\",\n \"def find_null(data, sub_reg):\\r\\n subreg_sqkm_data = data.loc[pd.IndexSlice[:, sub_reg, :], pd.IndexSlice['Sq Km']]\\r\\n if subreg_sqkm_data.isnull().values.any() == True:\\r\\n print(\\\"\\\\nSq km measurements are missing for:\\\")\\r\\n print(subreg_sqkm_data[subreg_sqkm_data.isnull()])\\r\\n else:\\r\\n print(\\\"\\\\nThere are no missing sq km values for this sub-region.\\\")\",\n \"def is_data_present(self, cycle: int, bus_item: BusItem) -> bool:\\n buffer = self.get_cycle_buffer(cycle)\\n if self.component_subtype == \\\"PEGB\\\":\\n return False\\n #print(buffer)\\n # for pe_id in buffer:\\n # pe_buffer = buffer[pe_id]\\n # # # TODO ad-hoc\\n # # if isinstance(pe_buffer, deque):\\n # # return False\\n # #print(pe_buffer)\\n #\\n # pe_read_buffer = pe_buffer[\\\"read\\\"]\\n # #print(pe_read_buffer)\\n # for data in pe_read_buffer:\\n # if data == bus_item:\\n # return True\\n elif self.component_subtype == \\\"PENB\\\":\\n read_buffer = buffer[\\\"read\\\"]\\n for entry in read_buffer:\\n if entry == bus_item:\\n return True\\n else:\\n for data in buffer:\\n if data == bus_item:\\n return True\\n return False\",\n \"def has_lone_molecule(self) -> bool:\\n return self._has_stray_molecules()\",\n \"def _exists(cursor, table, data):\\n cursor.execute('SELECT 1 FROM {} WHERE ({}) = ({})'.format(table, *_query_fields(data)), data)\\n return bool(cursor.fetchone())\",\n \"def has_error(self):\\r\\n return self._arm.has_error\",\n \"def test_generate_spin_id_data_array6(self):\\n\\n # The data.\\n data = ['1', 'GLY', None, None]\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\\n\\n # Test the string.\\n self.assertEqual(id, ':1')\",\n \"def pickleExists(name):\\n fileNames = [f for f in os.listdir(PICKLE_DIR) if name in f]\\n return not len(fileNames) == 0\",\n \"def verify_object(self, data):\\n rv = self.get(data[self.id_field])\\n result = not is_404(rv)\\n if result:\\n for key, value in data:\\n if not in_response(rv, value):\\n return False\\n return result\",\n \"def _check_row_exists(self, pk):\\n session = self.session_factory()\\n exists = session.query(PipelineRun).filter_by(id=pk).first()\\n session.close()\\n if exists:\\n return True\\n return False\",\n \"def is_data_by_filename(fname):\\n return \\\"Run2017\\\" in fname\",\n \"def isRenderable(data):\\n return data.find(\\\"<molecule\\\") != -1 and data.find(\\\"<atom\\\") != -1\",\n \"def pidExists(self, pid):\\n\\n prochash = self.getHash( 'datahash' ) # safely get copy of process dict\\n\\n try:\\n prochash[pid]\\n return 1\\n except KeyError:\\n return 0\",\n \"def pidExists(self, pid):\\n\\n prochash = self.getHash( 'datahash' ) # safely get copy of process dict\\n\\n try:\\n prochash[pid]\\n return 1\\n except KeyError:\\n return 0\",\n \"def test_generate_spin_id_data_array1(self):\\n\\n # The data.\\n data = ['1', 'GLY']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\\n\\n # Test the string.\\n self.assertEqual(id, ':1')\",\n \"def object_exists(self, fname):\\n return False\",\n \"def is_data_run(info, runinfo):\\n this_run_in_runinfo = runinfo[\\n (runinfo.fNight==info[\\\"night_int\\\"])&\\n (runinfo.fRunID==info[\\\"run\\\"])\\n ]\\n return len(this_run_in_runinfo) > 0 and this_run_in_runinfo.iloc[0].fRunTypeKey == 1\",\n \"def is_standard_residue(self):\\n return True\",\n \"def is_standard_residue(self):\\n return True\",\n \"def check_residue_callback(self):\\n\\n if not self.check_for_residue_existance():\\n return\\n\\n self.listbox_current_designs.delete(0, END)\\n self.current_residueFull = self.current_residue.get().split(\\\":\\\")\\n\\n if len(self.current_residueFull) > 1:\\n self.listbox_restypes.delete(9)\\n self.listbox_restypes.insert(9, \\\"Conserved\\\")\\n else:\\n res = self.current_residueFull[0] +\\\":\\\"+self.current_chain.get()\\n #print res\\n if not self.pose.total_residue():\\n return\\n\\n resType = self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get()))\\n try:\\n resName = self.pose.residue(resType).name()\\n except PyRosettaException:\\n print \\\"Residue does not exist in PDB...\\\"\\n return\\n\\n\\n self.current_residue_name_full.set(resName)\\n three_letter_name = resName.split(\\\"_\\\")[0]; #Fix for Rosetta designated chain endings, His_d\\n self.current_residue_name.set(resName)\\n\\n #Fix for not having data for certain residue types:\\n try:\\n self.design_accessible_sa.set(self.residue_definitions.resinfo[three_letter_name][0])\\n self.design_relative_mutability.set(self.residue_definitions.resinfo[three_letter_name][1])\\n self.design_surface_probability.set(self.residue_definitions.resinfo[three_letter_name][2])\\n except KeyError:\\n print \\\"No Data for restype\\\"\\n self.design_accessible_sa.set(\\\"\\\")\\n self.design_relative_mutability.set(\\\"\\\")\\n self.design_surface_probability.set(\\\"\\\")\\n\\n con = \\\"Conserved:\\\" +three_letter_name\\n self.listbox_restypes.delete(9)\\n self.listbox_restypes.insert(9, con)\\n if self.DesignDic.has_key(res):\\n for residues in self.DesignDic[res]:\\n self.listbox_current_designs.insert(END, residues)\",\n \"def is_section_exist(self, section_name: str) -> bool:\\n success = False\\n try:\\n self._vault_api.read_secret(path=section_name.upper(), mount_point=self.mount_point)\\n success = True\\n except InvalidPath:\\n pass\\n return success\",\n \"def validate_perturbed_residues(molecule, perturbed):\\n length = len(molecule)\\n numPerturbed = len(perturbed)\\n #if \",\n \"def has_data(self) -> bool:\\n return bool(self.data)\",\n \"def datafileexist(filename):\\n filePath = os.path.join(pathtofolder(), \\\"datas\\\", filename)\\n fileFormat = '.csv'\\n return os.path.exists(f'{filePath+fileFormat}')\",\n \"def has_data(self):\\n\\n return self._data is not None\",\n \"def has_data(self):\\n\\n return self._data is not None\",\n \"def object_exists(self, fname):\\n return True\",\n \"def check_file_existing(k_out, sphere_radius,full_path):\\n cwd = full_path\\n file_names = ['/T_ns_', '/Energy_', '/Distance-e-to-e_',\\n '/chain_on_iterations_']\\n\\n kout = f'{k_out:.3f}'\\n spr_rad = f'{sphere_radius:.3f}'\\n\\n current = \\\"kout_\\\" + kout + \\\"_\\\" + \\\"spr_rad_\\\" + spr_rad\\n for file_name in file_names:\\n #print (cwd + file_name + current + \\\".pkl\\\")\\n if not os.path.exists(cwd + file_name + current + \\\".pkl\\\"):\\n return False\\n return True\",\n \"def contains(self, key: int) -> bool:\\n return key in self.data[key % self._MOD]\",\n \"def exists (self, uuid):\\n return self.read (uuid) is not None\",\n \"def exists(self):\\r\\n return os.path.exists(self.full_path)\",\n \"def notebook_exists(self, name, path=''):\\n\\n\\t\\tos_path = self._get_os_path(name, path=path)\\n\\t\\treturn key_exists(self.bucket, os_path)\",\n \"def check_pin(self, card_number, pin):\\n database_cursor.execute(f\\\"SELECT pin FROM card WHERE number = {card_number};\\\")\\n result = database_cursor.fetchall()\\n print(result)\\n return result[0][0] == pin\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.84456354","0.82298267","0.8103048","0.79645956","0.79151535","0.77068615","0.6438838","0.6125528","0.6099552","0.5864683","0.57085097","0.5695363","0.5664928","0.55890244","0.55634105","0.5563084","0.5443872","0.5368424","0.53031784","0.52392286","0.51996315","0.5196843","0.51857466","0.5152284","0.5138617","0.5128279","0.5093066","0.5089089","0.5082572","0.5034413","0.50284654","0.5011257","0.50048465","0.4994763","0.4988176","0.49664694","0.4920419","0.4899246","0.48946112","0.48639914","0.48597467","0.48511195","0.48487946","0.4834712","0.48343724","0.48326963","0.48270947","0.48153344","0.48137128","0.47999707","0.4799783","0.47988078","0.47986013","0.47910193","0.47845072","0.4784424","0.47672492","0.4765287","0.47649592","0.47619885","0.47603056","0.47553596","0.4747467","0.47373736","0.47372913","0.47358072","0.47348586","0.47303337","0.47289446","0.4728379","0.47283474","0.47278193","0.4725916","0.4722491","0.47209215","0.47205305","0.4716785","0.47135073","0.47132444","0.4707685","0.4707685","0.47030553","0.47029337","0.4701298","0.46974564","0.46974564","0.46919194","0.46891528","0.46885633","0.46871367","0.46831068","0.46777126","0.46777126","0.46739495","0.46464646","0.464509","0.46434528","0.46401808","0.46389025","0.46277937"],"string":"[\n \"0.84456354\",\n \"0.82298267\",\n \"0.8103048\",\n \"0.79645956\",\n \"0.79151535\",\n \"0.77068615\",\n \"0.6438838\",\n \"0.6125528\",\n \"0.6099552\",\n \"0.5864683\",\n \"0.57085097\",\n \"0.5695363\",\n \"0.5664928\",\n \"0.55890244\",\n \"0.55634105\",\n \"0.5563084\",\n \"0.5443872\",\n \"0.5368424\",\n \"0.53031784\",\n \"0.52392286\",\n \"0.51996315\",\n \"0.5196843\",\n \"0.51857466\",\n \"0.5152284\",\n \"0.5138617\",\n \"0.5128279\",\n \"0.5093066\",\n \"0.5089089\",\n \"0.5082572\",\n \"0.5034413\",\n \"0.50284654\",\n \"0.5011257\",\n \"0.50048465\",\n \"0.4994763\",\n \"0.4988176\",\n \"0.49664694\",\n \"0.4920419\",\n \"0.4899246\",\n \"0.48946112\",\n \"0.48639914\",\n \"0.48597467\",\n \"0.48511195\",\n \"0.48487946\",\n \"0.4834712\",\n \"0.48343724\",\n \"0.48326963\",\n \"0.48270947\",\n \"0.48153344\",\n \"0.48137128\",\n \"0.47999707\",\n \"0.4799783\",\n \"0.47988078\",\n \"0.47986013\",\n \"0.47910193\",\n \"0.47845072\",\n \"0.4784424\",\n \"0.47672492\",\n \"0.4765287\",\n \"0.47649592\",\n \"0.47619885\",\n \"0.47603056\",\n \"0.47553596\",\n \"0.4747467\",\n \"0.47373736\",\n \"0.47372913\",\n \"0.47358072\",\n \"0.47348586\",\n \"0.47303337\",\n \"0.47289446\",\n \"0.4728379\",\n \"0.47283474\",\n \"0.47278193\",\n \"0.4725916\",\n \"0.4722491\",\n \"0.47209215\",\n \"0.47205305\",\n \"0.4716785\",\n \"0.47135073\",\n \"0.47132444\",\n \"0.4707685\",\n \"0.4707685\",\n \"0.47030553\",\n \"0.47029337\",\n \"0.4701298\",\n \"0.46974564\",\n \"0.46974564\",\n \"0.46919194\",\n \"0.46891528\",\n \"0.46885633\",\n \"0.46871367\",\n \"0.46831068\",\n \"0.46777126\",\n \"0.46777126\",\n \"0.46739495\",\n \"0.46464646\",\n \"0.464509\",\n \"0.46434528\",\n \"0.46401808\",\n \"0.46389025\",\n \"0.46277937\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8403741"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":81478,"cells":{"query":{"kind":"string","value":"Determine if moleculeresiduespin data exists (when a single spin is named). The function tested is pipe_control.mol_res_spin.exists_mol_res_spin_data()."},"document":{"kind":"string","value":"def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def isExist(data):\n return True/False","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def hasResidue(self, resname):\n if resname in self.map:\n return 1\n else:\n return 0","def datafolderexist(name):\n folderpath = os.path.join(pathtofolder(), name)\n return os.path.exists(folderpath)","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def object_exists(self, name: str):\n file_path = self.__get_file_path(name)\n return os.path.exists(file_path)","def file_exists(msl_data_path, filename):\n return os.path.isfile(msl_data_path + filename)","def exists(self):\n\t\tif self.hasUdim:\n\t\t\treturn len( self.udimPaths ) != 0\n\t\treturn super( textureFile, self ).exists","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def exists(self, name):\n assert name, \"Must input a valid dataset name.\"\n return name in self.manager.data[\"dataset\"]","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def exists(self, datadir):\n return False","def CheckForExistence(requested_data, available_data):\n if requested_data is not None:\n return 1 # The requested data exists.\n elif available_data:\n return -1 # The requested data does not exist.\n else:\n return 0 # No data exists at all.","def check_name_in_file(name_to_check, data):\r\n if name_to_check in data:\r\n return True\r\n return False","def exists(dtype, name, rootdir=None):\n return FreezableAPI.to_slug(dtype,name) in FreezableAPI.datasets(rootdir=rootdir)","def is_section_exist(self, section_name: str) -> bool:\n success = False\n try:\n self._vault_api.read_secret(path=section_name.upper(), mount_point=self.mount_point)\n success = True\n except InvalidPath:\n pass\n return success","def datafileexist(filename):\n filePath = os.path.join(pathtofolder(), \"datas\", filename)\n fileFormat = '.csv'\n return os.path.exists(f'{filePath+fileFormat}')","def pickleExists(name):\n fileNames = [f for f in os.listdir(PICKLE_DIR) if name in f]\n return not len(fileNames) == 0","async def exists(self, tag_name):\n try:\n if await self.get_id(tag_name):\n return True\n except RtbDoesntExists:\n return False","def check_if_file_exists(self, sensor_id:str, name:str)->str:\n ret_value = \"\"\n file_name = '%s/%s.*.%s.json' % (self.generate_data_prep, sensor_id, name)\n try: \n ret_value = glob.glob(file_name)\n except Exception as e:\n print(\"OSError - Failed top get file (%s) - %s\" % (file_name, e))\n ret_value = False \n \n if ret_value != False and len(ret_value) > 0: \n ret_value = ret_value[0]\n\n return ret_value","def exists(self, name):\n full_path = self.path(name)\n return self.__volume.exists(full_path)","def has_data(self, fragment, number):\n if fragment in self.mdv:\n if number in self.mdv[fragment]:\n return True\n return False","def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def data_available(dataset_name=None):\r\n for file_list in data_resources[dataset_name]['files']:\r\n for file in file_list:\r\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\r\n return False\r\n return True","def is_version_data_existed(self):\n # if exists, skip\n # return \n\n return True","def _object_exists(name):\n conn = sqlite3.connect('/dev/input')\n try:\n cur = conn.cursor()\n sql = 'SELECT ROWID FROM object WHERE name=? AND deleted=0'\n cur.execute(sql, (name, ))\n result = cur.fetchall()\n return len(result) > 0\n finally:\n conn.close()","def object_exists(self, fname):\n return self.object_exists","def is_data_by_filename(fname):\n return \"Run2017\" in fname","def has_material(obj, name):\n return name in obj.data.materials.keys()","def has_data(self) -> bool:\n raise NotImplementedError","def __in_delete_serial_name(self, name):\n # Open the delete .csv file\n # Initialize the reader\n # For a row in the reader,\n # If the checking name is in the row, \n # return True\n # Return False if the name is not found\n input_filename = \"HobowareDeleteSerial.csv\"\n input_file = open(os.path.join('Hobowarebin',input_filename), \"r\")\n reader = csv.reader(input_file, delimiter = \",\")\n \n for input_row in reader:\n if name in input_row:\n return True\n \n input_file.close()\n \n return False","def object_exists(self, fname):\n return True","def object_exists(self, fname):\n return False","def has_data(self):\n return self._data is not None","def exists(self):\n try:\n self.world.find(self.ehandle)\n except KeyError:\n return False\n else:\n return True","def exists(self, name):\n try:\n self.container.get_object(name)\n return True\n except NoSuchObject:\n return False","def exists(self, name):\n self.connect()\n self._write('EXISTS %s\\r\\n' % name)\n return self._get_numeric_response()","def exists(self):\n return os.path.exists(self.sensorpath)","def test_return_single_residue_info(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_single_residue_info('1')\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\n res5 = mol_res_spin.return_single_residue_info('-5')\n\n # Test the data of residue 1.\n self.assertEqual(res1, (1, None))\n\n # Test the data of residue 2.\n self.assertEqual(res2, (2, 'Glu'))\n\n # Test the data of residue 4.\n self.assertEqual(res4, (4, 'Pro'))\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5, (-5, None))","def has_name(self):\n return self.unpack_word(0x2) != 0","def has_mask(mask_name, path=None, data=None):\n if path is None and data is None:\n raise ValueError(\"Mask file not provided.\")\n if path:\n with open(path, 'r') as file:\n data = json.load(file)\n \n for inx, obj in enumerate(data[\"objects\"]):\n if obj['classTitle'] == mask_name:\n return inx\n \n return False","def exists(self):\n\n return os.path.exists(self[\"~filename\"])","def check_residue(self, chain_id, resid, resname):\n if resname in PTM_lookup.keys():\n return\n else:\n try:\n ref_resname = PTM_reverse_lookup[resname]\n except KeyError:\n # print \"skipping unrecognized residue\", resname\n return\n ptm_dict = PTM_lookup[ref_resname][resname]\n return (chain_id, resid, ref_resname, ptm_dict[\"goto_atom\"], ptm_dict[\"name\"])","def has_data(self, time, fragment, number):\n if time in self.mdvtc.keys():\n if fragment in self.mdvtc[time].mdv.keys():\n if number in self.mdvtc[time].mdv[fragment].keys():\n return True\n return False","def has_data(self) -> bool:\n return bool(self.data)","def check_model_exists(ckpt):\n expected_data = ckpt + \".data-00000-of-00001\"\n return os.path.exists(expected_data)","def test_count_no_spins(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 0)","def has_data(self):\n\n return self._data is not None","def has_data(self):\n\n return self._data is not None","def exists(self, number):\n\t\tslotIDList = [s.id for s in self.slotList]\n\t\ttry:\n\t\t\tindex = slotIDList.index(number)\n\t\t\treturn True\n\t\texcept ValueError:\n\t\t\treturn False\n\t\treturn False","def check_file_existing(k_out, sphere_radius,full_path):\n cwd = full_path\n file_names = ['/T_ns_', '/Energy_', '/Distance-e-to-e_',\n '/chain_on_iterations_']\n\n kout = f'{k_out:.3f}'\n spr_rad = f'{sphere_radius:.3f}'\n\n current = \"kout_\" + kout + \"_\" + \"spr_rad_\" + spr_rad\n for file_name in file_names:\n #print (cwd + file_name + current + \".pkl\")\n if not os.path.exists(cwd + file_name + current + \".pkl\"):\n return False\n return True","def has_data(self):\n return len(self.data) > 0","def exists(self) -> bool:\n try:\n result = self.get()\n except KeyError:\n return False\n return True","def check_for_residue_existance(self):\n if not self.pose.total_residue():\n print \"No pose Loaded.\"\n return False\n\n if not self.current_chain.get() or not self.current_residue.get():\n print \"Chain or residue not set\"\n return False\n\n current_region = self.current_residue.get().split(\":\")\n if len(current_region)>1:\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\n\n\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\n print \"Region not found in pose\"\n return False\n else:\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\n\n print \"Residue not found in pose\"\n return False\n\n #If everythig is good then:\n return True","def check_data_exist(data):\n if data is not None:\n if data.text is not None:\n return True\n return False","def exists():\n\treturn os.path.exists('data/strmr.db')","def volume_exists(vil, vol_name):\n\n exists = False\n try:\n if not vil:\n vil, err = get_basic_volume_info_all()\n if err:\n raise Exception(err)\n if vil:\n for v in vil:\n if v[\"name\"] == vol_name:\n exists = True\n except Exception, e:\n return False, 'Error checking for volume existance : %s' % str(e)\n else:\n return exists, None","def checkExistence(idMeta):\n # XXX add for diaries\n sqlq = \"\"\"\n SELECT dt\n FROM Electricity_10min\n WHERE `Meta_idMeta` = {}\n LIMIT 1;\n \"\"\".format(idMeta)\n try:\n result = mdb.getSQL(sqlq)[0]\n if (result):\n return True\n except:\n return False","def exists(self):\r\n return bool(self.bucket.lookup(self.name))","def exists(self):\n f = os.path.join(pth, '..', 'static/data', self.filename)\n return os.path.isfile(f)","def exists(name):\n\n return get_component(CachingPackage.COMPONENT_NAME).exists(name)","def exists(self):\r\n return os.path.exists(self.full_path)","def notebook_exists(self, name, path=''):\n\n\t\tos_path = self._get_os_path(name, path=path)\n\t\treturn key_exists(self.bucket, os_path)","def exist(self):\n return self.file_path.exists()","def has(resname):\n # check HOME directory first\n if os.path.exists(os.path.join(os.getenv(\"HOME\"), \".aphla\", resname)):\n return True\n else:\n return resource_exists(__name__, resname)","def check_for_data():\n if not (os.path.exists(ep.get_test_data_path()) or os.path.exists(ep.get_dbn_weight_path())):\n return False\n return True","def is_data_run(info, runinfo):\n this_run_in_runinfo = runinfo[\n (runinfo.fNight==info[\"night_int\"])&\n (runinfo.fRunID==info[\"run\"])\n ]\n return len(this_run_in_runinfo) > 0 and this_run_in_runinfo.iloc[0].fRunTypeKey == 1","def ResourceExists(self, name):\n pass","def check_exist(self):\n helper.RbdImageOperator._check_rbd_image(self.real_path)","def exists(sim):\n return (sim['N'] > 0)","def has_error(self):\r\n return self._arm.has_error","def user_exists(self,unique_ID):\n\t\ttry:\n\t\t\tself.data[unique_ID]\n\t\texcept KeyError:\n\t\t\treturn False\n\t\telse:\n\t\t\treturn True","def data_ready(self) -> bool:\n data_ready = ctypes.c_uint8()\n Utils.check(VL53L1X_C_LIBRARY.VL53L1_GetMeasurementDataReady(self.dev, byref(data_ready)))\n return data_ready.value != 0","def exists (self, uuid):\n return self.read (uuid) is not None","def id_exists(test_name):\n result_json = None\n try:\n with open(robot_dir + \"/output/results/{}.json\".format(test_name.replace(' ', ''))) as result_file:\n result_json = json.load(result_file)\n except:\n print(\"Failed to open the result json\")\n return False\n #look for values NEW_ASSOC, NEW_PROP1, NEW_PROP2\n print(result_json)\n if 6 == 6:\n return True\n return \"Length is not 6\"","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def hdf_exist_p(store, data_name):\n if not data_name.startswith(\"/\"):\n data_name = \"/\" + data_name\n if os.path.isfile(store):\n with HDFStore(store) as hdf:\n return data_name in hdf.keys()\n else:\n return False","def hasAtom(self, atomname):\n if atomname in self.atoms:\n return 1\n else:\n return 0","def is_section_exist(self, section_name: str) -> bool:\n pass","def particleExists(*args, **kwargs)->bool:\n pass","def exists(self, name):\n raise NotImplementedError()","def _exists(cursor, table, data):\n cursor.execute('SELECT 1 FROM {} WHERE ({}) = ({})'.format(table, *_query_fields(data)), data)\n return bool(cursor.fetchone())","def exists(self, name):\n return self.backend.exists(name)","def ResourceExists(resource_name, search_user_paths=True):\n try:\n ResourcePath(resource_name, search_user_paths)\n return True\n except ResourceNotFound:\n return False","def check_dataset_exists(dataset):\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\n return result == 0","def check_data_struct():\n if not os.path.exists(PROJECT_ROOT+'/data'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data')\n\n if not os.path.exists(PROJECT_ROOT+'/data/CUB_200_2011'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/CUB_200_2011')\n\n if not os.path.exists(PROJECT_ROOT+'/data/segmentations'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/segmentations')\n\n if not os.path.exists(PROJECT_ROOT+'/data/attributes.txt'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/attributes.txt')","def pl_exists(self, name):\n for i, d in enumerate(self.ui.leftwin.data):\n if d.data.name == name:\n return i\n\n return -1","def exists():\n check50.include(\"data\")\n check50.exists(\"adventure.py\")\n check50.exists(\"room.py\")","def exists(name, runas=None):\n vm_info = list_vms(name, info=True, runas=runas).splitlines()\n for info_line in vm_info:\n if \"Name: {}\".format(name) in info_line:\n return True\n return False","def find_null(data, sub_reg):\r\n subreg_sqkm_data = data.loc[pd.IndexSlice[:, sub_reg, :], pd.IndexSlice['Sq Km']]\r\n if subreg_sqkm_data.isnull().values.any() == True:\r\n print(\"\\nSq km measurements are missing for:\")\r\n print(subreg_sqkm_data[subreg_sqkm_data.isnull()])\r\n else:\r\n print(\"\\nThere are no missing sq km values for this sub-region.\")","def exists(identifier, network):\n foo = next(load(identifier, network), None)\n return foo is not None","def is_present(self):\n try:\n self.read_binary(0, 2)\n return True\n except:\n return False","def exist(self):","def IndexExists(self, arg0: 'unsigned long long') -> \"bool\":\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF3GQEULLULLBBT_IndexExists(self, arg0)"],"string":"[\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def isExist(data):\\n return True/False\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def hasResidue(self, resname):\\n if resname in self.map:\\n return 1\\n else:\\n return 0\",\n \"def datafolderexist(name):\\n folderpath = os.path.join(pathtofolder(), name)\\n return os.path.exists(folderpath)\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def object_exists(self, name: str):\\n file_path = self.__get_file_path(name)\\n return os.path.exists(file_path)\",\n \"def file_exists(msl_data_path, filename):\\n return os.path.isfile(msl_data_path + filename)\",\n \"def exists(self):\\n\\t\\tif self.hasUdim:\\n\\t\\t\\treturn len( self.udimPaths ) != 0\\n\\t\\treturn super( textureFile, self ).exists\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def exists(self, name):\\n assert name, \\\"Must input a valid dataset name.\\\"\\n return name in self.manager.data[\\\"dataset\\\"]\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def exists(self, datadir):\\n return False\",\n \"def CheckForExistence(requested_data, available_data):\\n if requested_data is not None:\\n return 1 # The requested data exists.\\n elif available_data:\\n return -1 # The requested data does not exist.\\n else:\\n return 0 # No data exists at all.\",\n \"def check_name_in_file(name_to_check, data):\\r\\n if name_to_check in data:\\r\\n return True\\r\\n return False\",\n \"def exists(dtype, name, rootdir=None):\\n return FreezableAPI.to_slug(dtype,name) in FreezableAPI.datasets(rootdir=rootdir)\",\n \"def is_section_exist(self, section_name: str) -> bool:\\n success = False\\n try:\\n self._vault_api.read_secret(path=section_name.upper(), mount_point=self.mount_point)\\n success = True\\n except InvalidPath:\\n pass\\n return success\",\n \"def datafileexist(filename):\\n filePath = os.path.join(pathtofolder(), \\\"datas\\\", filename)\\n fileFormat = '.csv'\\n return os.path.exists(f'{filePath+fileFormat}')\",\n \"def pickleExists(name):\\n fileNames = [f for f in os.listdir(PICKLE_DIR) if name in f]\\n return not len(fileNames) == 0\",\n \"async def exists(self, tag_name):\\n try:\\n if await self.get_id(tag_name):\\n return True\\n except RtbDoesntExists:\\n return False\",\n \"def check_if_file_exists(self, sensor_id:str, name:str)->str:\\n ret_value = \\\"\\\"\\n file_name = '%s/%s.*.%s.json' % (self.generate_data_prep, sensor_id, name)\\n try: \\n ret_value = glob.glob(file_name)\\n except Exception as e:\\n print(\\\"OSError - Failed top get file (%s) - %s\\\" % (file_name, e))\\n ret_value = False \\n \\n if ret_value != False and len(ret_value) > 0: \\n ret_value = ret_value[0]\\n\\n return ret_value\",\n \"def exists(self, name):\\n full_path = self.path(name)\\n return self.__volume.exists(full_path)\",\n \"def has_data(self, fragment, number):\\n if fragment in self.mdv:\\n if number in self.mdv[fragment]:\\n return True\\n return False\",\n \"def test_molecule_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the molecules.\\n i = 0\\n for molecule in mol_res_spin.molecule_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def data_available(dataset_name=None):\\r\\n for file_list in data_resources[dataset_name]['files']:\\r\\n for file in file_list:\\r\\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\\r\\n return False\\r\\n return True\",\n \"def is_version_data_existed(self):\\n # if exists, skip\\n # return \\n\\n return True\",\n \"def _object_exists(name):\\n conn = sqlite3.connect('/dev/input')\\n try:\\n cur = conn.cursor()\\n sql = 'SELECT ROWID FROM object WHERE name=? AND deleted=0'\\n cur.execute(sql, (name, ))\\n result = cur.fetchall()\\n return len(result) > 0\\n finally:\\n conn.close()\",\n \"def object_exists(self, fname):\\n return self.object_exists\",\n \"def is_data_by_filename(fname):\\n return \\\"Run2017\\\" in fname\",\n \"def has_material(obj, name):\\n return name in obj.data.materials.keys()\",\n \"def has_data(self) -> bool:\\n raise NotImplementedError\",\n \"def __in_delete_serial_name(self, name):\\n # Open the delete .csv file\\n # Initialize the reader\\n # For a row in the reader,\\n # If the checking name is in the row, \\n # return True\\n # Return False if the name is not found\\n input_filename = \\\"HobowareDeleteSerial.csv\\\"\\n input_file = open(os.path.join('Hobowarebin',input_filename), \\\"r\\\")\\n reader = csv.reader(input_file, delimiter = \\\",\\\")\\n \\n for input_row in reader:\\n if name in input_row:\\n return True\\n \\n input_file.close()\\n \\n return False\",\n \"def object_exists(self, fname):\\n return True\",\n \"def object_exists(self, fname):\\n return False\",\n \"def has_data(self):\\n return self._data is not None\",\n \"def exists(self):\\n try:\\n self.world.find(self.ehandle)\\n except KeyError:\\n return False\\n else:\\n return True\",\n \"def exists(self, name):\\n try:\\n self.container.get_object(name)\\n return True\\n except NoSuchObject:\\n return False\",\n \"def exists(self, name):\\n self.connect()\\n self._write('EXISTS %s\\\\r\\\\n' % name)\\n return self._get_numeric_response()\",\n \"def exists(self):\\n return os.path.exists(self.sensorpath)\",\n \"def test_return_single_residue_info(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_single_residue_info('1')\\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\\n res5 = mol_res_spin.return_single_residue_info('-5')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1, (1, None))\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2, (2, 'Glu'))\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4, (4, 'Pro'))\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5, (-5, None))\",\n \"def has_name(self):\\n return self.unpack_word(0x2) != 0\",\n \"def has_mask(mask_name, path=None, data=None):\\n if path is None and data is None:\\n raise ValueError(\\\"Mask file not provided.\\\")\\n if path:\\n with open(path, 'r') as file:\\n data = json.load(file)\\n \\n for inx, obj in enumerate(data[\\\"objects\\\"]):\\n if obj['classTitle'] == mask_name:\\n return inx\\n \\n return False\",\n \"def exists(self):\\n\\n return os.path.exists(self[\\\"~filename\\\"])\",\n \"def check_residue(self, chain_id, resid, resname):\\n if resname in PTM_lookup.keys():\\n return\\n else:\\n try:\\n ref_resname = PTM_reverse_lookup[resname]\\n except KeyError:\\n # print \\\"skipping unrecognized residue\\\", resname\\n return\\n ptm_dict = PTM_lookup[ref_resname][resname]\\n return (chain_id, resid, ref_resname, ptm_dict[\\\"goto_atom\\\"], ptm_dict[\\\"name\\\"])\",\n \"def has_data(self, time, fragment, number):\\n if time in self.mdvtc.keys():\\n if fragment in self.mdvtc[time].mdv.keys():\\n if number in self.mdvtc[time].mdv[fragment].keys():\\n return True\\n return False\",\n \"def has_data(self) -> bool:\\n return bool(self.data)\",\n \"def check_model_exists(ckpt):\\n expected_data = ckpt + \\\".data-00000-of-00001\\\"\\n return os.path.exists(expected_data)\",\n \"def test_count_no_spins(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Test the number of spins counted.\\n self.assertEqual(mol_res_spin.count_spins(), 0)\",\n \"def has_data(self):\\n\\n return self._data is not None\",\n \"def has_data(self):\\n\\n return self._data is not None\",\n \"def exists(self, number):\\n\\t\\tslotIDList = [s.id for s in self.slotList]\\n\\t\\ttry:\\n\\t\\t\\tindex = slotIDList.index(number)\\n\\t\\t\\treturn True\\n\\t\\texcept ValueError:\\n\\t\\t\\treturn False\\n\\t\\treturn False\",\n \"def check_file_existing(k_out, sphere_radius,full_path):\\n cwd = full_path\\n file_names = ['/T_ns_', '/Energy_', '/Distance-e-to-e_',\\n '/chain_on_iterations_']\\n\\n kout = f'{k_out:.3f}'\\n spr_rad = f'{sphere_radius:.3f}'\\n\\n current = \\\"kout_\\\" + kout + \\\"_\\\" + \\\"spr_rad_\\\" + spr_rad\\n for file_name in file_names:\\n #print (cwd + file_name + current + \\\".pkl\\\")\\n if not os.path.exists(cwd + file_name + current + \\\".pkl\\\"):\\n return False\\n return True\",\n \"def has_data(self):\\n return len(self.data) > 0\",\n \"def exists(self) -> bool:\\n try:\\n result = self.get()\\n except KeyError:\\n return False\\n return True\",\n \"def check_for_residue_existance(self):\\n if not self.pose.total_residue():\\n print \\\"No pose Loaded.\\\"\\n return False\\n\\n if not self.current_chain.get() or not self.current_residue.get():\\n print \\\"Chain or residue not set\\\"\\n return False\\n\\n current_region = self.current_residue.get().split(\\\":\\\")\\n if len(current_region)>1:\\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\\n\\n\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\\n print \\\"Region not found in pose\\\"\\n return False\\n else:\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\\n\\n print \\\"Residue not found in pose\\\"\\n return False\\n\\n #If everythig is good then:\\n return True\",\n \"def check_data_exist(data):\\n if data is not None:\\n if data.text is not None:\\n return True\\n return False\",\n \"def exists():\\n\\treturn os.path.exists('data/strmr.db')\",\n \"def volume_exists(vil, vol_name):\\n\\n exists = False\\n try:\\n if not vil:\\n vil, err = get_basic_volume_info_all()\\n if err:\\n raise Exception(err)\\n if vil:\\n for v in vil:\\n if v[\\\"name\\\"] == vol_name:\\n exists = True\\n except Exception, e:\\n return False, 'Error checking for volume existance : %s' % str(e)\\n else:\\n return exists, None\",\n \"def checkExistence(idMeta):\\n # XXX add for diaries\\n sqlq = \\\"\\\"\\\"\\n SELECT dt\\n FROM Electricity_10min\\n WHERE `Meta_idMeta` = {}\\n LIMIT 1;\\n \\\"\\\"\\\".format(idMeta)\\n try:\\n result = mdb.getSQL(sqlq)[0]\\n if (result):\\n return True\\n except:\\n return False\",\n \"def exists(self):\\r\\n return bool(self.bucket.lookup(self.name))\",\n \"def exists(self):\\n f = os.path.join(pth, '..', 'static/data', self.filename)\\n return os.path.isfile(f)\",\n \"def exists(name):\\n\\n return get_component(CachingPackage.COMPONENT_NAME).exists(name)\",\n \"def exists(self):\\r\\n return os.path.exists(self.full_path)\",\n \"def notebook_exists(self, name, path=''):\\n\\n\\t\\tos_path = self._get_os_path(name, path=path)\\n\\t\\treturn key_exists(self.bucket, os_path)\",\n \"def exist(self):\\n return self.file_path.exists()\",\n \"def has(resname):\\n # check HOME directory first\\n if os.path.exists(os.path.join(os.getenv(\\\"HOME\\\"), \\\".aphla\\\", resname)):\\n return True\\n else:\\n return resource_exists(__name__, resname)\",\n \"def check_for_data():\\n if not (os.path.exists(ep.get_test_data_path()) or os.path.exists(ep.get_dbn_weight_path())):\\n return False\\n return True\",\n \"def is_data_run(info, runinfo):\\n this_run_in_runinfo = runinfo[\\n (runinfo.fNight==info[\\\"night_int\\\"])&\\n (runinfo.fRunID==info[\\\"run\\\"])\\n ]\\n return len(this_run_in_runinfo) > 0 and this_run_in_runinfo.iloc[0].fRunTypeKey == 1\",\n \"def ResourceExists(self, name):\\n pass\",\n \"def check_exist(self):\\n helper.RbdImageOperator._check_rbd_image(self.real_path)\",\n \"def exists(sim):\\n return (sim['N'] > 0)\",\n \"def has_error(self):\\r\\n return self._arm.has_error\",\n \"def user_exists(self,unique_ID):\\n\\t\\ttry:\\n\\t\\t\\tself.data[unique_ID]\\n\\t\\texcept KeyError:\\n\\t\\t\\treturn False\\n\\t\\telse:\\n\\t\\t\\treturn True\",\n \"def data_ready(self) -> bool:\\n data_ready = ctypes.c_uint8()\\n Utils.check(VL53L1X_C_LIBRARY.VL53L1_GetMeasurementDataReady(self.dev, byref(data_ready)))\\n return data_ready.value != 0\",\n \"def exists (self, uuid):\\n return self.read (uuid) is not None\",\n \"def id_exists(test_name):\\n result_json = None\\n try:\\n with open(robot_dir + \\\"/output/results/{}.json\\\".format(test_name.replace(' ', ''))) as result_file:\\n result_json = json.load(result_file)\\n except:\\n print(\\\"Failed to open the result json\\\")\\n return False\\n #look for values NEW_ASSOC, NEW_PROP1, NEW_PROP2\\n print(result_json)\\n if 6 == 6:\\n return True\\n return \\\"Length is not 6\\\"\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def hdf_exist_p(store, data_name):\\n if not data_name.startswith(\\\"/\\\"):\\n data_name = \\\"/\\\" + data_name\\n if os.path.isfile(store):\\n with HDFStore(store) as hdf:\\n return data_name in hdf.keys()\\n else:\\n return False\",\n \"def hasAtom(self, atomname):\\n if atomname in self.atoms:\\n return 1\\n else:\\n return 0\",\n \"def is_section_exist(self, section_name: str) -> bool:\\n pass\",\n \"def particleExists(*args, **kwargs)->bool:\\n pass\",\n \"def exists(self, name):\\n raise NotImplementedError()\",\n \"def _exists(cursor, table, data):\\n cursor.execute('SELECT 1 FROM {} WHERE ({}) = ({})'.format(table, *_query_fields(data)), data)\\n return bool(cursor.fetchone())\",\n \"def exists(self, name):\\n return self.backend.exists(name)\",\n \"def ResourceExists(resource_name, search_user_paths=True):\\n try:\\n ResourcePath(resource_name, search_user_paths)\\n return True\\n except ResourceNotFound:\\n return False\",\n \"def check_dataset_exists(dataset):\\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\\n return result == 0\",\n \"def check_data_struct():\\n if not os.path.exists(PROJECT_ROOT+'/data'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data')\\n\\n if not os.path.exists(PROJECT_ROOT+'/data/CUB_200_2011'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/CUB_200_2011')\\n\\n if not os.path.exists(PROJECT_ROOT+'/data/segmentations'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/segmentations')\\n\\n if not os.path.exists(PROJECT_ROOT+'/data/attributes.txt'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/attributes.txt')\",\n \"def pl_exists(self, name):\\n for i, d in enumerate(self.ui.leftwin.data):\\n if d.data.name == name:\\n return i\\n\\n return -1\",\n \"def exists():\\n check50.include(\\\"data\\\")\\n check50.exists(\\\"adventure.py\\\")\\n check50.exists(\\\"room.py\\\")\",\n \"def exists(name, runas=None):\\n vm_info = list_vms(name, info=True, runas=runas).splitlines()\\n for info_line in vm_info:\\n if \\\"Name: {}\\\".format(name) in info_line:\\n return True\\n return False\",\n \"def find_null(data, sub_reg):\\r\\n subreg_sqkm_data = data.loc[pd.IndexSlice[:, sub_reg, :], pd.IndexSlice['Sq Km']]\\r\\n if subreg_sqkm_data.isnull().values.any() == True:\\r\\n print(\\\"\\\\nSq km measurements are missing for:\\\")\\r\\n print(subreg_sqkm_data[subreg_sqkm_data.isnull()])\\r\\n else:\\r\\n print(\\\"\\\\nThere are no missing sq km values for this sub-region.\\\")\",\n \"def exists(identifier, network):\\n foo = next(load(identifier, network), None)\\n return foo is not None\",\n \"def is_present(self):\\n try:\\n self.read_binary(0, 2)\\n return True\\n except:\\n return False\",\n \"def exist(self):\",\n \"def IndexExists(self, arg0: 'unsigned long long') -> \\\"bool\\\":\\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF3GQEULLULLBBT_IndexExists(self, arg0)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.83926356","0.83922964","0.8218184","0.81590086","0.8031726","0.7876572","0.6523379","0.6487321","0.5793478","0.566882","0.5593635","0.5562465","0.55435604","0.5511731","0.54539114","0.54490983","0.5361425","0.535502","0.53494656","0.53312635","0.5321676","0.5253612","0.5237997","0.5235978","0.523547","0.52340436","0.5230328","0.5208623","0.5207441","0.5203882","0.5200589","0.5175737","0.5171515","0.5159934","0.5151709","0.5148766","0.5148155","0.5148143","0.51476455","0.5135677","0.5134121","0.51188606","0.51124513","0.5112205","0.5107427","0.510414","0.5070812","0.5065101","0.50646555","0.5058361","0.5047478","0.50451875","0.50450295","0.5043988","0.5043988","0.50347346","0.50290585","0.5027331","0.50250566","0.5012515","0.50092834","0.5009209","0.4999564","0.4998946","0.49956572","0.49949807","0.49820578","0.49788505","0.4978504","0.4957683","0.495094","0.4948831","0.49448988","0.49367893","0.49328846","0.49323347","0.49261615","0.49220628","0.491179","0.4908152","0.49023247","0.49001694","0.48968872","0.48914665","0.48898914","0.48862222","0.48808813","0.4879407","0.48793852","0.48792627","0.48764887","0.48743197","0.48731118","0.4870802","0.4867288","0.4867199","0.48636085","0.4856462","0.48553485","0.48547968"],"string":"[\n \"0.83926356\",\n \"0.83922964\",\n \"0.8218184\",\n \"0.81590086\",\n \"0.8031726\",\n \"0.7876572\",\n \"0.6523379\",\n \"0.6487321\",\n \"0.5793478\",\n \"0.566882\",\n \"0.5593635\",\n \"0.5562465\",\n \"0.55435604\",\n \"0.5511731\",\n \"0.54539114\",\n \"0.54490983\",\n \"0.5361425\",\n \"0.535502\",\n \"0.53494656\",\n \"0.53312635\",\n \"0.5321676\",\n \"0.5253612\",\n \"0.5237997\",\n \"0.5235978\",\n \"0.523547\",\n \"0.52340436\",\n \"0.5230328\",\n \"0.5208623\",\n \"0.5207441\",\n \"0.5203882\",\n \"0.5200589\",\n \"0.5175737\",\n \"0.5171515\",\n \"0.5159934\",\n \"0.5151709\",\n \"0.5148766\",\n \"0.5148155\",\n \"0.5148143\",\n \"0.51476455\",\n \"0.5135677\",\n \"0.5134121\",\n \"0.51188606\",\n \"0.51124513\",\n \"0.5112205\",\n \"0.5107427\",\n \"0.510414\",\n \"0.5070812\",\n \"0.5065101\",\n \"0.50646555\",\n \"0.5058361\",\n \"0.5047478\",\n \"0.50451875\",\n \"0.50450295\",\n \"0.5043988\",\n \"0.5043988\",\n \"0.50347346\",\n \"0.50290585\",\n \"0.5027331\",\n \"0.50250566\",\n \"0.5012515\",\n \"0.50092834\",\n \"0.5009209\",\n \"0.4999564\",\n \"0.4998946\",\n \"0.49956572\",\n \"0.49949807\",\n \"0.49820578\",\n \"0.49788505\",\n \"0.4978504\",\n \"0.4957683\",\n \"0.495094\",\n \"0.4948831\",\n \"0.49448988\",\n \"0.49367893\",\n \"0.49328846\",\n \"0.49323347\",\n \"0.49261615\",\n \"0.49220628\",\n \"0.491179\",\n \"0.4908152\",\n \"0.49023247\",\n \"0.49001694\",\n \"0.48968872\",\n \"0.48914665\",\n \"0.48898914\",\n \"0.48862222\",\n \"0.48808813\",\n \"0.4879407\",\n \"0.48793852\",\n \"0.48792627\",\n \"0.48764887\",\n \"0.48743197\",\n \"0.48731118\",\n \"0.4870802\",\n \"0.4867288\",\n \"0.4867199\",\n \"0.48636085\",\n \"0.4856462\",\n \"0.48553485\",\n \"0.48547968\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8426691"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81479,"cells":{"query":{"kind":"string","value":"Determine if moleculeresiduespin data exists (when a single spin is numbered). The function tested is pipe_control.mol_res_spin.exists_mol_res_spin_data()."},"document":{"kind":"string","value":"def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def isExist(data):\n return True/False","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def has_data(self, fragment, number):\n if fragment in self.mdv:\n if number in self.mdv[fragment]:\n return True\n return False","def hasResidue(self, resname):\n if resname in self.map:\n return 1\n else:\n return 0","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def exists(self, number):\n\t\tslotIDList = [s.id for s in self.slotList]\n\t\ttry:\n\t\t\tindex = slotIDList.index(number)\n\t\t\treturn True\n\t\texcept ValueError:\n\t\t\treturn False\n\t\treturn False","def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def exists(self):\n\t\tif self.hasUdim:\n\t\t\treturn len( self.udimPaths ) != 0\n\t\treturn super( textureFile, self ).exists","def has_data(self, time, fragment, number):\n if time in self.mdvtc.keys():\n if fragment in self.mdvtc[time].mdv.keys():\n if number in self.mdvtc[time].mdv[fragment].keys():\n return True\n return False","def test_count_no_spins(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 0)","def file_exists(msl_data_path, filename):\n return os.path.isfile(msl_data_path + filename)","def CheckForExistence(requested_data, available_data):\n if requested_data is not None:\n return 1 # The requested data exists.\n elif available_data:\n return -1 # The requested data does not exist.\n else:\n return 0 # No data exists at all.","def test_return_single_residue_info(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_single_residue_info('1')\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\n res5 = mol_res_spin.return_single_residue_info('-5')\n\n # Test the data of residue 1.\n self.assertEqual(res1, (1, None))\n\n # Test the data of residue 2.\n self.assertEqual(res2, (2, 'Glu'))\n\n # Test the data of residue 4.\n self.assertEqual(res4, (4, 'Pro'))\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5, (-5, None))","def is_version_data_existed(self):\n # if exists, skip\n # return \n\n return True","def datafolderexist(name):\n folderpath = os.path.join(pathtofolder(), name)\n return os.path.exists(folderpath)","def exists(sim):\n return (sim['N'] > 0)","def exists(self, datadir):\n return False","def has_data(self):\n return self._data is not None","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def check_for_residue_existance(self):\n if not self.pose.total_residue():\n print \"No pose Loaded.\"\n return False\n\n if not self.current_chain.get() or not self.current_residue.get():\n print \"Chain or residue not set\"\n return False\n\n current_region = self.current_residue.get().split(\":\")\n if len(current_region)>1:\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\n\n\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\n print \"Region not found in pose\"\n return False\n else:\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\n\n print \"Residue not found in pose\"\n return False\n\n #If everythig is good then:\n return True","def has_data(self):\n return len(self.data) > 0","def has_data(self) -> bool:\n raise NotImplementedError","def is_data_run(info, runinfo):\n this_run_in_runinfo = runinfo[\n (runinfo.fNight==info[\"night_int\"])&\n (runinfo.fRunID==info[\"run\"])\n ]\n return len(this_run_in_runinfo) > 0 and this_run_in_runinfo.iloc[0].fRunTypeKey == 1","def has_data(self):\n\n return self._data is not None","def has_data(self):\n\n return self._data is not None","def has_data(self) -> bool:\n return bool(self.data)","def checkExistence(idMeta):\n # XXX add for diaries\n sqlq = \"\"\"\n SELECT dt\n FROM Electricity_10min\n WHERE `Meta_idMeta` = {}\n LIMIT 1;\n \"\"\".format(idMeta)\n try:\n result = mdb.getSQL(sqlq)[0]\n if (result):\n return True\n except:\n return False","def data_ready(self) -> bool:\n data_ready = ctypes.c_uint8()\n Utils.check(VL53L1X_C_LIBRARY.VL53L1_GetMeasurementDataReady(self.dev, byref(data_ready)))\n return data_ready.value != 0","def IndexExists(self, arg0: 'unsigned long long') -> \"bool\":\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF3GQEULLULLBBT_IndexExists(self, arg0)","def is_present(self):\n try:\n self.read_binary(0, 2)\n return True\n except:\n return False","def has_error(self):\r\n return self._arm.has_error","def datafileexist(filename):\n filePath = os.path.join(pathtofolder(), \"datas\", filename)\n fileFormat = '.csv'\n return os.path.exists(f'{filePath+fileFormat}')","def contains(self, seq_nr: str) -> bool:\n return bool(self.__data.get(seq_nr))","def check_model_exists(ckpt):\n expected_data = ckpt + \".data-00000-of-00001\"\n return os.path.exists(expected_data)","def object_exists(self, name: str):\n file_path = self.__get_file_path(name)\n return os.path.exists(file_path)","def exists(self):\n return os.path.exists(self.sensorpath)","def exists(self):\n try:\n self.world.find(self.ehandle)\n except KeyError:\n return False\n else:\n return True","def IndexExists(self, arg0: 'unsigned long long') -> \"bool\":\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF2GQEULLULLBBT_IndexExists(self, arg0)","def object_exists(self, fname):\n return self.object_exists","def has_mask(mask_name, path=None, data=None):\n if path is None and data is None:\n raise ValueError(\"Mask file not provided.\")\n if path:\n with open(path, 'r') as file:\n data = json.load(file)\n \n for inx, obj in enumerate(data[\"objects\"]):\n if obj['classTitle'] == mask_name:\n return inx\n \n return False","def find_null(data, sub_reg):\r\n subreg_sqkm_data = data.loc[pd.IndexSlice[:, sub_reg, :], pd.IndexSlice['Sq Km']]\r\n if subreg_sqkm_data.isnull().values.any() == True:\r\n print(\"\\nSq km measurements are missing for:\")\r\n print(subreg_sqkm_data[subreg_sqkm_data.isnull()])\r\n else:\r\n print(\"\\nThere are no missing sq km values for this sub-region.\")","def data_available(dataset_name=None):\r\n for file_list in data_resources[dataset_name]['files']:\r\n for file in file_list:\r\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\r\n return False\r\n return True","def is_data_by_filename(fname):\n return \"Run2017\" in fname","def id_exists(test_name):\n result_json = None\n try:\n with open(robot_dir + \"/output/results/{}.json\".format(test_name.replace(' ', ''))) as result_file:\n result_json = json.load(result_file)\n except:\n print(\"Failed to open the result json\")\n return False\n #look for values NEW_ASSOC, NEW_PROP1, NEW_PROP2\n print(result_json)\n if 6 == 6:\n return True\n return \"Length is not 6\"","def check_data_exist(data):\n if data is not None:\n if data.text is not None:\n return True\n return False","def object_exists(self, fname):\n return False","def checkIfThereIsData(self, i):\n _, amountOfThings = self.weaviate.Get(\"/\" + i)\n if len(amountOfThings[i]) == 0:\n return False\n else:\n return True","def test_molecule_loop(self):\n\n # Loop over the molecules.\n for mol in mol_res_spin.molecule_loop('#RNA'):\n # Test the molecule name.\n self.assertEqual(mol.name, 'RNA')\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)","def pickleExists(name):\n fileNames = [f for f in os.listdir(PICKLE_DIR) if name in f]\n return not len(fileNames) == 0","def exists(dtype, name, rootdir=None):\n return FreezableAPI.to_slug(dtype,name) in FreezableAPI.datasets(rootdir=rootdir)","def object_exists(self, fname):\n return True","def exists():\n\treturn os.path.exists('data/strmr.db')","def hasImageData(self,volumeNode):\n if not volumeNode:\n logging.debug('hasImageData failed: no volume node')\n return False\n if volumeNode.GetImageData() is None:\n logging.debug('hasImageData failed: no image data in volume node')\n return False\n return True","def verify_object(self, data):\n rv = self.get(data[self.id_field])\n result = not is_404(rv)\n if result:\n for key, value in data:\n if not in_response(rv, value):\n return False\n return result","def is_section_exist(self, section_name: str) -> bool:\n success = False\n try:\n self._vault_api.read_secret(path=section_name.upper(), mount_point=self.mount_point)\n success = True\n except InvalidPath:\n pass\n return success","def particleExists(*args, **kwargs)->bool:\n pass","def exists (self, uuid):\n return self.read (uuid) is not None","def check_file_existing(k_out, sphere_radius,full_path):\n cwd = full_path\n file_names = ['/T_ns_', '/Energy_', '/Distance-e-to-e_',\n '/chain_on_iterations_']\n\n kout = f'{k_out:.3f}'\n spr_rad = f'{sphere_radius:.3f}'\n\n current = \"kout_\" + kout + \"_\" + \"spr_rad_\" + spr_rad\n for file_name in file_names:\n #print (cwd + file_name + current + \".pkl\")\n if not os.path.exists(cwd + file_name + current + \".pkl\"):\n return False\n return True","def check_for_data():\n if not (os.path.exists(ep.get_test_data_path()) or os.path.exists(ep.get_dbn_weight_path())):\n return False\n return True","def hasImageData(self,volumeNode):\n if not volumeNode:\n logging.debug('hasImageData failed: no volume node')\n return False\n return True","def exists(self) -> bool:\n try:\n result = self.get()\n except KeyError:\n return False\n return True","def _exists(cursor, table, data):\n cursor.execute('SELECT 1 FROM {} WHERE ({}) = ({})'.format(table, *_query_fields(data)), data)\n return bool(cursor.fetchone())","async def exists(self, tag_name):\n try:\n if await self.get_id(tag_name):\n return True\n except RtbDoesntExists:\n return False","def _loaded_data(self):\n try:\n dsize = [int(d) for d\n in self.run('fits size', via='get').split()]\n except (ValueError, TypeError, AttributeError) as err:\n log.debug(f' FITS size error: {err}')\n return False\n else:\n if 0 in dsize:\n return False\n else:\n return True","def has_data(self, fit_id, species_id, start=None, stop=None):\n if not (fit_id in self.raw_results and species_id in\\\n self.raw_results[fit_id]):\n return False\n if all([isinstance(x, datetime) for x in [start, stop]]):\n ts = self.raw_results[fit_id][\"start\"]\n if not any([start < x < stop for x in ts]):\n return False\n return True","def hasError(self, pin):\r\n return bool(self.Mask & (0b1 << pin))","def exists(self, name):\n assert name, \"Must input a valid dataset name.\"\n return name in self.manager.data[\"dataset\"]","def exist(self):\n return self.file_path.exists()","def _object_exists(name):\n conn = sqlite3.connect('/dev/input')\n try:\n cur = conn.cursor()\n sql = 'SELECT ROWID FROM object WHERE name=? AND deleted=0'\n cur.execute(sql, (name, ))\n result = cur.fetchall()\n return len(result) > 0\n finally:\n conn.close()","def exists(identifier, network):\n foo = next(load(identifier, network), None)\n return foo is not None","def is_empty(self):\n for key, dataset in self.datasets.items():\n try:\n has_data = dataset.has_data()\n except MFDataException as mfde:\n raise MFDataException(\n mfdata_except=mfde,\n model=self._container_package.model_name,\n package=self._container_package._get_pname(),\n message=\"Error occurred while verifying\"\n ' data of dataset \"{}\" in block '\n '\"{}\"'.format(dataset.structure.name, self.structure.name),\n )\n\n if has_data is not None and has_data:\n return False\n return True","def exists(self):\n\n return os.path.exists(self[\"~filename\"])","def exists(self):\r\n return os.path.exists(self.full_path)","def check_if_file_exists(self, sensor_id:str, name:str)->str:\n ret_value = \"\"\n file_name = '%s/%s.*.%s.json' % (self.generate_data_prep, sensor_id, name)\n try: \n ret_value = glob.glob(file_name)\n except Exception as e:\n print(\"OSError - Failed top get file (%s) - %s\" % (file_name, e))\n ret_value = False \n \n if ret_value != False and len(ret_value) > 0: \n ret_value = ret_value[0]\n\n return ret_value","def race_entry_exists(self, race_id):\n try:\n self.consolidated_db.data.loc[race_id] # Throws a KeyError if no entry is in the dataframe.\n return True\n except KeyError:\n return False","def exists(self):\n f = os.path.join(pth, '..', 'static/data', self.filename)\n return os.path.isfile(f)","def hasImageData(self,volumeNode):\n if not volumeNode:\n logging.debug('no volume node')\n return False\n if volumeNode.GetImageData() is None:\n logging.debug('no image data')\n return False\n return True","def check_residue(self, chain_id, resid, resname):\n if resname in PTM_lookup.keys():\n return\n else:\n try:\n ref_resname = PTM_reverse_lookup[resname]\n except KeyError:\n # print \"skipping unrecognized residue\", resname\n return\n ptm_dict = PTM_lookup[ref_resname][resname]\n return (chain_id, resid, ref_resname, ptm_dict[\"goto_atom\"], ptm_dict[\"name\"])","def _check_row_exists(self, pk):\n session = self.session_factory()\n exists = session.query(PipelineRun).filter_by(id=pk).first()\n session.close()\n if exists:\n return True\n return False","def pidExists(self, pid):\n\n prochash = self.getHash( 'datahash' ) # safely get copy of process dict\n\n try:\n prochash[pid]\n return 1\n except KeyError:\n return 0","def pidExists(self, pid):\n\n prochash = self.getHash( 'datahash' ) # safely get copy of process dict\n\n try:\n prochash[pid]\n return 1\n except KeyError:\n return 0","def check_exist(self):\n helper.RbdImageOperator._check_rbd_image(self.real_path)","def has_material(obj, name):\n return name in obj.data.materials.keys()","def hasImageData(self,volumeNode):\n if not volumeNode:\n print('no volume node')\n return False\n if volumeNode.GetImageData() == None:\n print('no image data')\n return False\n return True","def check_dataset_exists(dataset):\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\n return result == 0","def item_exists(self, call_number):\n return call_number in self.item_list.keys()","def has_id(self, data):\n # (Dict[str, Any]) -> bool\n return self.id_column.name in data","def test_molecule_loop_no_selection(self):\n\n # Molecule data.\n name = ['Ap4Aase', 'RNA']\n\n # Loop over the molecules.\n i = 0\n for mol in mol_res_spin.molecule_loop():\n # Test the molecule names.\n self.assertEqual(mol.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)","def task_validate_rawdata_file(pk):\n\n # init and checks\n valid = False\n logger = Logger.get_logger(StringIO())\n try:\n df = Data.objects.get(id=pk)\n assert df.kind == 'rd_file'\n tr = df.content_object\n except:\n logger.log('ERROR')\n return valid\n\n try:\n logger.log('looking at raw data file with pk: %s' % pk)\n rd, sr = read_hdf5_arc(df.file.path)\n logger.log('found rd_file: %s' % df.name)\n len_rd_sec = rd.shape[0] / sr\n logger.log('found data in %d channels, for %d sec' % (\n rd.shape[1], len_rd_sec))\n\n # TODO: more checks?\n\n logger.log('rd_file passed all checks')\n valid = True\n except Exception, ex:\n logger.log('ERROR: rawdata file check: %s' % str(ex))\n finally:\n df.save()\n tr.valid_rd_log = logger.get_content()\n tr.save()\n return valid","def check(self, mu):\n return self.find(mu)[0] is not None","def is_data_present(self, cycle: int, bus_item: BusItem) -> bool:\n buffer = self.get_cycle_buffer(cycle)\n if self.component_subtype == \"PEGB\":\n return False\n #print(buffer)\n # for pe_id in buffer:\n # pe_buffer = buffer[pe_id]\n # # # TODO ad-hoc\n # # if isinstance(pe_buffer, deque):\n # # return False\n # #print(pe_buffer)\n #\n # pe_read_buffer = pe_buffer[\"read\"]\n # #print(pe_read_buffer)\n # for data in pe_read_buffer:\n # if data == bus_item:\n # return True\n elif self.component_subtype == \"PENB\":\n read_buffer = buffer[\"read\"]\n for entry in read_buffer:\n if entry == bus_item:\n return True\n else:\n for data in buffer:\n if data == bus_item:\n return True\n return False","def notebook_exists(self, name, path=''):\n\n\t\tos_path = self._get_os_path(name, path=path)\n\t\treturn key_exists(self.bucket, os_path)"],"string":"[\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def isExist(data):\\n return True/False\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def has_data(self, fragment, number):\\n if fragment in self.mdv:\\n if number in self.mdv[fragment]:\\n return True\\n return False\",\n \"def hasResidue(self, resname):\\n if resname in self.map:\\n return 1\\n else:\\n return 0\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def exists(self, number):\\n\\t\\tslotIDList = [s.id for s in self.slotList]\\n\\t\\ttry:\\n\\t\\t\\tindex = slotIDList.index(number)\\n\\t\\t\\treturn True\\n\\t\\texcept ValueError:\\n\\t\\t\\treturn False\\n\\t\\treturn False\",\n \"def test_molecule_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the molecules.\\n i = 0\\n for molecule in mol_res_spin.molecule_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def exists(self):\\n\\t\\tif self.hasUdim:\\n\\t\\t\\treturn len( self.udimPaths ) != 0\\n\\t\\treturn super( textureFile, self ).exists\",\n \"def has_data(self, time, fragment, number):\\n if time in self.mdvtc.keys():\\n if fragment in self.mdvtc[time].mdv.keys():\\n if number in self.mdvtc[time].mdv[fragment].keys():\\n return True\\n return False\",\n \"def test_count_no_spins(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Test the number of spins counted.\\n self.assertEqual(mol_res_spin.count_spins(), 0)\",\n \"def file_exists(msl_data_path, filename):\\n return os.path.isfile(msl_data_path + filename)\",\n \"def CheckForExistence(requested_data, available_data):\\n if requested_data is not None:\\n return 1 # The requested data exists.\\n elif available_data:\\n return -1 # The requested data does not exist.\\n else:\\n return 0 # No data exists at all.\",\n \"def test_return_single_residue_info(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_single_residue_info('1')\\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\\n res5 = mol_res_spin.return_single_residue_info('-5')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1, (1, None))\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2, (2, 'Glu'))\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4, (4, 'Pro'))\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5, (-5, None))\",\n \"def is_version_data_existed(self):\\n # if exists, skip\\n # return \\n\\n return True\",\n \"def datafolderexist(name):\\n folderpath = os.path.join(pathtofolder(), name)\\n return os.path.exists(folderpath)\",\n \"def exists(sim):\\n return (sim['N'] > 0)\",\n \"def exists(self, datadir):\\n return False\",\n \"def has_data(self):\\n return self._data is not None\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def check_for_residue_existance(self):\\n if not self.pose.total_residue():\\n print \\\"No pose Loaded.\\\"\\n return False\\n\\n if not self.current_chain.get() or not self.current_residue.get():\\n print \\\"Chain or residue not set\\\"\\n return False\\n\\n current_region = self.current_residue.get().split(\\\":\\\")\\n if len(current_region)>1:\\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\\n\\n\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\\n print \\\"Region not found in pose\\\"\\n return False\\n else:\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\\n\\n print \\\"Residue not found in pose\\\"\\n return False\\n\\n #If everythig is good then:\\n return True\",\n \"def has_data(self):\\n return len(self.data) > 0\",\n \"def has_data(self) -> bool:\\n raise NotImplementedError\",\n \"def is_data_run(info, runinfo):\\n this_run_in_runinfo = runinfo[\\n (runinfo.fNight==info[\\\"night_int\\\"])&\\n (runinfo.fRunID==info[\\\"run\\\"])\\n ]\\n return len(this_run_in_runinfo) > 0 and this_run_in_runinfo.iloc[0].fRunTypeKey == 1\",\n \"def has_data(self):\\n\\n return self._data is not None\",\n \"def has_data(self):\\n\\n return self._data is not None\",\n \"def has_data(self) -> bool:\\n return bool(self.data)\",\n \"def checkExistence(idMeta):\\n # XXX add for diaries\\n sqlq = \\\"\\\"\\\"\\n SELECT dt\\n FROM Electricity_10min\\n WHERE `Meta_idMeta` = {}\\n LIMIT 1;\\n \\\"\\\"\\\".format(idMeta)\\n try:\\n result = mdb.getSQL(sqlq)[0]\\n if (result):\\n return True\\n except:\\n return False\",\n \"def data_ready(self) -> bool:\\n data_ready = ctypes.c_uint8()\\n Utils.check(VL53L1X_C_LIBRARY.VL53L1_GetMeasurementDataReady(self.dev, byref(data_ready)))\\n return data_ready.value != 0\",\n \"def IndexExists(self, arg0: 'unsigned long long') -> \\\"bool\\\":\\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF3GQEULLULLBBT_IndexExists(self, arg0)\",\n \"def is_present(self):\\n try:\\n self.read_binary(0, 2)\\n return True\\n except:\\n return False\",\n \"def has_error(self):\\r\\n return self._arm.has_error\",\n \"def datafileexist(filename):\\n filePath = os.path.join(pathtofolder(), \\\"datas\\\", filename)\\n fileFormat = '.csv'\\n return os.path.exists(f'{filePath+fileFormat}')\",\n \"def contains(self, seq_nr: str) -> bool:\\n return bool(self.__data.get(seq_nr))\",\n \"def check_model_exists(ckpt):\\n expected_data = ckpt + \\\".data-00000-of-00001\\\"\\n return os.path.exists(expected_data)\",\n \"def object_exists(self, name: str):\\n file_path = self.__get_file_path(name)\\n return os.path.exists(file_path)\",\n \"def exists(self):\\n return os.path.exists(self.sensorpath)\",\n \"def exists(self):\\n try:\\n self.world.find(self.ehandle)\\n except KeyError:\\n return False\\n else:\\n return True\",\n \"def IndexExists(self, arg0: 'unsigned long long') -> \\\"bool\\\":\\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF2GQEULLULLBBT_IndexExists(self, arg0)\",\n \"def object_exists(self, fname):\\n return self.object_exists\",\n \"def has_mask(mask_name, path=None, data=None):\\n if path is None and data is None:\\n raise ValueError(\\\"Mask file not provided.\\\")\\n if path:\\n with open(path, 'r') as file:\\n data = json.load(file)\\n \\n for inx, obj in enumerate(data[\\\"objects\\\"]):\\n if obj['classTitle'] == mask_name:\\n return inx\\n \\n return False\",\n \"def find_null(data, sub_reg):\\r\\n subreg_sqkm_data = data.loc[pd.IndexSlice[:, sub_reg, :], pd.IndexSlice['Sq Km']]\\r\\n if subreg_sqkm_data.isnull().values.any() == True:\\r\\n print(\\\"\\\\nSq km measurements are missing for:\\\")\\r\\n print(subreg_sqkm_data[subreg_sqkm_data.isnull()])\\r\\n else:\\r\\n print(\\\"\\\\nThere are no missing sq km values for this sub-region.\\\")\",\n \"def data_available(dataset_name=None):\\r\\n for file_list in data_resources[dataset_name]['files']:\\r\\n for file in file_list:\\r\\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\\r\\n return False\\r\\n return True\",\n \"def is_data_by_filename(fname):\\n return \\\"Run2017\\\" in fname\",\n \"def id_exists(test_name):\\n result_json = None\\n try:\\n with open(robot_dir + \\\"/output/results/{}.json\\\".format(test_name.replace(' ', ''))) as result_file:\\n result_json = json.load(result_file)\\n except:\\n print(\\\"Failed to open the result json\\\")\\n return False\\n #look for values NEW_ASSOC, NEW_PROP1, NEW_PROP2\\n print(result_json)\\n if 6 == 6:\\n return True\\n return \\\"Length is not 6\\\"\",\n \"def check_data_exist(data):\\n if data is not None:\\n if data.text is not None:\\n return True\\n return False\",\n \"def object_exists(self, fname):\\n return False\",\n \"def checkIfThereIsData(self, i):\\n _, amountOfThings = self.weaviate.Get(\\\"/\\\" + i)\\n if len(amountOfThings[i]) == 0:\\n return False\\n else:\\n return True\",\n \"def test_molecule_loop(self):\\n\\n # Loop over the molecules.\\n for mol in mol_res_spin.molecule_loop('#RNA'):\\n # Test the molecule name.\\n self.assertEqual(mol.name, 'RNA')\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)\",\n \"def pickleExists(name):\\n fileNames = [f for f in os.listdir(PICKLE_DIR) if name in f]\\n return not len(fileNames) == 0\",\n \"def exists(dtype, name, rootdir=None):\\n return FreezableAPI.to_slug(dtype,name) in FreezableAPI.datasets(rootdir=rootdir)\",\n \"def object_exists(self, fname):\\n return True\",\n \"def exists():\\n\\treturn os.path.exists('data/strmr.db')\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n logging.debug('hasImageData failed: no volume node')\\n return False\\n if volumeNode.GetImageData() is None:\\n logging.debug('hasImageData failed: no image data in volume node')\\n return False\\n return True\",\n \"def verify_object(self, data):\\n rv = self.get(data[self.id_field])\\n result = not is_404(rv)\\n if result:\\n for key, value in data:\\n if not in_response(rv, value):\\n return False\\n return result\",\n \"def is_section_exist(self, section_name: str) -> bool:\\n success = False\\n try:\\n self._vault_api.read_secret(path=section_name.upper(), mount_point=self.mount_point)\\n success = True\\n except InvalidPath:\\n pass\\n return success\",\n \"def particleExists(*args, **kwargs)->bool:\\n pass\",\n \"def exists (self, uuid):\\n return self.read (uuid) is not None\",\n \"def check_file_existing(k_out, sphere_radius,full_path):\\n cwd = full_path\\n file_names = ['/T_ns_', '/Energy_', '/Distance-e-to-e_',\\n '/chain_on_iterations_']\\n\\n kout = f'{k_out:.3f}'\\n spr_rad = f'{sphere_radius:.3f}'\\n\\n current = \\\"kout_\\\" + kout + \\\"_\\\" + \\\"spr_rad_\\\" + spr_rad\\n for file_name in file_names:\\n #print (cwd + file_name + current + \\\".pkl\\\")\\n if not os.path.exists(cwd + file_name + current + \\\".pkl\\\"):\\n return False\\n return True\",\n \"def check_for_data():\\n if not (os.path.exists(ep.get_test_data_path()) or os.path.exists(ep.get_dbn_weight_path())):\\n return False\\n return True\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n logging.debug('hasImageData failed: no volume node')\\n return False\\n return True\",\n \"def exists(self) -> bool:\\n try:\\n result = self.get()\\n except KeyError:\\n return False\\n return True\",\n \"def _exists(cursor, table, data):\\n cursor.execute('SELECT 1 FROM {} WHERE ({}) = ({})'.format(table, *_query_fields(data)), data)\\n return bool(cursor.fetchone())\",\n \"async def exists(self, tag_name):\\n try:\\n if await self.get_id(tag_name):\\n return True\\n except RtbDoesntExists:\\n return False\",\n \"def _loaded_data(self):\\n try:\\n dsize = [int(d) for d\\n in self.run('fits size', via='get').split()]\\n except (ValueError, TypeError, AttributeError) as err:\\n log.debug(f' FITS size error: {err}')\\n return False\\n else:\\n if 0 in dsize:\\n return False\\n else:\\n return True\",\n \"def has_data(self, fit_id, species_id, start=None, stop=None):\\n if not (fit_id in self.raw_results and species_id in\\\\\\n self.raw_results[fit_id]):\\n return False\\n if all([isinstance(x, datetime) for x in [start, stop]]):\\n ts = self.raw_results[fit_id][\\\"start\\\"]\\n if not any([start < x < stop for x in ts]):\\n return False\\n return True\",\n \"def hasError(self, pin):\\r\\n return bool(self.Mask & (0b1 << pin))\",\n \"def exists(self, name):\\n assert name, \\\"Must input a valid dataset name.\\\"\\n return name in self.manager.data[\\\"dataset\\\"]\",\n \"def exist(self):\\n return self.file_path.exists()\",\n \"def _object_exists(name):\\n conn = sqlite3.connect('/dev/input')\\n try:\\n cur = conn.cursor()\\n sql = 'SELECT ROWID FROM object WHERE name=? AND deleted=0'\\n cur.execute(sql, (name, ))\\n result = cur.fetchall()\\n return len(result) > 0\\n finally:\\n conn.close()\",\n \"def exists(identifier, network):\\n foo = next(load(identifier, network), None)\\n return foo is not None\",\n \"def is_empty(self):\\n for key, dataset in self.datasets.items():\\n try:\\n has_data = dataset.has_data()\\n except MFDataException as mfde:\\n raise MFDataException(\\n mfdata_except=mfde,\\n model=self._container_package.model_name,\\n package=self._container_package._get_pname(),\\n message=\\\"Error occurred while verifying\\\"\\n ' data of dataset \\\"{}\\\" in block '\\n '\\\"{}\\\"'.format(dataset.structure.name, self.structure.name),\\n )\\n\\n if has_data is not None and has_data:\\n return False\\n return True\",\n \"def exists(self):\\n\\n return os.path.exists(self[\\\"~filename\\\"])\",\n \"def exists(self):\\r\\n return os.path.exists(self.full_path)\",\n \"def check_if_file_exists(self, sensor_id:str, name:str)->str:\\n ret_value = \\\"\\\"\\n file_name = '%s/%s.*.%s.json' % (self.generate_data_prep, sensor_id, name)\\n try: \\n ret_value = glob.glob(file_name)\\n except Exception as e:\\n print(\\\"OSError - Failed top get file (%s) - %s\\\" % (file_name, e))\\n ret_value = False \\n \\n if ret_value != False and len(ret_value) > 0: \\n ret_value = ret_value[0]\\n\\n return ret_value\",\n \"def race_entry_exists(self, race_id):\\n try:\\n self.consolidated_db.data.loc[race_id] # Throws a KeyError if no entry is in the dataframe.\\n return True\\n except KeyError:\\n return False\",\n \"def exists(self):\\n f = os.path.join(pth, '..', 'static/data', self.filename)\\n return os.path.isfile(f)\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n logging.debug('no volume node')\\n return False\\n if volumeNode.GetImageData() is None:\\n logging.debug('no image data')\\n return False\\n return True\",\n \"def check_residue(self, chain_id, resid, resname):\\n if resname in PTM_lookup.keys():\\n return\\n else:\\n try:\\n ref_resname = PTM_reverse_lookup[resname]\\n except KeyError:\\n # print \\\"skipping unrecognized residue\\\", resname\\n return\\n ptm_dict = PTM_lookup[ref_resname][resname]\\n return (chain_id, resid, ref_resname, ptm_dict[\\\"goto_atom\\\"], ptm_dict[\\\"name\\\"])\",\n \"def _check_row_exists(self, pk):\\n session = self.session_factory()\\n exists = session.query(PipelineRun).filter_by(id=pk).first()\\n session.close()\\n if exists:\\n return True\\n return False\",\n \"def pidExists(self, pid):\\n\\n prochash = self.getHash( 'datahash' ) # safely get copy of process dict\\n\\n try:\\n prochash[pid]\\n return 1\\n except KeyError:\\n return 0\",\n \"def pidExists(self, pid):\\n\\n prochash = self.getHash( 'datahash' ) # safely get copy of process dict\\n\\n try:\\n prochash[pid]\\n return 1\\n except KeyError:\\n return 0\",\n \"def check_exist(self):\\n helper.RbdImageOperator._check_rbd_image(self.real_path)\",\n \"def has_material(obj, name):\\n return name in obj.data.materials.keys()\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n print('no volume node')\\n return False\\n if volumeNode.GetImageData() == None:\\n print('no image data')\\n return False\\n return True\",\n \"def check_dataset_exists(dataset):\\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\\n return result == 0\",\n \"def item_exists(self, call_number):\\n return call_number in self.item_list.keys()\",\n \"def has_id(self, data):\\n # (Dict[str, Any]) -> bool\\n return self.id_column.name in data\",\n \"def test_molecule_loop_no_selection(self):\\n\\n # Molecule data.\\n name = ['Ap4Aase', 'RNA']\\n\\n # Loop over the molecules.\\n i = 0\\n for mol in mol_res_spin.molecule_loop():\\n # Test the molecule names.\\n self.assertEqual(mol.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)\",\n \"def task_validate_rawdata_file(pk):\\n\\n # init and checks\\n valid = False\\n logger = Logger.get_logger(StringIO())\\n try:\\n df = Data.objects.get(id=pk)\\n assert df.kind == 'rd_file'\\n tr = df.content_object\\n except:\\n logger.log('ERROR')\\n return valid\\n\\n try:\\n logger.log('looking at raw data file with pk: %s' % pk)\\n rd, sr = read_hdf5_arc(df.file.path)\\n logger.log('found rd_file: %s' % df.name)\\n len_rd_sec = rd.shape[0] / sr\\n logger.log('found data in %d channels, for %d sec' % (\\n rd.shape[1], len_rd_sec))\\n\\n # TODO: more checks?\\n\\n logger.log('rd_file passed all checks')\\n valid = True\\n except Exception, ex:\\n logger.log('ERROR: rawdata file check: %s' % str(ex))\\n finally:\\n df.save()\\n tr.valid_rd_log = logger.get_content()\\n tr.save()\\n return valid\",\n \"def check(self, mu):\\n return self.find(mu)[0] is not None\",\n \"def is_data_present(self, cycle: int, bus_item: BusItem) -> bool:\\n buffer = self.get_cycle_buffer(cycle)\\n if self.component_subtype == \\\"PEGB\\\":\\n return False\\n #print(buffer)\\n # for pe_id in buffer:\\n # pe_buffer = buffer[pe_id]\\n # # # TODO ad-hoc\\n # # if isinstance(pe_buffer, deque):\\n # # return False\\n # #print(pe_buffer)\\n #\\n # pe_read_buffer = pe_buffer[\\\"read\\\"]\\n # #print(pe_read_buffer)\\n # for data in pe_read_buffer:\\n # if data == bus_item:\\n # return True\\n elif self.component_subtype == \\\"PENB\\\":\\n read_buffer = buffer[\\\"read\\\"]\\n for entry in read_buffer:\\n if entry == bus_item:\\n return True\\n else:\\n for data in buffer:\\n if data == bus_item:\\n return True\\n return False\",\n \"def notebook_exists(self, name, path=''):\\n\\n\\t\\tos_path = self._get_os_path(name, path=path)\\n\\t\\treturn key_exists(self.bucket, os_path)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.8392751","0.823386","0.8206758","0.817102","0.8049526","0.75779665","0.6515433","0.63660663","0.5854637","0.57079095","0.5615342","0.55319315","0.552877","0.5456042","0.54262865","0.5386728","0.53743654","0.5337322","0.53064","0.5303351","0.5252378","0.5202764","0.5199057","0.518386","0.5181761","0.5138209","0.51238996","0.51179075","0.51161474","0.5106249","0.50874954","0.50516295","0.50516295","0.5039105","0.5025562","0.5024052","0.50036716","0.5001499","0.49964494","0.49821496","0.4975445","0.49717012","0.49692017","0.4966122","0.49638677","0.49547866","0.49472466","0.49395996","0.49313352","0.49109071","0.49042016","0.4902595","0.48818666","0.48772696","0.48772216","0.48697636","0.48667684","0.4864519","0.48560485","0.48520356","0.4848297","0.48450685","0.48437572","0.48431095","0.48426518","0.48336697","0.483169","0.48237398","0.48162717","0.48145005","0.48128644","0.48125252","0.4812162","0.48057058","0.48053294","0.48035577","0.4803093","0.4798875","0.4797848","0.4797135","0.47917426","0.47912914","0.4788284","0.4785832","0.4776126","0.4771883","0.47676823","0.47663724","0.47663724","0.4764386","0.47609645","0.47562605","0.47532523","0.47509405","0.47452828","0.47440404","0.4743485","0.4741196","0.47371083","0.4736755"],"string":"[\n \"0.8392751\",\n \"0.823386\",\n \"0.8206758\",\n \"0.817102\",\n \"0.8049526\",\n \"0.75779665\",\n \"0.6515433\",\n \"0.63660663\",\n \"0.5854637\",\n \"0.57079095\",\n \"0.5615342\",\n \"0.55319315\",\n \"0.552877\",\n \"0.5456042\",\n \"0.54262865\",\n \"0.5386728\",\n \"0.53743654\",\n \"0.5337322\",\n \"0.53064\",\n \"0.5303351\",\n \"0.5252378\",\n \"0.5202764\",\n \"0.5199057\",\n \"0.518386\",\n \"0.5181761\",\n \"0.5138209\",\n \"0.51238996\",\n \"0.51179075\",\n \"0.51161474\",\n \"0.5106249\",\n \"0.50874954\",\n \"0.50516295\",\n \"0.50516295\",\n \"0.5039105\",\n \"0.5025562\",\n \"0.5024052\",\n \"0.50036716\",\n \"0.5001499\",\n \"0.49964494\",\n \"0.49821496\",\n \"0.4975445\",\n \"0.49717012\",\n \"0.49692017\",\n \"0.4966122\",\n \"0.49638677\",\n \"0.49547866\",\n \"0.49472466\",\n \"0.49395996\",\n \"0.49313352\",\n \"0.49109071\",\n \"0.49042016\",\n \"0.4902595\",\n \"0.48818666\",\n \"0.48772696\",\n \"0.48772216\",\n \"0.48697636\",\n \"0.48667684\",\n \"0.4864519\",\n \"0.48560485\",\n \"0.48520356\",\n \"0.4848297\",\n \"0.48450685\",\n \"0.48437572\",\n \"0.48431095\",\n \"0.48426518\",\n \"0.48336697\",\n \"0.483169\",\n \"0.48237398\",\n \"0.48162717\",\n \"0.48145005\",\n \"0.48128644\",\n \"0.48125252\",\n \"0.4812162\",\n \"0.48057058\",\n \"0.48053294\",\n \"0.48035577\",\n \"0.4803093\",\n \"0.4798875\",\n \"0.4797848\",\n \"0.4797135\",\n \"0.47917426\",\n \"0.47912914\",\n \"0.4788284\",\n \"0.4785832\",\n \"0.4776126\",\n \"0.4771883\",\n \"0.47676823\",\n \"0.47663724\",\n \"0.47663724\",\n \"0.4764386\",\n \"0.47609645\",\n \"0.47562605\",\n \"0.47532523\",\n \"0.47509405\",\n \"0.47452828\",\n \"0.47440404\",\n \"0.4743485\",\n \"0.4741196\",\n \"0.47371083\",\n \"0.4736755\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8513595"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81480,"cells":{"query":{"kind":"string","value":"Determine if moleculeresiduespin data exists when no data exists. The function tested is pipe_control.mol_res_spin.exists_mol_res_spin_data()."},"document":{"kind":"string","value":"def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def isExist(data):\n return True/False","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def CheckForExistence(requested_data, available_data):\n if requested_data is not None:\n return 1 # The requested data exists.\n elif available_data:\n return -1 # The requested data does not exist.\n else:\n return 0 # No data exists at all.","def is_version_data_existed(self):\n # if exists, skip\n # return \n\n return True","def find_null(data, sub_reg):\r\n subreg_sqkm_data = data.loc[pd.IndexSlice[:, sub_reg, :], pd.IndexSlice['Sq Km']]\r\n if subreg_sqkm_data.isnull().values.any() == True:\r\n print(\"\\nSq km measurements are missing for:\")\r\n print(subreg_sqkm_data[subreg_sqkm_data.isnull()])\r\n else:\r\n print(\"\\nThere are no missing sq km values for this sub-region.\")","def test_count_no_spins(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 0)","def has_data(self) -> bool:\n raise NotImplementedError","def datafolderexist(name):\n folderpath = os.path.join(pathtofolder(), name)\n return os.path.exists(folderpath)","def has_data(self):\n return self._data is not None","def is_empty(self):\n for key, dataset in self.datasets.items():\n try:\n has_data = dataset.has_data()\n except MFDataException as mfde:\n raise MFDataException(\n mfdata_except=mfde,\n model=self._container_package.model_name,\n package=self._container_package._get_pname(),\n message=\"Error occurred while verifying\"\n ' data of dataset \"{}\" in block '\n '\"{}\"'.format(dataset.structure.name, self.structure.name),\n )\n\n if has_data is not None and has_data:\n return False\n return True","def has_data(self):\n return len(self.data) > 0","def exists(self, datadir):\n return False","def file_exists(msl_data_path, filename):\n return os.path.isfile(msl_data_path + filename)","def check_data_exist(data):\n if data is not None:\n if data.text is not None:\n return True\n return False","def has_data(self):\n\n return self._data is not None","def has_data(self):\n\n return self._data is not None","def exists(self):\n\t\tif self.hasUdim:\n\t\t\treturn len( self.udimPaths ) != 0\n\t\treturn super( textureFile, self ).exists","def _check_data_valid(self):\n\n is_valid = (sum(~np.isnan(self.data).flatten()) > 0 and self.data.flatten().sum() != 0)\n if not is_valid:\n raise FITSException(f\"No data in {self.survey}\")","def data_available(dataset_name=None):\r\n for file_list in data_resources[dataset_name]['files']:\r\n for file in file_list:\r\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\r\n return False\r\n return True","def check_for_data():\n if not (os.path.exists(ep.get_test_data_path()) or os.path.exists(ep.get_dbn_weight_path())):\n return False\n return True","def hasResidue(self, resname):\n if resname in self.map:\n return 1\n else:\n return 0","def hasImageData(self,volumeNode):\n if not volumeNode:\n logging.debug('hasImageData failed: no volume node')\n return False\n if volumeNode.GetImageData() is None:\n logging.debug('hasImageData failed: no image data in volume node')\n return False\n return True","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def has_data(self) -> bool:\n return bool(self.data)","def has_error(self):\r\n return self._arm.has_error","def check_exist(self):\n helper.RbdImageOperator._check_rbd_image(self.real_path)","def hasImageData(self,volumeNode):\n if not volumeNode:\n print('no volume node')\n return False\n if volumeNode.GetImageData() == None:\n print('no image data')\n return False\n return True","def hasImageData(self,volumeNode):\n if not volumeNode:\n logging.debug('no volume node')\n return False\n if volumeNode.GetImageData() is None:\n logging.debug('no image data')\n return False\n return True","def has_data(self, fragment, number):\n if fragment in self.mdv:\n if number in self.mdv[fragment]:\n return True\n return False","def data_ready(self) -> bool:\n data_ready = ctypes.c_uint8()\n Utils.check(VL53L1X_C_LIBRARY.VL53L1_GetMeasurementDataReady(self.dev, byref(data_ready)))\n return data_ready.value != 0","def hasImageData(self,volumeNode):\n if not volumeNode:\n logging.debug('hasImageData failed: no volume node')\n return False\n if volumeNode.GetImageData() is None:\n logging.debug('hasImageData failed: no image data in volume node')\n return False\n return True","def _check_notnull(self):\n candnull = self.df_test_resampled[self.candidate_col_name].isnull().all()\n refnull = self.df_test_resampled[self.reference_col_name].isnull().all()\n if candnull or refnull:\n return 1, 'No data for selected time frame'\n else:\n return 0, 'No error occurred'","def test_narrative_data_missing(self, config_handler):\n spec = Spec.from_dict(\n {\"name\": \"homogeneity_coefficient\", \"unit\": \"percentage\", \"dtype\": \"float\"}\n )\n with raises(SmifDataNotFoundError):\n config_handler.read_narrative_variant_data(\"does not exist\", spec)","def check_data(dataframe):\n if dataframe.iloc[0, 0] == 'No data available':\n return False\n else:\n return True","def checkIfThereIsData(self, i):\n _, amountOfThings = self.weaviate.Get(\"/\" + i)\n if len(amountOfThings[i]) == 0:\n return False\n else:\n return True","def datafileexist(filename):\n filePath = os.path.join(pathtofolder(), \"datas\", filename)\n fileFormat = '.csv'\n return os.path.exists(f'{filePath+fileFormat}')","def hasImageData(self,volumeNode):\n if not volumeNode:\n logging.debug('hasImageData failed: no volume node')\n return False\n return True","def check_data_struct():\n if not os.path.exists(PROJECT_ROOT+'/data'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data')\n\n if not os.path.exists(PROJECT_ROOT+'/data/CUB_200_2011'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/CUB_200_2011')\n\n if not os.path.exists(PROJECT_ROOT+'/data/segmentations'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/segmentations')\n\n if not os.path.exists(PROJECT_ROOT+'/data/attributes.txt'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/attributes.txt')","def exists(sim):\n return (sim['N'] > 0)","def has_data(self, time, fragment, number):\n if time in self.mdvtc.keys():\n if fragment in self.mdvtc[time].mdv.keys():\n if number in self.mdvtc[time].mdv[fragment].keys():\n return True\n return False","def exists(self):\n return os.path.exists(self.sensorpath)","def has_data(self, *args, **kwargs):\n return False","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def exists(self) -> bool:\n try:\n result = self.get()\n except KeyError:\n return False\n return True","def exist(self):","def check_model_exists(ckpt):\n expected_data = ckpt + \".data-00000-of-00001\"\n return os.path.exists(expected_data)","def data(self):\n file_name = join(PARENT_BASE_DIR, '.files', 'data.data.json')\n if isfile(file_name):\n debug(f'{file_name} file is exist.')\n debug(f'try for load {file_name} file ->->->->->->->->->->')\n start_load_file = time()\n with open(file_name, 'r', encoding='utf-8')as file:\n data = file.read()\n data = loads(data)\n debug(f'load file - [runtime: {time() - start_load_file}] <-<-<-<-<-<-<-<-<-<-')\n return data, 'data exist.'\n else:\n debug(f'{file_name} file is not exist.')\n return None, 'data not exist in \"base directory/.files/data.data.json\"'","def checkExistence(idMeta):\n # XXX add for diaries\n sqlq = \"\"\"\n SELECT dt\n FROM Electricity_10min\n WHERE `Meta_idMeta` = {}\n LIMIT 1;\n \"\"\".format(idMeta)\n try:\n result = mdb.getSQL(sqlq)[0]\n if (result):\n return True\n except:\n return False","def check_dataset_exists(dataset):\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\n return result == 0","def exists():\n\treturn os.path.exists('data/strmr.db')","def check_for_residue_existance(self):\n if not self.pose.total_residue():\n print \"No pose Loaded.\"\n return False\n\n if not self.current_chain.get() or not self.current_residue.get():\n print \"Chain or residue not set\"\n return False\n\n current_region = self.current_residue.get().split(\":\")\n if len(current_region)>1:\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\n\n\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\n print \"Region not found in pose\"\n return False\n else:\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\n\n print \"Residue not found in pose\"\n return False\n\n #If everythig is good then:\n return True","def checkIfStatisticReady(self, statistic):\n\n return statistic.final_json is not None","def checkfolderdata(folder = 'datas'):\n if datafolderexist(folder):\n return True\n else:\n createdatafolder(folder)\n checkfolderdata(folder)","def check_file_existing(k_out, sphere_radius,full_path):\n cwd = full_path\n file_names = ['/T_ns_', '/Energy_', '/Distance-e-to-e_',\n '/chain_on_iterations_']\n\n kout = f'{k_out:.3f}'\n spr_rad = f'{sphere_radius:.3f}'\n\n current = \"kout_\" + kout + \"_\" + \"spr_rad_\" + spr_rad\n for file_name in file_names:\n #print (cwd + file_name + current + \".pkl\")\n if not os.path.exists(cwd + file_name + current + \".pkl\"):\n return False\n return True","def _exists(cursor, table, data):\n cursor.execute('SELECT 1 FROM {} WHERE ({}) = ({})'.format(table, *_query_fields(data)), data)\n return bool(cursor.fetchone())","def __check_array__(self):\n if self.data_array is None:\n mess = 'No data array is present, please load before attempting to create XYZ array.'\n if isinstance(self.mess_inst, MessagesGUI):\n self.mess_inst.message(mess)\n else:\n print(mess)\n return False\n else:\n return True","def exists(self):\n f = os.path.join(pth, '..', 'static/data', self.filename)\n return os.path.isfile(f)","def check_if_file_exists(self, sensor_id:str, name:str)->str:\n ret_value = \"\"\n file_name = '%s/%s.*.%s.json' % (self.generate_data_prep, sensor_id, name)\n try: \n ret_value = glob.glob(file_name)\n except Exception as e:\n print(\"OSError - Failed top get file (%s) - %s\" % (file_name, e))\n ret_value = False \n \n if ret_value != False and len(ret_value) > 0: \n ret_value = ret_value[0]\n\n return ret_value","def IndexExists(self, arg0: 'unsigned long long') -> \"bool\":\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF3GQEULLULLBBT_IndexExists(self, arg0)","def exists(self):\n try:\n self.world.find(self.ehandle)\n except KeyError:\n return False\n else:\n return True","def check_data_exist(hdir):\n cmd = 'ls ' + hdir + '*/* > ' + zspace\n os.system(cmd)\n with open(zspace, 'r') as f:\n out = f.read()\n mcf.rm_files(zspace)\n\n for name in ['dtf1', 'fov', 'bpix1', 'evt1', 'msk1', 'mtl1', 'std_dtfstat1', 'std_flt1', 'asol']:\n mc = re.search(name, out)\n if mc is None:\n line = 'Some data files are missing and the re-process is terminated. Check: ' + hdir + '\\n'\n with open(zspace, 'w') as fo:\n fo.write(line)\n\n cmd = 'cat ' + zspace + ' | mailx -s \"Subject: hrc re-process failed\" tisobe@cfa.harvard.edu'\n os.system(cmd)\n\n return False\n\n return True","def _loaded_data(self):\n try:\n dsize = [int(d) for d\n in self.run('fits size', via='get').split()]\n except (ValueError, TypeError, AttributeError) as err:\n log.debug(f' FITS size error: {err}')\n return False\n else:\n if 0 in dsize:\n return False\n else:\n return True","def f_is_empty(self):\n return self._data is None","def observation_exists(self, concatenated_observation_data):\n local_observation = self.observation_exists_locally(\n concatenated_observation_data\n )\n if local_observation:\n return local_observation\n\n try:\n return Observation.objects.get(\n concatenated_data=concatenated_observation_data\n )\n except ObjectDoesNotExist:\n return None","def IndexExists(self, arg0: 'unsigned long long') -> \"bool\":\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF2GQEULLULLBBT_IndexExists(self, arg0)","def object_exists(self, fname):\n return False","def is_finished(self):\n for i in range(self.rows):\n for j in range(self.cols):\n if self.cubes[i][j].value == 0:\n return False\n return True","def is_present(self):\n try:\n self.read_binary(0, 2)\n return True\n except:\n return False","def exists(self):\r\n try:\r\n self.refresh()\r\n except:\r\n return False\r\n return True","def object_exists(self, name: str):\n file_path = self.__get_file_path(name)\n return os.path.exists(file_path)","def is_stock_data_exists(self, stock_code):\n conn = self.db_engine.connect()\n try:\n num = pd.read_sql(\"\"\"\n SELECT count(1) AS num FROM \"{0}\".\"{1}\"\n WHERE stock_code='{2}' AND end_update_time IS NOT NULL\n \"\"\".format(Schemas.SCHEMA_META, Tables.TABLE_TICK_UPDATE_LOGS,\n stock_code), con=conn)['num'][0]\n except:\n self.logger.log_error(traceback.format_exc())\n return Error.ERROR_DB_EXECUTION_FAILED, None\n finally:\n conn.close()\n\n return Error.SUCCESS, num > 0","def exists():\n check50.include(\"data\")\n check50.exists(\"adventure.py\")\n check50.exists(\"room.py\")","def isUndefinedData(program: ghidra.program.model.listing.Program, addr: ghidra.program.model.address.Address) -> bool:\n ...","def assert_data_fragments_correct(self) -> bool:\n read_path = Path(os.environ[\"DATA_PATH\"]) / \"fragments\"\n if not read_path.exists():\n return False\n bin_images = [img for img in read_path.iterdir() if \"binarized\" in img.name]\n if len(bin_images) == 0:\n return False\n return True","def test_return_single_residue_info(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_single_residue_info('1')\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\n res5 = mol_res_spin.return_single_residue_info('-5')\n\n # Test the data of residue 1.\n self.assertEqual(res1, (1, None))\n\n # Test the data of residue 2.\n self.assertEqual(res2, (2, 'Glu'))\n\n # Test the data of residue 4.\n self.assertEqual(res4, (4, 'Pro'))\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5, (-5, None))","def exist(self):\n return self.file_path.exists()","def is_data_run(info, runinfo):\n this_run_in_runinfo = runinfo[\n (runinfo.fNight==info[\"night_int\"])&\n (runinfo.fRunID==info[\"run\"])\n ]\n return len(this_run_in_runinfo) > 0 and this_run_in_runinfo.iloc[0].fRunTypeKey == 1","def particleExists(*args, **kwargs)->bool:\n pass","def has_error(self):\n return self.error_found","def check_Data(self):\r\n \r\n if self._target_data is None:\r\n self.processData()","def has_data(self):\n if len(self.channels) > 0:\n return True\n return False","def HasData(self, search_all_index = False):\n\t\tif not search_all_index:\n\t\t\treturn ExistsFile(self.__datafilename(self.__pindex))\n\t\tfor pindex in range(0, len(GV.provinces)):\n\t\t\tif ExistsFile(self.__datafilename(pindex)):\n\t\t\t\treturn True\n\t\treturn False","def get_data_not_yet_ready_file(self):\n pass","def object_exists(self, fname):\n return True","def exists(dtype, name, rootdir=None):\n return FreezableAPI.to_slug(dtype,name) in FreezableAPI.datasets(rootdir=rootdir)","def exists(self):\r\n return os.path.exists(self.full_path)","def object_exists(self, fname):\n return self.object_exists","def race_entry_exists(self, race_id):\n try:\n self.consolidated_db.data.loc[race_id] # Throws a KeyError if no entry is in the dataframe.\n return True\n except KeyError:\n return False","def check_resource_data(self, resource):\n if pd.isna(resource).any().any():\n bad_vars = pd.isna(resource).any(axis=0)\n bad_vars = resource.columns[bad_vars].values.tolist()\n msg = ('Found NaN values for site {} in variables {}'\n .format(self.site, bad_vars))\n logger.error(msg)\n raise InputError(msg)","def exists(self, name):\n assert name, \"Must input a valid dataset name.\"\n return name in self.manager.data[\"dataset\"]","def check_path(data_pointer, log, msg):\n if not os.path.exists(data_pointer):\n log.debug(msg)\n return False\n else:\n return data_pointer"],"string":"[\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def isExist(data):\\n return True/False\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_molecule_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the molecules.\\n i = 0\\n for molecule in mol_res_spin.molecule_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def CheckForExistence(requested_data, available_data):\\n if requested_data is not None:\\n return 1 # The requested data exists.\\n elif available_data:\\n return -1 # The requested data does not exist.\\n else:\\n return 0 # No data exists at all.\",\n \"def is_version_data_existed(self):\\n # if exists, skip\\n # return \\n\\n return True\",\n \"def find_null(data, sub_reg):\\r\\n subreg_sqkm_data = data.loc[pd.IndexSlice[:, sub_reg, :], pd.IndexSlice['Sq Km']]\\r\\n if subreg_sqkm_data.isnull().values.any() == True:\\r\\n print(\\\"\\\\nSq km measurements are missing for:\\\")\\r\\n print(subreg_sqkm_data[subreg_sqkm_data.isnull()])\\r\\n else:\\r\\n print(\\\"\\\\nThere are no missing sq km values for this sub-region.\\\")\",\n \"def test_count_no_spins(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Test the number of spins counted.\\n self.assertEqual(mol_res_spin.count_spins(), 0)\",\n \"def has_data(self) -> bool:\\n raise NotImplementedError\",\n \"def datafolderexist(name):\\n folderpath = os.path.join(pathtofolder(), name)\\n return os.path.exists(folderpath)\",\n \"def has_data(self):\\n return self._data is not None\",\n \"def is_empty(self):\\n for key, dataset in self.datasets.items():\\n try:\\n has_data = dataset.has_data()\\n except MFDataException as mfde:\\n raise MFDataException(\\n mfdata_except=mfde,\\n model=self._container_package.model_name,\\n package=self._container_package._get_pname(),\\n message=\\\"Error occurred while verifying\\\"\\n ' data of dataset \\\"{}\\\" in block '\\n '\\\"{}\\\"'.format(dataset.structure.name, self.structure.name),\\n )\\n\\n if has_data is not None and has_data:\\n return False\\n return True\",\n \"def has_data(self):\\n return len(self.data) > 0\",\n \"def exists(self, datadir):\\n return False\",\n \"def file_exists(msl_data_path, filename):\\n return os.path.isfile(msl_data_path + filename)\",\n \"def check_data_exist(data):\\n if data is not None:\\n if data.text is not None:\\n return True\\n return False\",\n \"def has_data(self):\\n\\n return self._data is not None\",\n \"def has_data(self):\\n\\n return self._data is not None\",\n \"def exists(self):\\n\\t\\tif self.hasUdim:\\n\\t\\t\\treturn len( self.udimPaths ) != 0\\n\\t\\treturn super( textureFile, self ).exists\",\n \"def _check_data_valid(self):\\n\\n is_valid = (sum(~np.isnan(self.data).flatten()) > 0 and self.data.flatten().sum() != 0)\\n if not is_valid:\\n raise FITSException(f\\\"No data in {self.survey}\\\")\",\n \"def data_available(dataset_name=None):\\r\\n for file_list in data_resources[dataset_name]['files']:\\r\\n for file in file_list:\\r\\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\\r\\n return False\\r\\n return True\",\n \"def check_for_data():\\n if not (os.path.exists(ep.get_test_data_path()) or os.path.exists(ep.get_dbn_weight_path())):\\n return False\\n return True\",\n \"def hasResidue(self, resname):\\n if resname in self.map:\\n return 1\\n else:\\n return 0\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n logging.debug('hasImageData failed: no volume node')\\n return False\\n if volumeNode.GetImageData() is None:\\n logging.debug('hasImageData failed: no image data in volume node')\\n return False\\n return True\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def has_data(self) -> bool:\\n return bool(self.data)\",\n \"def has_error(self):\\r\\n return self._arm.has_error\",\n \"def check_exist(self):\\n helper.RbdImageOperator._check_rbd_image(self.real_path)\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n print('no volume node')\\n return False\\n if volumeNode.GetImageData() == None:\\n print('no image data')\\n return False\\n return True\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n logging.debug('no volume node')\\n return False\\n if volumeNode.GetImageData() is None:\\n logging.debug('no image data')\\n return False\\n return True\",\n \"def has_data(self, fragment, number):\\n if fragment in self.mdv:\\n if number in self.mdv[fragment]:\\n return True\\n return False\",\n \"def data_ready(self) -> bool:\\n data_ready = ctypes.c_uint8()\\n Utils.check(VL53L1X_C_LIBRARY.VL53L1_GetMeasurementDataReady(self.dev, byref(data_ready)))\\n return data_ready.value != 0\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n logging.debug('hasImageData failed: no volume node')\\n return False\\n if volumeNode.GetImageData() is None:\\n logging.debug('hasImageData failed: no image data in volume node')\\n return False\\n return True\",\n \"def _check_notnull(self):\\n candnull = self.df_test_resampled[self.candidate_col_name].isnull().all()\\n refnull = self.df_test_resampled[self.reference_col_name].isnull().all()\\n if candnull or refnull:\\n return 1, 'No data for selected time frame'\\n else:\\n return 0, 'No error occurred'\",\n \"def test_narrative_data_missing(self, config_handler):\\n spec = Spec.from_dict(\\n {\\\"name\\\": \\\"homogeneity_coefficient\\\", \\\"unit\\\": \\\"percentage\\\", \\\"dtype\\\": \\\"float\\\"}\\n )\\n with raises(SmifDataNotFoundError):\\n config_handler.read_narrative_variant_data(\\\"does not exist\\\", spec)\",\n \"def check_data(dataframe):\\n if dataframe.iloc[0, 0] == 'No data available':\\n return False\\n else:\\n return True\",\n \"def checkIfThereIsData(self, i):\\n _, amountOfThings = self.weaviate.Get(\\\"/\\\" + i)\\n if len(amountOfThings[i]) == 0:\\n return False\\n else:\\n return True\",\n \"def datafileexist(filename):\\n filePath = os.path.join(pathtofolder(), \\\"datas\\\", filename)\\n fileFormat = '.csv'\\n return os.path.exists(f'{filePath+fileFormat}')\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n logging.debug('hasImageData failed: no volume node')\\n return False\\n return True\",\n \"def check_data_struct():\\n if not os.path.exists(PROJECT_ROOT+'/data'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data')\\n\\n if not os.path.exists(PROJECT_ROOT+'/data/CUB_200_2011'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/CUB_200_2011')\\n\\n if not os.path.exists(PROJECT_ROOT+'/data/segmentations'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/segmentations')\\n\\n if not os.path.exists(PROJECT_ROOT+'/data/attributes.txt'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/attributes.txt')\",\n \"def exists(sim):\\n return (sim['N'] > 0)\",\n \"def has_data(self, time, fragment, number):\\n if time in self.mdvtc.keys():\\n if fragment in self.mdvtc[time].mdv.keys():\\n if number in self.mdvtc[time].mdv[fragment].keys():\\n return True\\n return False\",\n \"def exists(self):\\n return os.path.exists(self.sensorpath)\",\n \"def has_data(self, *args, **kwargs):\\n return False\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def exists(self) -> bool:\\n try:\\n result = self.get()\\n except KeyError:\\n return False\\n return True\",\n \"def exist(self):\",\n \"def check_model_exists(ckpt):\\n expected_data = ckpt + \\\".data-00000-of-00001\\\"\\n return os.path.exists(expected_data)\",\n \"def data(self):\\n file_name = join(PARENT_BASE_DIR, '.files', 'data.data.json')\\n if isfile(file_name):\\n debug(f'{file_name} file is exist.')\\n debug(f'try for load {file_name} file ->->->->->->->->->->')\\n start_load_file = time()\\n with open(file_name, 'r', encoding='utf-8')as file:\\n data = file.read()\\n data = loads(data)\\n debug(f'load file - [runtime: {time() - start_load_file}] <-<-<-<-<-<-<-<-<-<-')\\n return data, 'data exist.'\\n else:\\n debug(f'{file_name} file is not exist.')\\n return None, 'data not exist in \\\"base directory/.files/data.data.json\\\"'\",\n \"def checkExistence(idMeta):\\n # XXX add for diaries\\n sqlq = \\\"\\\"\\\"\\n SELECT dt\\n FROM Electricity_10min\\n WHERE `Meta_idMeta` = {}\\n LIMIT 1;\\n \\\"\\\"\\\".format(idMeta)\\n try:\\n result = mdb.getSQL(sqlq)[0]\\n if (result):\\n return True\\n except:\\n return False\",\n \"def check_dataset_exists(dataset):\\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\\n return result == 0\",\n \"def exists():\\n\\treturn os.path.exists('data/strmr.db')\",\n \"def check_for_residue_existance(self):\\n if not self.pose.total_residue():\\n print \\\"No pose Loaded.\\\"\\n return False\\n\\n if not self.current_chain.get() or not self.current_residue.get():\\n print \\\"Chain or residue not set\\\"\\n return False\\n\\n current_region = self.current_residue.get().split(\\\":\\\")\\n if len(current_region)>1:\\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\\n\\n\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\\n print \\\"Region not found in pose\\\"\\n return False\\n else:\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\\n\\n print \\\"Residue not found in pose\\\"\\n return False\\n\\n #If everythig is good then:\\n return True\",\n \"def checkIfStatisticReady(self, statistic):\\n\\n return statistic.final_json is not None\",\n \"def checkfolderdata(folder = 'datas'):\\n if datafolderexist(folder):\\n return True\\n else:\\n createdatafolder(folder)\\n checkfolderdata(folder)\",\n \"def check_file_existing(k_out, sphere_radius,full_path):\\n cwd = full_path\\n file_names = ['/T_ns_', '/Energy_', '/Distance-e-to-e_',\\n '/chain_on_iterations_']\\n\\n kout = f'{k_out:.3f}'\\n spr_rad = f'{sphere_radius:.3f}'\\n\\n current = \\\"kout_\\\" + kout + \\\"_\\\" + \\\"spr_rad_\\\" + spr_rad\\n for file_name in file_names:\\n #print (cwd + file_name + current + \\\".pkl\\\")\\n if not os.path.exists(cwd + file_name + current + \\\".pkl\\\"):\\n return False\\n return True\",\n \"def _exists(cursor, table, data):\\n cursor.execute('SELECT 1 FROM {} WHERE ({}) = ({})'.format(table, *_query_fields(data)), data)\\n return bool(cursor.fetchone())\",\n \"def __check_array__(self):\\n if self.data_array is None:\\n mess = 'No data array is present, please load before attempting to create XYZ array.'\\n if isinstance(self.mess_inst, MessagesGUI):\\n self.mess_inst.message(mess)\\n else:\\n print(mess)\\n return False\\n else:\\n return True\",\n \"def exists(self):\\n f = os.path.join(pth, '..', 'static/data', self.filename)\\n return os.path.isfile(f)\",\n \"def check_if_file_exists(self, sensor_id:str, name:str)->str:\\n ret_value = \\\"\\\"\\n file_name = '%s/%s.*.%s.json' % (self.generate_data_prep, sensor_id, name)\\n try: \\n ret_value = glob.glob(file_name)\\n except Exception as e:\\n print(\\\"OSError - Failed top get file (%s) - %s\\\" % (file_name, e))\\n ret_value = False \\n \\n if ret_value != False and len(ret_value) > 0: \\n ret_value = ret_value[0]\\n\\n return ret_value\",\n \"def IndexExists(self, arg0: 'unsigned long long') -> \\\"bool\\\":\\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF3GQEULLULLBBT_IndexExists(self, arg0)\",\n \"def exists(self):\\n try:\\n self.world.find(self.ehandle)\\n except KeyError:\\n return False\\n else:\\n return True\",\n \"def check_data_exist(hdir):\\n cmd = 'ls ' + hdir + '*/* > ' + zspace\\n os.system(cmd)\\n with open(zspace, 'r') as f:\\n out = f.read()\\n mcf.rm_files(zspace)\\n\\n for name in ['dtf1', 'fov', 'bpix1', 'evt1', 'msk1', 'mtl1', 'std_dtfstat1', 'std_flt1', 'asol']:\\n mc = re.search(name, out)\\n if mc is None:\\n line = 'Some data files are missing and the re-process is terminated. Check: ' + hdir + '\\\\n'\\n with open(zspace, 'w') as fo:\\n fo.write(line)\\n\\n cmd = 'cat ' + zspace + ' | mailx -s \\\"Subject: hrc re-process failed\\\" tisobe@cfa.harvard.edu'\\n os.system(cmd)\\n\\n return False\\n\\n return True\",\n \"def _loaded_data(self):\\n try:\\n dsize = [int(d) for d\\n in self.run('fits size', via='get').split()]\\n except (ValueError, TypeError, AttributeError) as err:\\n log.debug(f' FITS size error: {err}')\\n return False\\n else:\\n if 0 in dsize:\\n return False\\n else:\\n return True\",\n \"def f_is_empty(self):\\n return self._data is None\",\n \"def observation_exists(self, concatenated_observation_data):\\n local_observation = self.observation_exists_locally(\\n concatenated_observation_data\\n )\\n if local_observation:\\n return local_observation\\n\\n try:\\n return Observation.objects.get(\\n concatenated_data=concatenated_observation_data\\n )\\n except ObjectDoesNotExist:\\n return None\",\n \"def IndexExists(self, arg0: 'unsigned long long') -> \\\"bool\\\":\\n return _itkQuadEdgeCellTraitsInfoPython.itkMapContainerULLQEMPF2GQEULLULLBBT_IndexExists(self, arg0)\",\n \"def object_exists(self, fname):\\n return False\",\n \"def is_finished(self):\\n for i in range(self.rows):\\n for j in range(self.cols):\\n if self.cubes[i][j].value == 0:\\n return False\\n return True\",\n \"def is_present(self):\\n try:\\n self.read_binary(0, 2)\\n return True\\n except:\\n return False\",\n \"def exists(self):\\r\\n try:\\r\\n self.refresh()\\r\\n except:\\r\\n return False\\r\\n return True\",\n \"def object_exists(self, name: str):\\n file_path = self.__get_file_path(name)\\n return os.path.exists(file_path)\",\n \"def is_stock_data_exists(self, stock_code):\\n conn = self.db_engine.connect()\\n try:\\n num = pd.read_sql(\\\"\\\"\\\"\\n SELECT count(1) AS num FROM \\\"{0}\\\".\\\"{1}\\\"\\n WHERE stock_code='{2}' AND end_update_time IS NOT NULL\\n \\\"\\\"\\\".format(Schemas.SCHEMA_META, Tables.TABLE_TICK_UPDATE_LOGS,\\n stock_code), con=conn)['num'][0]\\n except:\\n self.logger.log_error(traceback.format_exc())\\n return Error.ERROR_DB_EXECUTION_FAILED, None\\n finally:\\n conn.close()\\n\\n return Error.SUCCESS, num > 0\",\n \"def exists():\\n check50.include(\\\"data\\\")\\n check50.exists(\\\"adventure.py\\\")\\n check50.exists(\\\"room.py\\\")\",\n \"def isUndefinedData(program: ghidra.program.model.listing.Program, addr: ghidra.program.model.address.Address) -> bool:\\n ...\",\n \"def assert_data_fragments_correct(self) -> bool:\\n read_path = Path(os.environ[\\\"DATA_PATH\\\"]) / \\\"fragments\\\"\\n if not read_path.exists():\\n return False\\n bin_images = [img for img in read_path.iterdir() if \\\"binarized\\\" in img.name]\\n if len(bin_images) == 0:\\n return False\\n return True\",\n \"def test_return_single_residue_info(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_single_residue_info('1')\\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\\n res5 = mol_res_spin.return_single_residue_info('-5')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1, (1, None))\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2, (2, 'Glu'))\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4, (4, 'Pro'))\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5, (-5, None))\",\n \"def exist(self):\\n return self.file_path.exists()\",\n \"def is_data_run(info, runinfo):\\n this_run_in_runinfo = runinfo[\\n (runinfo.fNight==info[\\\"night_int\\\"])&\\n (runinfo.fRunID==info[\\\"run\\\"])\\n ]\\n return len(this_run_in_runinfo) > 0 and this_run_in_runinfo.iloc[0].fRunTypeKey == 1\",\n \"def particleExists(*args, **kwargs)->bool:\\n pass\",\n \"def has_error(self):\\n return self.error_found\",\n \"def check_Data(self):\\r\\n \\r\\n if self._target_data is None:\\r\\n self.processData()\",\n \"def has_data(self):\\n if len(self.channels) > 0:\\n return True\\n return False\",\n \"def HasData(self, search_all_index = False):\\n\\t\\tif not search_all_index:\\n\\t\\t\\treturn ExistsFile(self.__datafilename(self.__pindex))\\n\\t\\tfor pindex in range(0, len(GV.provinces)):\\n\\t\\t\\tif ExistsFile(self.__datafilename(pindex)):\\n\\t\\t\\t\\treturn True\\n\\t\\treturn False\",\n \"def get_data_not_yet_ready_file(self):\\n pass\",\n \"def object_exists(self, fname):\\n return True\",\n \"def exists(dtype, name, rootdir=None):\\n return FreezableAPI.to_slug(dtype,name) in FreezableAPI.datasets(rootdir=rootdir)\",\n \"def exists(self):\\r\\n return os.path.exists(self.full_path)\",\n \"def object_exists(self, fname):\\n return self.object_exists\",\n \"def race_entry_exists(self, race_id):\\n try:\\n self.consolidated_db.data.loc[race_id] # Throws a KeyError if no entry is in the dataframe.\\n return True\\n except KeyError:\\n return False\",\n \"def check_resource_data(self, resource):\\n if pd.isna(resource).any().any():\\n bad_vars = pd.isna(resource).any(axis=0)\\n bad_vars = resource.columns[bad_vars].values.tolist()\\n msg = ('Found NaN values for site {} in variables {}'\\n .format(self.site, bad_vars))\\n logger.error(msg)\\n raise InputError(msg)\",\n \"def exists(self, name):\\n assert name, \\\"Must input a valid dataset name.\\\"\\n return name in self.manager.data[\\\"dataset\\\"]\",\n \"def check_path(data_pointer, log, msg):\\n if not os.path.exists(data_pointer):\\n log.debug(msg)\\n return False\\n else:\\n return data_pointer\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.86641157","0.8070875","0.80186194","0.7868918","0.77041644","0.74484134","0.70216393","0.65485287","0.62315524","0.58949995","0.57270414","0.56871605","0.5657348","0.55692613","0.5513263","0.54984736","0.5497161","0.5481748","0.54525614","0.5450925","0.54388183","0.5406339","0.53657335","0.5355811","0.5355811","0.5350778","0.5341495","0.53017735","0.52996707","0.52966595","0.52885866","0.5276143","0.5266837","0.52622414","0.5206072","0.5202674","0.51862824","0.5177456","0.5169517","0.51370424","0.51347876","0.5126996","0.51168704","0.511479","0.51146257","0.51144385","0.5099447","0.50660443","0.50604916","0.5051816","0.50401056","0.5026022","0.5010882","0.5004063","0.49921292","0.4987414","0.4986773","0.498029","0.49761283","0.49686736","0.49615484","0.49590027","0.49574438","0.49564293","0.49535203","0.4940448","0.4928709","0.4923579","0.49222773","0.49205434","0.4913223","0.48997742","0.48959357","0.48899558","0.48854196","0.48835286","0.48784587","0.48776227","0.4874964","0.48731154","0.48608556","0.4860103","0.48583764","0.48567742","0.48473588","0.4840397","0.4833516","0.48298126","0.48282284","0.48216456","0.48190257","0.48184243","0.4815044","0.48144925","0.48107463","0.48080346","0.4800753","0.47968677","0.47939306","0.4791374"],"string":"[\n \"0.86641157\",\n \"0.8070875\",\n \"0.80186194\",\n \"0.7868918\",\n \"0.77041644\",\n \"0.74484134\",\n \"0.70216393\",\n \"0.65485287\",\n \"0.62315524\",\n \"0.58949995\",\n \"0.57270414\",\n \"0.56871605\",\n \"0.5657348\",\n \"0.55692613\",\n \"0.5513263\",\n \"0.54984736\",\n \"0.5497161\",\n \"0.5481748\",\n \"0.54525614\",\n \"0.5450925\",\n \"0.54388183\",\n \"0.5406339\",\n \"0.53657335\",\n \"0.5355811\",\n \"0.5355811\",\n \"0.5350778\",\n \"0.5341495\",\n \"0.53017735\",\n \"0.52996707\",\n \"0.52966595\",\n \"0.52885866\",\n \"0.5276143\",\n \"0.5266837\",\n \"0.52622414\",\n \"0.5206072\",\n \"0.5202674\",\n \"0.51862824\",\n \"0.5177456\",\n \"0.5169517\",\n \"0.51370424\",\n \"0.51347876\",\n \"0.5126996\",\n \"0.51168704\",\n \"0.511479\",\n \"0.51146257\",\n \"0.51144385\",\n \"0.5099447\",\n \"0.50660443\",\n \"0.50604916\",\n \"0.5051816\",\n \"0.50401056\",\n \"0.5026022\",\n \"0.5010882\",\n \"0.5004063\",\n \"0.49921292\",\n \"0.4987414\",\n \"0.4986773\",\n \"0.498029\",\n \"0.49761283\",\n \"0.49686736\",\n \"0.49615484\",\n \"0.49590027\",\n \"0.49574438\",\n \"0.49564293\",\n \"0.49535203\",\n \"0.4940448\",\n \"0.4928709\",\n \"0.4923579\",\n \"0.49222773\",\n \"0.49205434\",\n \"0.4913223\",\n \"0.48997742\",\n \"0.48959357\",\n \"0.48899558\",\n \"0.48854196\",\n \"0.48835286\",\n \"0.48784587\",\n \"0.48776227\",\n \"0.4874964\",\n \"0.48731154\",\n \"0.48608556\",\n \"0.4860103\",\n \"0.48583764\",\n \"0.48567742\",\n \"0.48473588\",\n \"0.4840397\",\n \"0.4833516\",\n \"0.48298126\",\n \"0.48282284\",\n \"0.48216456\",\n \"0.48190257\",\n \"0.48184243\",\n \"0.4815044\",\n \"0.48144925\",\n \"0.48107463\",\n \"0.48080346\",\n \"0.4800753\",\n \"0.47968677\",\n \"0.47939306\",\n \"0.4791374\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8743408"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81481,"cells":{"query":{"kind":"string","value":"Determine if moleculeresiduespin data exists when no data pipe exists. The function tested is pipe_control.mol_res_spin.exists_mol_res_spin_data()."},"document":{"kind":"string","value":"def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def isExist(data):\n return True/False","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_count_no_spins(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 0)","def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_return_spin_pipe_fail(self):\n\n # Try to get a spin from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')","def has_data(self):\n return self._data is not None","def is_version_data_existed(self):\n # if exists, skip\n # return \n\n return True","def CheckForExistence(requested_data, available_data):\n if requested_data is not None:\n return 1 # The requested data exists.\n elif available_data:\n return -1 # The requested data does not exist.\n else:\n return 0 # No data exists at all.","def has_data(self):\n return len(self.data) > 0","def has_data(self) -> bool:\n raise NotImplementedError","def has_data(self):\n\n return self._data is not None","def has_data(self):\n\n return self._data is not None","def data_available(dataset_name=None):\r\n for file_list in data_resources[dataset_name]['files']:\r\n for file in file_list:\r\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\r\n return False\r\n return True","def datafolderexist(name):\n folderpath = os.path.join(pathtofolder(), name)\n return os.path.exists(folderpath)","def exists(self, datadir):\n return False","def hasImageData(self,volumeNode):\n if not volumeNode:\n logging.debug('hasImageData failed: no volume node')\n return False\n if volumeNode.GetImageData() is None:\n logging.debug('hasImageData failed: no image data in volume node')\n return False\n return True","def is_empty(self):\n for key, dataset in self.datasets.items():\n try:\n has_data = dataset.has_data()\n except MFDataException as mfde:\n raise MFDataException(\n mfdata_except=mfde,\n model=self._container_package.model_name,\n package=self._container_package._get_pname(),\n message=\"Error occurred while verifying\"\n ' data of dataset \"{}\" in block '\n '\"{}\"'.format(dataset.structure.name, self.structure.name),\n )\n\n if has_data is not None and has_data:\n return False\n return True","def has_data(self) -> bool:\n return bool(self.data)","def check_for_data():\n if not (os.path.exists(ep.get_test_data_path()) or os.path.exists(ep.get_dbn_weight_path())):\n return False\n return True","def hasImageData(self,volumeNode):\n if not volumeNode:\n print('no volume node')\n return False\n if volumeNode.GetImageData() == None:\n print('no image data')\n return False\n return True","def check_pipe_setup(pipe=None, sequence=False, j=False):\n\n # The data pipe.\n if pipe == None:\n pipe = pipes.cdp_name()\n\n # Get the data pipe.\n dp = pipes.get_pipe(pipe)\n\n # Test if the current data pipe exists.\n check_pipe(pipe)\n\n # Test if sequence data exists.\n if sequence and not exists_mol_res_spin_data(pipe):\n raise RelaxNoSequenceError(pipe)\n\n # Test if J coupling data exists.\n if j:\n # Search for interatomic data.\n data = False\n for interatom in interatomic_loop():\n if hasattr(interatom, 'j_coupling'):\n data = True\n break\n\n # No data.\n if not data:\n raise RelaxNoJError()","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def _check_data_valid(self):\n\n is_valid = (sum(~np.isnan(self.data).flatten()) > 0 and self.data.flatten().sum() != 0)\n if not is_valid:\n raise FITSException(f\"No data in {self.survey}\")","def hasImageData(self,volumeNode):\n if not volumeNode:\n logging.debug('no volume node')\n return False\n if volumeNode.GetImageData() is None:\n logging.debug('no image data')\n return False\n return True","def find_null(data, sub_reg):\r\n subreg_sqkm_data = data.loc[pd.IndexSlice[:, sub_reg, :], pd.IndexSlice['Sq Km']]\r\n if subreg_sqkm_data.isnull().values.any() == True:\r\n print(\"\\nSq km measurements are missing for:\")\r\n print(subreg_sqkm_data[subreg_sqkm_data.isnull()])\r\n else:\r\n print(\"\\nThere are no missing sq km values for this sub-region.\")","def check_data_exist(data):\n if data is not None:\n if data.text is not None:\n return True\n return False","def file_exists(msl_data_path, filename):\n return os.path.isfile(msl_data_path + filename)","def data_ready(self) -> bool:\n data_ready = ctypes.c_uint8()\n Utils.check(VL53L1X_C_LIBRARY.VL53L1_GetMeasurementDataReady(self.dev, byref(data_ready)))\n return data_ready.value != 0","def hasImageData(self,volumeNode):\n if not volumeNode:\n logging.debug('hasImageData failed: no volume node')\n return False\n if volumeNode.GetImageData() is None:\n logging.debug('hasImageData failed: no image data in volume node')\n return False\n return True","def hasImageData(self,volumeNode):\n if not volumeNode:\n logging.debug('hasImageData failed: no volume node')\n return False\n return True","def has_data(self, *args, **kwargs):\n return False","def has_error(self):\r\n return self._arm.has_error","def test_return_residue_pipe_fail(self):\n\n # Try to get a residue from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')","def check_dataset_exists(dataset):\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\n return result == 0","def datafileexist(filename):\n filePath = os.path.join(pathtofolder(), \"datas\", filename)\n fileFormat = '.csv'\n return os.path.exists(f'{filePath+fileFormat}')","def check_data_struct():\n if not os.path.exists(PROJECT_ROOT+'/data'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data')\n\n if not os.path.exists(PROJECT_ROOT+'/data/CUB_200_2011'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/CUB_200_2011')\n\n if not os.path.exists(PROJECT_ROOT+'/data/segmentations'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/segmentations')\n\n if not os.path.exists(PROJECT_ROOT+'/data/attributes.txt'):\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/attributes.txt')","def test_count_spins_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Test for the error.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.count_spins)","def hasResidue(self, resname):\n if resname in self.map:\n return 1\n else:\n return 0","def check_model_exists(ckpt):\n expected_data = ckpt + \".data-00000-of-00001\"\n return os.path.exists(expected_data)","def check_exist(self):\n helper.RbdImageOperator._check_rbd_image(self.real_path)","def check_data(dataframe):\n if dataframe.iloc[0, 0] == 'No data available':\n return False\n else:\n return True","def exists(self):\n f = os.path.join(pth, '..', 'static/data', self.filename)\n return os.path.isfile(f)","def data(self):\n file_name = join(PARENT_BASE_DIR, '.files', 'data.data.json')\n if isfile(file_name):\n debug(f'{file_name} file is exist.')\n debug(f'try for load {file_name} file ->->->->->->->->->->')\n start_load_file = time()\n with open(file_name, 'r', encoding='utf-8')as file:\n data = file.read()\n data = loads(data)\n debug(f'load file - [runtime: {time() - start_load_file}] <-<-<-<-<-<-<-<-<-<-')\n return data, 'data exist.'\n else:\n debug(f'{file_name} file is not exist.')\n return None, 'data not exist in \"base directory/.files/data.data.json\"'","def assert_data_fragments_correct(self) -> bool:\n read_path = Path(os.environ[\"DATA_PATH\"]) / \"fragments\"\n if not read_path.exists():\n return False\n bin_images = [img for img in read_path.iterdir() if \"binarized\" in img.name]\n if len(bin_images) == 0:\n return False\n return True","def checkIfThereIsData(self, i):\n _, amountOfThings = self.weaviate.Get(\"/\" + i)\n if len(amountOfThings[i]) == 0:\n return False\n else:\n return True","def check_Data(self):\r\n \r\n if self._target_data is None:\r\n self.processData()","def has_data(self):\n if len(self.channels) > 0:\n return True\n return False","def exists(self):\n\t\tif self.hasUdim:\n\t\t\treturn len( self.udimPaths ) != 0\n\t\treturn super( textureFile, self ).exists","def has_data(self, fragment, number):\n if fragment in self.mdv:\n if number in self.mdv[fragment]:\n return True\n return False","def test_return_molecule_pipe_fail(self):\n\n # Try to get a molecule from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')","def is_empty(self):\n\n # Is the molecule structure data object empty?\n if hasattr(self, 'structure'):\n return False\n\n # Is the molecule/residue/spin data object empty?\n if not self.mol.is_empty():\n return False\n\n # Is the interatomic data object empty?\n if not self.interatomic.is_empty():\n return False\n\n # Tests for the initialised data (the pipe type can be set in an empty data pipe, so this isn't checked).\n if self.hybrid_pipes:\n return False\n\n # An object has been added to the container.\n for name in dir(self):\n # Skip the objects initialised in __init__().\n if name in ['mol', 'interatomic', 'pipe_type', 'hybrid_pipes']:\n continue\n\n # Skip the PipeContainer methods.\n if name in self.__class__.__dict__:\n continue\n\n # Skip special objects.\n if match(\"^_\", name):\n continue\n\n # An object has been added.\n return False\n\n # The data pipe is empty.\n return True","def has_datamask(self):\n return self.datamask is not None","def check_data_exist(hdir):\n cmd = 'ls ' + hdir + '*/* > ' + zspace\n os.system(cmd)\n with open(zspace, 'r') as f:\n out = f.read()\n mcf.rm_files(zspace)\n\n for name in ['dtf1', 'fov', 'bpix1', 'evt1', 'msk1', 'mtl1', 'std_dtfstat1', 'std_flt1', 'asol']:\n mc = re.search(name, out)\n if mc is None:\n line = 'Some data files are missing and the re-process is terminated. Check: ' + hdir + '\\n'\n with open(zspace, 'w') as fo:\n fo.write(line)\n\n cmd = 'cat ' + zspace + ' | mailx -s \"Subject: hrc re-process failed\" tisobe@cfa.harvard.edu'\n os.system(cmd)\n\n return False\n\n return True","def _check_notnull(self):\n candnull = self.df_test_resampled[self.candidate_col_name].isnull().all()\n refnull = self.df_test_resampled[self.reference_col_name].isnull().all()\n if candnull or refnull:\n return 1, 'No data for selected time frame'\n else:\n return 0, 'No error occurred'","def particleExists(*args, **kwargs)->bool:\n pass","def get_data_not_yet_ready_file(self):\n pass","def checkfolderdata(folder = 'datas'):\n if datafolderexist(folder):\n return True\n else:\n createdatafolder(folder)\n checkfolderdata(folder)","def exists():\n\treturn os.path.exists('data/strmr.db')","def check_path(data_pointer, log, msg):\n if not os.path.exists(data_pointer):\n log.debug(msg)\n return False\n else:\n return data_pointer","def exists(self):\n return os.path.exists(self.sensorpath)","def _exists(cursor, table, data):\n cursor.execute('SELECT 1 FROM {} WHERE ({}) = ({})'.format(table, *_query_fields(data)), data)\n return bool(cursor.fetchone())","def check_source_val_exists(self, src, pe, cycle):\n if src.location == \"PENB\":\n bus = self.architecture.component_map[pe.neighbor_bus]\n return bus.check_data_exists(cycle)\n elif src.location == \"PEGB\":\n src_pe_id = self.convert_relative_pe_id_to_absolute(src.index, pe)\n pe_id = pe.category_id\n bus = self.find_pe_global_bus(pe_id)\n print(f\"check_source_val_exists(): source PE {src_pe_id}\")\n\n # If source value has just been written by Bus, can't read it until next cycle\n print(bus.pegb_read_buffer_written)\n for i, item in enumerate(bus.pegb_read_buffer_written):\n if src_pe_id == item['src'] and pe_id == item['dst'] and src.source_id == item['id']:\n # Clear up this flag for next cycle\n #bus.pegb_read_buffer_written = []\n del bus.pegb_read_buffer_written[i]\n return False\n return bus.check_data_exists_from_pegb_read_buffer(cycle, src_pe_id, pe_id, src.source_id)\n elif src.location == \"PUNB\":\n containing_pu_id = pe.pu_id\n pu = self.architecture.component_map[containing_pu_id]\n punb_id = pu.neighbor_bus\n punb = self.architecture.component_map[punb_id]\n return punb.check_data_exists(cycle)\n elif src.location == \"PUGB\":\n return True\n elif src.location == \"ALU\":\n return True\n else:\n return True","def test_residue_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for residue in mol_res_spin.residue_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def is_data_present(self, cycle: int, bus_item: BusItem) -> bool:\n buffer = self.get_cycle_buffer(cycle)\n if self.component_subtype == \"PEGB\":\n return False\n #print(buffer)\n # for pe_id in buffer:\n # pe_buffer = buffer[pe_id]\n # # # TODO ad-hoc\n # # if isinstance(pe_buffer, deque):\n # # return False\n # #print(pe_buffer)\n #\n # pe_read_buffer = pe_buffer[\"read\"]\n # #print(pe_read_buffer)\n # for data in pe_read_buffer:\n # if data == bus_item:\n # return True\n elif self.component_subtype == \"PENB\":\n read_buffer = buffer[\"read\"]\n for entry in read_buffer:\n if entry == bus_item:\n return True\n else:\n for data in buffer:\n if data == bus_item:\n return True\n return False","def check_resource_data(self, resource):\n if pd.isna(resource).any().any():\n bad_vars = pd.isna(resource).any(axis=0)\n bad_vars = resource.columns[bad_vars].values.tolist()\n msg = ('Found NaN values for site {} in variables {}'\n .format(self.site, bad_vars))\n logger.error(msg)\n raise InputError(msg)","def check_pivot(self):\n cur = self.conn.cursor(cursor_factory=psycopg2.extras.DictCursor)\n cur.execute(\"SELECT count(*) as count FROM comuni\")\n if cur.fetchone()['count'] == 0:\n return False\n\n return True","def check_for_residue_existance(self):\n if not self.pose.total_residue():\n print \"No pose Loaded.\"\n return False\n\n if not self.current_chain.get() or not self.current_residue.get():\n print \"Chain or residue not set\"\n return False\n\n current_region = self.current_residue.get().split(\":\")\n if len(current_region)>1:\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\n\n\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\n print \"Region not found in pose\"\n return False\n else:\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\n\n print \"Residue not found in pose\"\n return False\n\n #If everythig is good then:\n return True","def get_is_data_available(self):\n return self._data_available","def test_spin_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for spin in mol_res_spin.spin_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def _check_data_point(cube, metadata):\n point_index = []\n\n for dim_length in cube.shape:\n point_index.append(int(random.random() * dim_length))\n\n point_index = tuple(point_index)\n\n try:\n point_cube = cube[point_index]\n _data_point = point_cube.data\n except Exception:\n msg = 'Unable to extract data point {} from file: {}'.format(\n point_index, metadata['basename'])\n raise FileValidationError(msg)\n else:\n return True","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.data_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.data_dir))\n if not osp.exists(self.split_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.split_dir))","def is_data_run(info, runinfo):\n this_run_in_runinfo = runinfo[\n (runinfo.fNight==info[\"night_int\"])&\n (runinfo.fRunID==info[\"run\"])\n ]\n return len(this_run_in_runinfo) > 0 and this_run_in_runinfo.iloc[0].fRunTypeKey == 1","def isUndefinedData(program: ghidra.program.model.listing.Program, addr: ghidra.program.model.address.Address) -> bool:\n ...","def available(self) -> bool:\n return (\n super().available\n and self.coordinator.data is not None\n and self.module_id in self.coordinator.data\n and self.data_id in self.coordinator.data[self.module_id]\n )","def has_data(self, time, fragment, number):\n if time in self.mdvtc.keys():\n if fragment in self.mdvtc[time].mdv.keys():\n if number in self.mdvtc[time].mdv[fragment].keys():\n return True\n return False","def exists():\n check50.include(\"data\")\n check50.exists(\"adventure.py\")\n check50.exists(\"room.py\")","def test_narrative_data_missing(self, config_handler):\n spec = Spec.from_dict(\n {\"name\": \"homogeneity_coefficient\", \"unit\": \"percentage\", \"dtype\": \"float\"}\n )\n with raises(SmifDataNotFoundError):\n config_handler.read_narrative_variant_data(\"does not exist\", spec)","def __check_array__(self):\n if self.data_array is None:\n mess = 'No data array is present, please load before attempting to create XYZ array.'\n if isinstance(self.mess_inst, MessagesGUI):\n self.mess_inst.message(mess)\n else:\n print(mess)\n return False\n else:\n return True","def f_is_empty(self):\n return self._data is None","def exists(sim):\n return (sim['N'] > 0)","def checkExistence(idMeta):\n # XXX add for diaries\n sqlq = \"\"\"\n SELECT dt\n FROM Electricity_10min\n WHERE `Meta_idMeta` = {}\n LIMIT 1;\n \"\"\".format(idMeta)\n try:\n result = mdb.getSQL(sqlq)[0]\n if (result):\n return True\n except:\n return False","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.data_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.data_dir))\n if not osp.exists(self.raw_mat_path):\n raise RuntimeError(\"'{}' is not available\".format(self.raw_mat_path))\n if not osp.exists(self.split_new_det_mat_path):\n raise RuntimeError(\"'{}' is not available\".format(self.split_new_det_mat_path))\n if not osp.exists(self.split_new_lab_mat_path):\n raise RuntimeError(\"'{}' is not available\".format(self.split_new_lab_mat_path))","def checkIfStatisticReady(self, statistic):\n\n return statistic.final_json is not None","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))","def has_cargo(self) -> bool:\n return bool(self.proto.cargo_space_taken)","def HasData(self, search_all_index = False):\n\t\tif not search_all_index:\n\t\t\treturn ExistsFile(self.__datafilename(self.__pindex))\n\t\tfor pindex in range(0, len(GV.provinces)):\n\t\t\tif ExistsFile(self.__datafilename(pindex)):\n\t\t\t\treturn True\n\t\treturn False","def _loaded_data(self):\n try:\n dsize = [int(d) for d\n in self.run('fits size', via='get').split()]\n except (ValueError, TypeError, AttributeError) as err:\n log.debug(f' FITS size error: {err}')\n return False\n else:\n if 0 in dsize:\n return False\n else:\n return True","def exists(self):\n try:\n self.world.find(self.ehandle)\n except KeyError:\n return False\n else:\n return True","def has_data(self, fit_id, species_id, start=None, stop=None):\n if not (fit_id in self.raw_results and species_id in\\\n self.raw_results[fit_id]):\n return False\n if all([isinstance(x, datetime) for x in [start, stop]]):\n ts = self.raw_results[fit_id][\"start\"]\n if not any([start < x < stop for x in ts]):\n return False\n return True","def _check_row_exists(self, pk):\n session = self.session_factory()\n exists = session.query(PipelineRun).filter_by(id=pk).first()\n session.close()\n if exists:\n return True\n return False","def data_ready(self):\n data_ready = len(self.barcode) > 0\n data_ready &= self.price > 0\n data_ready &= len(self.description) > 0\n return data_ready"],"string":"[\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def isExist(data):\\n return True/False\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_count_no_spins(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Test the number of spins counted.\\n self.assertEqual(mol_res_spin.count_spins(), 0)\",\n \"def test_molecule_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the molecules.\\n i = 0\\n for molecule in mol_res_spin.molecule_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_return_spin_pipe_fail(self):\\n\\n # Try to get a spin from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')\",\n \"def has_data(self):\\n return self._data is not None\",\n \"def is_version_data_existed(self):\\n # if exists, skip\\n # return \\n\\n return True\",\n \"def CheckForExistence(requested_data, available_data):\\n if requested_data is not None:\\n return 1 # The requested data exists.\\n elif available_data:\\n return -1 # The requested data does not exist.\\n else:\\n return 0 # No data exists at all.\",\n \"def has_data(self):\\n return len(self.data) > 0\",\n \"def has_data(self) -> bool:\\n raise NotImplementedError\",\n \"def has_data(self):\\n\\n return self._data is not None\",\n \"def has_data(self):\\n\\n return self._data is not None\",\n \"def data_available(dataset_name=None):\\r\\n for file_list in data_resources[dataset_name]['files']:\\r\\n for file in file_list:\\r\\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\\r\\n return False\\r\\n return True\",\n \"def datafolderexist(name):\\n folderpath = os.path.join(pathtofolder(), name)\\n return os.path.exists(folderpath)\",\n \"def exists(self, datadir):\\n return False\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n logging.debug('hasImageData failed: no volume node')\\n return False\\n if volumeNode.GetImageData() is None:\\n logging.debug('hasImageData failed: no image data in volume node')\\n return False\\n return True\",\n \"def is_empty(self):\\n for key, dataset in self.datasets.items():\\n try:\\n has_data = dataset.has_data()\\n except MFDataException as mfde:\\n raise MFDataException(\\n mfdata_except=mfde,\\n model=self._container_package.model_name,\\n package=self._container_package._get_pname(),\\n message=\\\"Error occurred while verifying\\\"\\n ' data of dataset \\\"{}\\\" in block '\\n '\\\"{}\\\"'.format(dataset.structure.name, self.structure.name),\\n )\\n\\n if has_data is not None and has_data:\\n return False\\n return True\",\n \"def has_data(self) -> bool:\\n return bool(self.data)\",\n \"def check_for_data():\\n if not (os.path.exists(ep.get_test_data_path()) or os.path.exists(ep.get_dbn_weight_path())):\\n return False\\n return True\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n print('no volume node')\\n return False\\n if volumeNode.GetImageData() == None:\\n print('no image data')\\n return False\\n return True\",\n \"def check_pipe_setup(pipe=None, sequence=False, j=False):\\n\\n # The data pipe.\\n if pipe == None:\\n pipe = pipes.cdp_name()\\n\\n # Get the data pipe.\\n dp = pipes.get_pipe(pipe)\\n\\n # Test if the current data pipe exists.\\n check_pipe(pipe)\\n\\n # Test if sequence data exists.\\n if sequence and not exists_mol_res_spin_data(pipe):\\n raise RelaxNoSequenceError(pipe)\\n\\n # Test if J coupling data exists.\\n if j:\\n # Search for interatomic data.\\n data = False\\n for interatom in interatomic_loop():\\n if hasattr(interatom, 'j_coupling'):\\n data = True\\n break\\n\\n # No data.\\n if not data:\\n raise RelaxNoJError()\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def _check_data_valid(self):\\n\\n is_valid = (sum(~np.isnan(self.data).flatten()) > 0 and self.data.flatten().sum() != 0)\\n if not is_valid:\\n raise FITSException(f\\\"No data in {self.survey}\\\")\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n logging.debug('no volume node')\\n return False\\n if volumeNode.GetImageData() is None:\\n logging.debug('no image data')\\n return False\\n return True\",\n \"def find_null(data, sub_reg):\\r\\n subreg_sqkm_data = data.loc[pd.IndexSlice[:, sub_reg, :], pd.IndexSlice['Sq Km']]\\r\\n if subreg_sqkm_data.isnull().values.any() == True:\\r\\n print(\\\"\\\\nSq km measurements are missing for:\\\")\\r\\n print(subreg_sqkm_data[subreg_sqkm_data.isnull()])\\r\\n else:\\r\\n print(\\\"\\\\nThere are no missing sq km values for this sub-region.\\\")\",\n \"def check_data_exist(data):\\n if data is not None:\\n if data.text is not None:\\n return True\\n return False\",\n \"def file_exists(msl_data_path, filename):\\n return os.path.isfile(msl_data_path + filename)\",\n \"def data_ready(self) -> bool:\\n data_ready = ctypes.c_uint8()\\n Utils.check(VL53L1X_C_LIBRARY.VL53L1_GetMeasurementDataReady(self.dev, byref(data_ready)))\\n return data_ready.value != 0\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n logging.debug('hasImageData failed: no volume node')\\n return False\\n if volumeNode.GetImageData() is None:\\n logging.debug('hasImageData failed: no image data in volume node')\\n return False\\n return True\",\n \"def hasImageData(self,volumeNode):\\n if not volumeNode:\\n logging.debug('hasImageData failed: no volume node')\\n return False\\n return True\",\n \"def has_data(self, *args, **kwargs):\\n return False\",\n \"def has_error(self):\\r\\n return self._arm.has_error\",\n \"def test_return_residue_pipe_fail(self):\\n\\n # Try to get a residue from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')\",\n \"def check_dataset_exists(dataset):\\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\\n return result == 0\",\n \"def datafileexist(filename):\\n filePath = os.path.join(pathtofolder(), \\\"datas\\\", filename)\\n fileFormat = '.csv'\\n return os.path.exists(f'{filePath+fileFormat}')\",\n \"def check_data_struct():\\n if not os.path.exists(PROJECT_ROOT+'/data'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data')\\n\\n if not os.path.exists(PROJECT_ROOT+'/data/CUB_200_2011'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/CUB_200_2011')\\n\\n if not os.path.exists(PROJECT_ROOT+'/data/segmentations'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/segmentations')\\n\\n if not os.path.exists(PROJECT_ROOT+'/data/attributes.txt'):\\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), PROJECT_ROOT+'/data/attributes.txt')\",\n \"def test_count_spins_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Test for the error.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.count_spins)\",\n \"def hasResidue(self, resname):\\n if resname in self.map:\\n return 1\\n else:\\n return 0\",\n \"def check_model_exists(ckpt):\\n expected_data = ckpt + \\\".data-00000-of-00001\\\"\\n return os.path.exists(expected_data)\",\n \"def check_exist(self):\\n helper.RbdImageOperator._check_rbd_image(self.real_path)\",\n \"def check_data(dataframe):\\n if dataframe.iloc[0, 0] == 'No data available':\\n return False\\n else:\\n return True\",\n \"def exists(self):\\n f = os.path.join(pth, '..', 'static/data', self.filename)\\n return os.path.isfile(f)\",\n \"def data(self):\\n file_name = join(PARENT_BASE_DIR, '.files', 'data.data.json')\\n if isfile(file_name):\\n debug(f'{file_name} file is exist.')\\n debug(f'try for load {file_name} file ->->->->->->->->->->')\\n start_load_file = time()\\n with open(file_name, 'r', encoding='utf-8')as file:\\n data = file.read()\\n data = loads(data)\\n debug(f'load file - [runtime: {time() - start_load_file}] <-<-<-<-<-<-<-<-<-<-')\\n return data, 'data exist.'\\n else:\\n debug(f'{file_name} file is not exist.')\\n return None, 'data not exist in \\\"base directory/.files/data.data.json\\\"'\",\n \"def assert_data_fragments_correct(self) -> bool:\\n read_path = Path(os.environ[\\\"DATA_PATH\\\"]) / \\\"fragments\\\"\\n if not read_path.exists():\\n return False\\n bin_images = [img for img in read_path.iterdir() if \\\"binarized\\\" in img.name]\\n if len(bin_images) == 0:\\n return False\\n return True\",\n \"def checkIfThereIsData(self, i):\\n _, amountOfThings = self.weaviate.Get(\\\"/\\\" + i)\\n if len(amountOfThings[i]) == 0:\\n return False\\n else:\\n return True\",\n \"def check_Data(self):\\r\\n \\r\\n if self._target_data is None:\\r\\n self.processData()\",\n \"def has_data(self):\\n if len(self.channels) > 0:\\n return True\\n return False\",\n \"def exists(self):\\n\\t\\tif self.hasUdim:\\n\\t\\t\\treturn len( self.udimPaths ) != 0\\n\\t\\treturn super( textureFile, self ).exists\",\n \"def has_data(self, fragment, number):\\n if fragment in self.mdv:\\n if number in self.mdv[fragment]:\\n return True\\n return False\",\n \"def test_return_molecule_pipe_fail(self):\\n\\n # Try to get a molecule from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')\",\n \"def is_empty(self):\\n\\n # Is the molecule structure data object empty?\\n if hasattr(self, 'structure'):\\n return False\\n\\n # Is the molecule/residue/spin data object empty?\\n if not self.mol.is_empty():\\n return False\\n\\n # Is the interatomic data object empty?\\n if not self.interatomic.is_empty():\\n return False\\n\\n # Tests for the initialised data (the pipe type can be set in an empty data pipe, so this isn't checked).\\n if self.hybrid_pipes:\\n return False\\n\\n # An object has been added to the container.\\n for name in dir(self):\\n # Skip the objects initialised in __init__().\\n if name in ['mol', 'interatomic', 'pipe_type', 'hybrid_pipes']:\\n continue\\n\\n # Skip the PipeContainer methods.\\n if name in self.__class__.__dict__:\\n continue\\n\\n # Skip special objects.\\n if match(\\\"^_\\\", name):\\n continue\\n\\n # An object has been added.\\n return False\\n\\n # The data pipe is empty.\\n return True\",\n \"def has_datamask(self):\\n return self.datamask is not None\",\n \"def check_data_exist(hdir):\\n cmd = 'ls ' + hdir + '*/* > ' + zspace\\n os.system(cmd)\\n with open(zspace, 'r') as f:\\n out = f.read()\\n mcf.rm_files(zspace)\\n\\n for name in ['dtf1', 'fov', 'bpix1', 'evt1', 'msk1', 'mtl1', 'std_dtfstat1', 'std_flt1', 'asol']:\\n mc = re.search(name, out)\\n if mc is None:\\n line = 'Some data files are missing and the re-process is terminated. Check: ' + hdir + '\\\\n'\\n with open(zspace, 'w') as fo:\\n fo.write(line)\\n\\n cmd = 'cat ' + zspace + ' | mailx -s \\\"Subject: hrc re-process failed\\\" tisobe@cfa.harvard.edu'\\n os.system(cmd)\\n\\n return False\\n\\n return True\",\n \"def _check_notnull(self):\\n candnull = self.df_test_resampled[self.candidate_col_name].isnull().all()\\n refnull = self.df_test_resampled[self.reference_col_name].isnull().all()\\n if candnull or refnull:\\n return 1, 'No data for selected time frame'\\n else:\\n return 0, 'No error occurred'\",\n \"def particleExists(*args, **kwargs)->bool:\\n pass\",\n \"def get_data_not_yet_ready_file(self):\\n pass\",\n \"def checkfolderdata(folder = 'datas'):\\n if datafolderexist(folder):\\n return True\\n else:\\n createdatafolder(folder)\\n checkfolderdata(folder)\",\n \"def exists():\\n\\treturn os.path.exists('data/strmr.db')\",\n \"def check_path(data_pointer, log, msg):\\n if not os.path.exists(data_pointer):\\n log.debug(msg)\\n return False\\n else:\\n return data_pointer\",\n \"def exists(self):\\n return os.path.exists(self.sensorpath)\",\n \"def _exists(cursor, table, data):\\n cursor.execute('SELECT 1 FROM {} WHERE ({}) = ({})'.format(table, *_query_fields(data)), data)\\n return bool(cursor.fetchone())\",\n \"def check_source_val_exists(self, src, pe, cycle):\\n if src.location == \\\"PENB\\\":\\n bus = self.architecture.component_map[pe.neighbor_bus]\\n return bus.check_data_exists(cycle)\\n elif src.location == \\\"PEGB\\\":\\n src_pe_id = self.convert_relative_pe_id_to_absolute(src.index, pe)\\n pe_id = pe.category_id\\n bus = self.find_pe_global_bus(pe_id)\\n print(f\\\"check_source_val_exists(): source PE {src_pe_id}\\\")\\n\\n # If source value has just been written by Bus, can't read it until next cycle\\n print(bus.pegb_read_buffer_written)\\n for i, item in enumerate(bus.pegb_read_buffer_written):\\n if src_pe_id == item['src'] and pe_id == item['dst'] and src.source_id == item['id']:\\n # Clear up this flag for next cycle\\n #bus.pegb_read_buffer_written = []\\n del bus.pegb_read_buffer_written[i]\\n return False\\n return bus.check_data_exists_from_pegb_read_buffer(cycle, src_pe_id, pe_id, src.source_id)\\n elif src.location == \\\"PUNB\\\":\\n containing_pu_id = pe.pu_id\\n pu = self.architecture.component_map[containing_pu_id]\\n punb_id = pu.neighbor_bus\\n punb = self.architecture.component_map[punb_id]\\n return punb.check_data_exists(cycle)\\n elif src.location == \\\"PUGB\\\":\\n return True\\n elif src.location == \\\"ALU\\\":\\n return True\\n else:\\n return True\",\n \"def test_residue_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for residue in mol_res_spin.residue_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def is_data_present(self, cycle: int, bus_item: BusItem) -> bool:\\n buffer = self.get_cycle_buffer(cycle)\\n if self.component_subtype == \\\"PEGB\\\":\\n return False\\n #print(buffer)\\n # for pe_id in buffer:\\n # pe_buffer = buffer[pe_id]\\n # # # TODO ad-hoc\\n # # if isinstance(pe_buffer, deque):\\n # # return False\\n # #print(pe_buffer)\\n #\\n # pe_read_buffer = pe_buffer[\\\"read\\\"]\\n # #print(pe_read_buffer)\\n # for data in pe_read_buffer:\\n # if data == bus_item:\\n # return True\\n elif self.component_subtype == \\\"PENB\\\":\\n read_buffer = buffer[\\\"read\\\"]\\n for entry in read_buffer:\\n if entry == bus_item:\\n return True\\n else:\\n for data in buffer:\\n if data == bus_item:\\n return True\\n return False\",\n \"def check_resource_data(self, resource):\\n if pd.isna(resource).any().any():\\n bad_vars = pd.isna(resource).any(axis=0)\\n bad_vars = resource.columns[bad_vars].values.tolist()\\n msg = ('Found NaN values for site {} in variables {}'\\n .format(self.site, bad_vars))\\n logger.error(msg)\\n raise InputError(msg)\",\n \"def check_pivot(self):\\n cur = self.conn.cursor(cursor_factory=psycopg2.extras.DictCursor)\\n cur.execute(\\\"SELECT count(*) as count FROM comuni\\\")\\n if cur.fetchone()['count'] == 0:\\n return False\\n\\n return True\",\n \"def check_for_residue_existance(self):\\n if not self.pose.total_residue():\\n print \\\"No pose Loaded.\\\"\\n return False\\n\\n if not self.current_chain.get() or not self.current_residue.get():\\n print \\\"Chain or residue not set\\\"\\n return False\\n\\n current_region = self.current_residue.get().split(\\\":\\\")\\n if len(current_region)>1:\\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\\n\\n\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\\n print \\\"Region not found in pose\\\"\\n return False\\n else:\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\\n\\n print \\\"Residue not found in pose\\\"\\n return False\\n\\n #If everythig is good then:\\n return True\",\n \"def get_is_data_available(self):\\n return self._data_available\",\n \"def test_spin_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for spin in mol_res_spin.spin_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def _check_data_point(cube, metadata):\\n point_index = []\\n\\n for dim_length in cube.shape:\\n point_index.append(int(random.random() * dim_length))\\n\\n point_index = tuple(point_index)\\n\\n try:\\n point_cube = cube[point_index]\\n _data_point = point_cube.data\\n except Exception:\\n msg = 'Unable to extract data point {} from file: {}'.format(\\n point_index, metadata['basename'])\\n raise FileValidationError(msg)\\n else:\\n return True\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.data_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.data_dir))\\n if not osp.exists(self.split_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.split_dir))\",\n \"def is_data_run(info, runinfo):\\n this_run_in_runinfo = runinfo[\\n (runinfo.fNight==info[\\\"night_int\\\"])&\\n (runinfo.fRunID==info[\\\"run\\\"])\\n ]\\n return len(this_run_in_runinfo) > 0 and this_run_in_runinfo.iloc[0].fRunTypeKey == 1\",\n \"def isUndefinedData(program: ghidra.program.model.listing.Program, addr: ghidra.program.model.address.Address) -> bool:\\n ...\",\n \"def available(self) -> bool:\\n return (\\n super().available\\n and self.coordinator.data is not None\\n and self.module_id in self.coordinator.data\\n and self.data_id in self.coordinator.data[self.module_id]\\n )\",\n \"def has_data(self, time, fragment, number):\\n if time in self.mdvtc.keys():\\n if fragment in self.mdvtc[time].mdv.keys():\\n if number in self.mdvtc[time].mdv[fragment].keys():\\n return True\\n return False\",\n \"def exists():\\n check50.include(\\\"data\\\")\\n check50.exists(\\\"adventure.py\\\")\\n check50.exists(\\\"room.py\\\")\",\n \"def test_narrative_data_missing(self, config_handler):\\n spec = Spec.from_dict(\\n {\\\"name\\\": \\\"homogeneity_coefficient\\\", \\\"unit\\\": \\\"percentage\\\", \\\"dtype\\\": \\\"float\\\"}\\n )\\n with raises(SmifDataNotFoundError):\\n config_handler.read_narrative_variant_data(\\\"does not exist\\\", spec)\",\n \"def __check_array__(self):\\n if self.data_array is None:\\n mess = 'No data array is present, please load before attempting to create XYZ array.'\\n if isinstance(self.mess_inst, MessagesGUI):\\n self.mess_inst.message(mess)\\n else:\\n print(mess)\\n return False\\n else:\\n return True\",\n \"def f_is_empty(self):\\n return self._data is None\",\n \"def exists(sim):\\n return (sim['N'] > 0)\",\n \"def checkExistence(idMeta):\\n # XXX add for diaries\\n sqlq = \\\"\\\"\\\"\\n SELECT dt\\n FROM Electricity_10min\\n WHERE `Meta_idMeta` = {}\\n LIMIT 1;\\n \\\"\\\"\\\".format(idMeta)\\n try:\\n result = mdb.getSQL(sqlq)[0]\\n if (result):\\n return True\\n except:\\n return False\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.data_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.data_dir))\\n if not osp.exists(self.raw_mat_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.raw_mat_path))\\n if not osp.exists(self.split_new_det_mat_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.split_new_det_mat_path))\\n if not osp.exists(self.split_new_lab_mat_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.split_new_lab_mat_path))\",\n \"def checkIfStatisticReady(self, statistic):\\n\\n return statistic.final_json is not None\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\",\n \"def has_cargo(self) -> bool:\\n return bool(self.proto.cargo_space_taken)\",\n \"def HasData(self, search_all_index = False):\\n\\t\\tif not search_all_index:\\n\\t\\t\\treturn ExistsFile(self.__datafilename(self.__pindex))\\n\\t\\tfor pindex in range(0, len(GV.provinces)):\\n\\t\\t\\tif ExistsFile(self.__datafilename(pindex)):\\n\\t\\t\\t\\treturn True\\n\\t\\treturn False\",\n \"def _loaded_data(self):\\n try:\\n dsize = [int(d) for d\\n in self.run('fits size', via='get').split()]\\n except (ValueError, TypeError, AttributeError) as err:\\n log.debug(f' FITS size error: {err}')\\n return False\\n else:\\n if 0 in dsize:\\n return False\\n else:\\n return True\",\n \"def exists(self):\\n try:\\n self.world.find(self.ehandle)\\n except KeyError:\\n return False\\n else:\\n return True\",\n \"def has_data(self, fit_id, species_id, start=None, stop=None):\\n if not (fit_id in self.raw_results and species_id in\\\\\\n self.raw_results[fit_id]):\\n return False\\n if all([isinstance(x, datetime) for x in [start, stop]]):\\n ts = self.raw_results[fit_id][\\\"start\\\"]\\n if not any([start < x < stop for x in ts]):\\n return False\\n return True\",\n \"def _check_row_exists(self, pk):\\n session = self.session_factory()\\n exists = session.query(PipelineRun).filter_by(id=pk).first()\\n session.close()\\n if exists:\\n return True\\n return False\",\n \"def data_ready(self):\\n data_ready = len(self.barcode) > 0\\n data_ready &= self.price > 0\\n data_ready &= len(self.description) > 0\\n return data_ready\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.8865291","0.8417973","0.80885214","0.80438846","0.7852497","0.7701418","0.7463378","0.65262586","0.6252962","0.59931844","0.58717984","0.5862831","0.5473991","0.54632425","0.54621637","0.5440022","0.5434693","0.5432748","0.5344402","0.5344402","0.53330797","0.53242415","0.52894723","0.5285269","0.52686435","0.5248087","0.5246962","0.5224105","0.52161855","0.5203858","0.51919776","0.5187771","0.51663655","0.5151863","0.5140558","0.5122836","0.51187575","0.5102601","0.508129","0.50738263","0.5060721","0.5057485","0.49947914","0.49859646","0.4980179","0.4957016","0.49560776","0.4951691","0.49400005","0.49383","0.49347332","0.49339086","0.49291915","0.49236134","0.49204597","0.49065876","0.49025452","0.48883042","0.48848963","0.48846272","0.48836923","0.4879927","0.48780417","0.48775622","0.48681802","0.48669055","0.48610082","0.4860316","0.48344857","0.483284","0.48037985","0.47994533","0.4795425","0.47863194","0.47811836","0.4780228","0.47800928","0.47796392","0.47748393","0.4767741","0.47665894","0.47659725","0.4759035","0.47448742","0.4740959","0.47308424","0.4729205","0.47264898","0.47256657","0.47172597","0.47162297","0.4714754","0.4714058","0.47130033","0.47062367","0.47058943","0.46980327","0.46938342","0.46876442","0.46873313"],"string":"[\n \"0.8865291\",\n \"0.8417973\",\n \"0.80885214\",\n \"0.80438846\",\n \"0.7852497\",\n \"0.7701418\",\n \"0.7463378\",\n \"0.65262586\",\n \"0.6252962\",\n \"0.59931844\",\n \"0.58717984\",\n \"0.5862831\",\n \"0.5473991\",\n \"0.54632425\",\n \"0.54621637\",\n \"0.5440022\",\n \"0.5434693\",\n \"0.5432748\",\n \"0.5344402\",\n \"0.5344402\",\n \"0.53330797\",\n \"0.53242415\",\n \"0.52894723\",\n \"0.5285269\",\n \"0.52686435\",\n \"0.5248087\",\n \"0.5246962\",\n \"0.5224105\",\n \"0.52161855\",\n \"0.5203858\",\n \"0.51919776\",\n \"0.5187771\",\n \"0.51663655\",\n \"0.5151863\",\n \"0.5140558\",\n \"0.5122836\",\n \"0.51187575\",\n \"0.5102601\",\n \"0.508129\",\n \"0.50738263\",\n \"0.5060721\",\n \"0.5057485\",\n \"0.49947914\",\n \"0.49859646\",\n \"0.4980179\",\n \"0.4957016\",\n \"0.49560776\",\n \"0.4951691\",\n \"0.49400005\",\n \"0.49383\",\n \"0.49347332\",\n \"0.49339086\",\n \"0.49291915\",\n \"0.49236134\",\n \"0.49204597\",\n \"0.49065876\",\n \"0.49025452\",\n \"0.48883042\",\n \"0.48848963\",\n \"0.48846272\",\n \"0.48836923\",\n \"0.4879927\",\n \"0.48780417\",\n \"0.48775622\",\n \"0.48681802\",\n \"0.48669055\",\n \"0.48610082\",\n \"0.4860316\",\n \"0.48344857\",\n \"0.483284\",\n \"0.48037985\",\n \"0.47994533\",\n \"0.4795425\",\n \"0.47863194\",\n \"0.47811836\",\n \"0.4780228\",\n \"0.47800928\",\n \"0.47796392\",\n \"0.47748393\",\n \"0.4767741\",\n \"0.47665894\",\n \"0.47659725\",\n \"0.4759035\",\n \"0.47448742\",\n \"0.4740959\",\n \"0.47308424\",\n \"0.4729205\",\n \"0.47264898\",\n \"0.47256657\",\n \"0.47172597\",\n \"0.47162297\",\n \"0.4714754\",\n \"0.4714058\",\n \"0.47130033\",\n \"0.47062367\",\n \"0.47058943\",\n \"0.46980327\",\n \"0.46938342\",\n \"0.46876442\",\n \"0.46873313\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7589267"},"document_rank":{"kind":"string","value":"6"}}},{"rowIdx":81482,"cells":{"query":{"kind":"string","value":"Test the format_info_full() function for all combinations of input."},"document":{"kind":"string","value":"def test_format_info_full1(self):\n\n # The spin info and expected string - covering all possible combinations.\n info = [\n # 5 bits of info.\n {'mol_name': 'Ubi', 'res_name': 'Ala', 'res_num': 10, 'spin_name': 'N', 'spin_num': 200, 'string': \"Molecule Ubi, residue Ala 10, spin N 200\"},\n\n # 4 bits of info.\n {'mol_name': None, 'res_name': 'Ala', 'res_num': 10, 'spin_name': 'N', 'spin_num': 200, 'string': \"Residue Ala 10, spin N 200\"},\n {'mol_name': 'Ubi', 'res_name': None, 'res_num': 10, 'spin_name': 'N', 'spin_num': 200, 'string': \"Molecule Ubi, residue 10, spin N 200\"},\n {'mol_name': 'Ubi', 'res_name': 'Ala', 'res_num': None, 'spin_name': 'N', 'spin_num': 200, 'string': \"Molecule Ubi, residue Ala, spin N 200\"},\n {'mol_name': 'Ubi', 'res_name': 'Ala', 'res_num': 10, 'spin_name': None, 'spin_num': 200, 'string': \"Molecule Ubi, residue Ala 10, spin 200\"},\n {'mol_name': 'Ubi', 'res_name': 'Ala', 'res_num': 10, 'spin_name': 'N', 'spin_num': None, 'string': \"Molecule Ubi, residue Ala 10, spin N\"},\n\n # 3 bits of info.\n {'mol_name': None, 'res_name': None, 'res_num': 10, 'spin_name': 'N', 'spin_num': 200, 'string': \"Residue 10, spin N 200\"},\n {'mol_name': None, 'res_name': 'Ala', 'res_num': None, 'spin_name': 'N', 'spin_num': 200, 'string': \"Residue Ala, spin N 200\"},\n {'mol_name': None, 'res_name': 'Ala', 'res_num': 10, 'spin_name': None, 'spin_num': 200, 'string': \"Residue Ala 10, spin 200\"},\n {'mol_name': None, 'res_name': 'Ala', 'res_num': 10, 'spin_name': 'N', 'spin_num': None, 'string': \"Residue Ala 10, spin N\"},\n {'mol_name': 'Ubi', 'res_name': None, 'res_num': None, 'spin_name': 'N', 'spin_num': 200, 'string': \"Molecule Ubi, spin N 200\"},\n {'mol_name': 'Ubi', 'res_name': None, 'res_num': 10, 'spin_name': None, 'spin_num': 200, 'string': \"Molecule Ubi, residue 10, spin 200\"},\n {'mol_name': 'Ubi', 'res_name': None, 'res_num': 10, 'spin_name': 'N', 'spin_num': None, 'string': \"Molecule Ubi, residue 10, spin N\"},\n {'mol_name': 'Ubi', 'res_name': 'Ala', 'res_num': None, 'spin_name': None, 'spin_num': 200, 'string': \"Molecule Ubi, residue Ala, spin 200\"},\n {'mol_name': 'Ubi', 'res_name': 'Ala', 'res_num': None, 'spin_name': 'N', 'spin_num': None, 'string': \"Molecule Ubi, residue Ala, spin N\"},\n {'mol_name': 'Ubi', 'res_name': 'Ala', 'res_num': 10, 'spin_name': None, 'spin_num': None, 'string': \"Molecule Ubi, residue Ala 10\"},\n\n # 2 bits of info.\n {'mol_name': None, 'res_name': None, 'res_num': None, 'spin_name': 'N', 'spin_num': 200, 'string': \"Spin N 200\"},\n {'mol_name': None, 'res_name': None, 'res_num': 10, 'spin_name': None, 'spin_num': 200, 'string': \"Residue 10, spin 200\"},\n {'mol_name': None, 'res_name': None, 'res_num': 10, 'spin_name': 'N', 'spin_num': None, 'string': \"Residue 10, spin N\"},\n {'mol_name': None, 'res_name': 'Ala', 'res_num': None, 'spin_name': None, 'spin_num': 200, 'string': \"Residue Ala, spin 200\"},\n {'mol_name': None, 'res_name': 'Ala', 'res_num': None, 'spin_name': 'N', 'spin_num': None, 'string': \"Residue Ala, spin N\"},\n {'mol_name': None, 'res_name': 'Ala', 'res_num': 10, 'spin_name': None, 'spin_num': None, 'string': \"Residue Ala 10\"},\n {'mol_name': 'Ubi', 'res_name': None, 'res_num': None, 'spin_name': None, 'spin_num': 200, 'string': \"Molecule Ubi, spin 200\"},\n {'mol_name': 'Ubi', 'res_name': None, 'res_num': None, 'spin_name': 'N', 'spin_num': None, 'string': \"Molecule Ubi, spin N\"},\n {'mol_name': 'Ubi', 'res_name': None, 'res_num': 10, 'spin_name': None, 'spin_num': None, 'string': \"Molecule Ubi, residue 10\"},\n {'mol_name': 'Ubi', 'res_name': 'Ala', 'res_num': None, 'spin_name': None, 'spin_num': None, 'string': \"Molecule Ubi, residue Ala\"},\n\n # 1 bit of info.\n {'mol_name': None, 'res_name': None, 'res_num': None, 'spin_name': None, 'spin_num': 200, 'string': \"Spin 200\"},\n {'mol_name': None, 'res_name': None, 'res_num': None, 'spin_name': 'N', 'spin_num': None, 'string': \"Spin N\"},\n {'mol_name': None, 'res_name': None, 'res_num': 10, 'spin_name': None, 'spin_num': None, 'string': \"Residue 10\"},\n {'mol_name': None, 'res_name': 'Ala', 'res_num': None, 'spin_name': None, 'spin_num': None, 'string': \"Residue Ala\"},\n {'mol_name': 'Ubi', 'res_name': None, 'res_num': None, 'spin_name': None, 'spin_num': None, 'string': \"Molecule Ubi\"},\n\n # 0 bits of info.\n {'mol_name': None, 'res_name': None, 'res_num': None, 'spin_name': None, 'spin_num': None, 'string': \"\"},\n ]\n\n # Printout.\n print(\"Checking %s combinations.\" % len(info))\n\n # Create and check each string.\n for i in range(len(info)):\n print(\" Checking %s\" % info[i])\n string = mol_res_spin.format_info_full(mol_name=info[i]['mol_name'], res_name=info[i]['res_name'], res_num=info[i]['res_num'], spin_name=info[i]['spin_name'], spin_num=info[i]['spin_num'])\n self.assertEqual(string, info[i]['string'])"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_format_correlation_info(self):\r\n # With 999 permutations.\r\n exp = 'Correlation coefficient\\tParametric p-value\\tNonparametric ' + \\\r\n 'p-value\\tCI (lower)\\tCI (upper)\\n0.7778\\t0.0000\\t' + \\\r\n '0.000\\t0.0000\\t1.0000\\n'\r\n obs = format_correlation_info(0.7778, 0, 0, (0, 1), 999)\r\n self.assertEqual(obs, exp)\r\n\r\n # With 0 permutations.\r\n exp = 'Correlation coefficient\\tParametric p-value\\tNonparametric ' + \\\r\n 'p-value\\tCI (lower)\\tCI (upper)\\n0.7778\\t0.0000\\t' + \\\r\n 'N/A\\t0.0000\\t1.0000\\n'\r\n obs = format_correlation_info(0.7778, 0, 0, (0, 1), 0)\r\n self.assertEqual(obs, exp)\r\n\r\n # With a small number of permutations.\r\n exp = 'Correlation coefficient\\tParametric p-value\\tNonparametric ' + \\\r\n 'p-value\\tCI (lower)\\tCI (upper)\\n0.7778\\t0.0000\\t' + \\\r\n 'Too few iters to compute p-value (num_iters=1)\\t' + \\\r\n '0.0000\\t1.0000\\n'\r\n obs = format_correlation_info(0.7778, 0, 0, (0, 1), 1)\r\n self.assertEqual(obs, exp)\r\n\r\n # With undefined confidence interval.\r\n exp = 'Correlation coefficient\\tParametric p-value\\tNonparametric ' + \\\r\n 'p-value\\tCI (lower)\\tCI (upper)\\n0.7778\\t0.0000\\t' + \\\r\n 'N/A\\tN/A\\tN/A\\n'\r\n obs = format_correlation_info(0.7778, 0, 0, (None, None), 0)\r\n self.assertEqual(obs, exp)","def test_is_entry_formatted(self):\n\n valid_formats = test_case_data.get('valid_formats')\n for i, valid_entry in enumerate(test_case_data.get('valid_entries')):\n entry = [value.strip() for value in valid_entry.split(',')]\n format_fields = valid_formats[i].split(',')\n valid = self.parser._is_entry_formatted(entry, format_fields)\n self.assertTrue(valid, f'{entry} is not of a valid format')\n\n # fails with invalid entries\n for invalid_entry in test_case_data.get('invalid_entries'):\n entry = [value.strip() for value in invalid_entry.split(',')]\n for f in valid_formats:\n format_fields = f.split(',')\n entry_dict = self.parser._is_entry_formatted(entry, format_fields)\n self.assertFalse(entry_dict, f'{entry} is not of a valid format')","def PrintDetailedE(GaussE, TinkE, sumE, result_format):\n ## Force to lowercase for search\n result_format = [each_form.lower() for each_form in result_format]\n if 'all' in result_format:\n print(\"\\n\")\n print(f\"Gaussian Energy (au): {GaussE/har2ev:.10f} +\")\n print(f\"Tinker Energy (au): {TinkE/har2ev:.10f}\")\n print(\"===========================================\")\n print(f\"QM/MM Energy (au): {sumE/har2ev:.10f}\\n\")\n print(\"\\n\")\n print(f\"Gaussian Energy (kcal/mol): {GaussE/kcal2ev:.10f} +\")\n print(f\"Tinker Energy (kcal/mol): {TinkE/kcal2ev:.10f}\")\n print(\"====================================================\")\n print(f\"QM/MM Energy (kcal/mol): {sumE/kcal2ev:.10f}\\n\")\n print(\"\\n\")\n print(f\"Gaussian Energy (eV): {GaussE:.10f} +\")\n print(f\"Tinker Energy (eV): {TinkE:.10f}\")\n print(\"============================================\")\n print(f\"QM/MM Energy (eV): {sumE:.10f}\\n\")\n else:\n one_printed = False\n print(\"\")\n for form in result_format:\n if form.lower() == 'au':\n print(f\"Gaussian Energy (au): {GaussE/har2ev:.10f} +\")\n print(f\"Tinker Energy (au): {TinkE/har2ev:.10f}\")\n print(\"==========================================\")\n print(f\"QM/MM Energy (au): {sumE/har2ev:.10f}\\n\")\n one_printed = True\n elif form.lower() in ('hartree', 'hartrees', 'hartree(s)'):\n print(f\"Gaussian Energy (Hartrees): {GaussE/har2ev:.10f} +\")\n print(f\"Tinker Energy (Hartrees): {TinkE/har2ev:.10f}\")\n print(\"================================================\")\n print(f\"QM/MM Energy (Hartrees): {sumE/har2ev:.10f}\\n\")\n one_printed = True\n elif form.lower() in ('kcal', 'kcal/mol'):\n print(f\"Gaussian Energy (kcal/mol): {GaussE/kcal2ev:.10f} +\")\n print(f\"Tinker Energy (kcal/mol): {TinkE/kcal2ev:.10f}\")\n print(\"====================================================\")\n print(f\"QM/MM Energy (kcal/mol): {sumE/kcal2ev:.10f}\\n\")\n one_printed = True\n elif form.lower() == 'ev':\n print(f\"Gaussian Energy (eV): {GaussE:.10f} +\")\n print(f\"Tinker Energy (eV): {TinkE:.10f}\")\n print(\"============================================\")\n print(f\"QM/MM Energy (eV): {sumE:.10f}\\n\")\n one_printed = True\n else:\n if one_printed == True:\n print(f\"I can't parse your requested result_format, '{form}'.\")\n print(\"I only accept a list of values, such as:\")\n print(\" 'au', 'hartrees', 'ev', 'kcal', 'all'\")\n else:\n print(f\"I can't parse your requested result_format, '{form}'.\")\n print(\"I only accept a list of values, such as:\")\n print(\" 'au', 'hartrees', 'ev', 'kcal', 'all'\")\n print(\"Printing au instead...\\n\")\n print(f\"Gaussian Energy (au): {GaussE/har2ev:.10f} +\")\n print(f\"Tinker Energy (au): {TinkE/har2ev:.10f}\")\n print(\"============================================\")\n print(f\"QM/MM Energy (au): {sumE/har2ev:.10f}\\n\")","def helper():\n for mode in PackingMode:\n for bin_algo in PackingBin:\n for size, w, h in ('big_enough', 50, 50), ('too_small', 5, 5):\n name = '_'.join(('test', mode, bin_algo, size))\n print(\"\"\"\\\n def %s(self):\n # create bins that are %s to hold the rectangles\n p = self._common(PackingMode.%s, PackingBin.%s, %s, %s)\"\"\" %\n (name, size.replace('_', ' '), mode, bin_algo, w, h))\n if size == 'big_enough':\n print(\"\"\"\\\n # check that bins were created\n self.assertGreater(len(p.bin_list()), 0)\n # check that all of the rectangles made it in\n self.assertEqual(len(p.rect_list()), len(self.rectangles))\n\"\"\")\n else:\n print(\"\"\"\\\n # check that none of the rectangles made it in\n self.assertEqual(len(p.rect_list()), 0)\n\"\"\")","def test_buoy_format1():\n with pytest.raises(AssertionError) as err_info:\n Check_BuoyDC.check_buoy_format(buoy_format_fail_1)\n assert str(err_info.value) == 'Input formatted incorrectly, see instructions'","def test_enforce_iterable():\n formatter = TabularOutputFormatter()\n loremipsum = (\n \"lorem ipsum dolor sit amet consectetur adipiscing elit sed do eiusmod\".split(\n \" \"\n )\n )\n\n for format_name in formatter.supported_formats:\n formatter.format_name = format_name\n try:\n formatted = next(formatter.format_output(zip(loremipsum), [\"lorem\"]))\n except TypeError:\n assert False, \"{0} doesn't return iterable\".format(format_name)","def test_match_entry_to_format(self):\n\n # matches valid entries with valid formats\n for valid_entry in test_case_data.get('valid_entries'):\n entry = [e.strip() for e in valid_entry.split(',')]\n entry_dict = self.parser._match_entry_to_format(entry)\n\n self.assertTrue(entry_dict, f'{entry} is not of a valid format')\n\n # fails with invalid entries\n for invalid_entry in test_case_data.get('invalid_entries'):\n entry = [e.strip() for e in invalid_entry.split(',')]\n entry_dict = self.parser._match_entry_to_format(entry)\n\n self.assertFalse(entry_dict, f'{entry} is not of a valid format')","def checkMTSinfoCompliance(info):\n if len(info) != 3:\n print(\"MTS INFO DOES NOT ADHERE TO MY STANDARD: processingUnit_machine_order\")\n exit(5)","def test_build_format_map(all_sets: dict, expected: dict) -> None:\n result = build_format_map(all_sets, regular=False)\n assert result == expected","def test_reponse_format(y):\r\n print(\"test_response_format()...\", end = \"\")\r\n for item in y:\r\n assert (item == 0 or item == 1)\r\n print(\"Passed!\")","def test_buoy_format2():\n with pytest.raises(AssertionError) as err_info:\n Check_BuoyDC.check_buoy_format(buoy_format_fail_2)\n assert str(err_info.value) == 'Input length incorrect, see instructions'","def get_format_opts(cls, format_=\"value\", fields=[]):\n return \" -f {0} {1}\".format(format_, \" \".join([\"-c \" + it for it in fields]))","def handle_short_info(files, directories, args):\n result_info = []\n # Define the width of columns\n max_length = 0\n if directories:\n max_length = max(max(len(item) for item in directories[d])\n for d in directories)\n if files:\n max_length = max(max_length, max(len(item) for item in files))\n col_width = max_length + 1\n terminal_width = shutil.get_terminal_size().columns\n if args.format == 'single-column' or args.one:\n columns = 1\n else:\n columns = terminal_width // (max_length + 1) or 1\n\n if not files and len(directories) == 1:\n d = list(directories.keys())[0]\n result_info.extend(handle_files_group(directories[d],\n columns, col_width, args))\n log.debug(result_info)\n return result_info\n\n if files:\n result_info.extend(handle_files_group(files, columns, col_width, args))\n for d in directories:\n result_info.append(f'{d}:')\n result_info.extend(handle_files_group(directories[d],\n columns, col_width, args))\n log.debug(result_info)\n return result_info","def format_info(self, *args):\n if self._pretty:\n return self.format_multiline_message(*args, color='cyan', start='[INFO] ', multiline=' ~~ ')\n return self.format_multiline_message(*args)","def test_feature_format(X):\r\n print(\"test_feature_format()...\", end = \"\")\r\n for row in range(len(X)):\r\n for col in range(len(X[0])):\r\n assert (isinstance(X[row][col], float) == True)\r\n print(\"Passed!\")","def test_supported_formats_interpolations(self):\n params_82 = {\n 'ReQuEsT': \"DescribeCoverage\",\n 'SeRvIcE': \"WCS\",\n \"BOGUS\": \"SSS\",\n 'Version': \"1.0.0\",\n \"COVERAGE\": self.names[0]\n }\n response = self.query_server(params_82)\n soup = BeautifulSoup(response.text, 'xml')\n formats = list(map(lambda f: f.text, soup.find_all('formats')))\n self.assertTrue(\n len(set([\"GeoTIFF\", \"HDF-EOS\", \"DTED\", \"NITF\", \"GML\"]).intersection(formats)) > 0,\n msg=\"The first format returned in a coverage description should be one of the five defined in the spec.\")\n interpolations = list(map(lambda f: f.text, soup.find_all('interpolationMethod')))\n self.assertTrue(\n len(\n set([\"nearest neighbor\", \"bilinear\", \"bicubic\", \"lost area\", \"barycentric\"]).intersection(\n interpolations)) > 0,\n msg=\"Supported interpolations must be one of the five defined in the spec.\")","def test_tabular_format_output_wrapper():\n data = [[\"1\", None], [\"2\", \"Sam\"], [\"3\", \"Joe\"]]\n headers = [\"id\", \"name\"]\n expected = dedent(\n \"\"\"\\\n +----+------+\n | id | name |\n +----+------+\n | 1 | N/A |\n | 2 | Sam |\n | 3 | Joe |\n +----+------+\"\"\"\n )\n\n assert expected == \"\\n\".join(\n format_output(iter(data), headers, format_name=\"ascii\", missing_value=\"N/A\")\n )","def test_nothing_fits():\n freetimes, _ = free([], 9, 0, 17, 0, day_range, 600)\n fmt_freetime = output_format(freetimes)\n for i in fmt_freetime:\n print(i)\n assert fmt_freetime == []","def testFormatLabelAndValue(self):\n\n self.assertEqual('Abc: xyz', self.inv._FormatLabelAndValue('abc', 'xyz', 1))\n self.assertEqual('ABc: xyz', self.inv._FormatLabelAndValue('abc', 'xyz', 2))\n self.assertEqual('ABC: xyz', self.inv._FormatLabelAndValue('abc', 'xyz', 4))","def _info(self, N):\n IDs = self.chemicals.IDs\n data = self.data\n IDs, data = nonzeros(IDs, data)\n N_IDs = len(IDs)\n if N_IDs == 0:\n return f\"{type(self).__name__}: (all zeros)\"\n else:\n basic_info = f\"{type(self).__name__}:\\n\"\n new_line = '\\n'\n data_info = ''\n lengths = [len(i) for i in IDs]\n maxlen = max(lengths) + 1\n N_max = N or tmo.Stream.display_units.N\n too_many_chemicals = N_IDs > N_max\n N = N_max if too_many_chemicals else N_IDs\n for i in range(N):\n spaces = ' ' * (maxlen - lengths[i])\n if i != 0:\n data_info += new_line\n data_info += IDs[i] + spaces + f' {data[i]:.3g}'\n if too_many_chemicals:\n data_info += new_line + '...'\n return (basic_info\n + data_info)","def test_format_best_results(self):\r\n # Single category.\r\n exp = ('Method name\\tNumber of categories\\tCategories\\t'\r\n 'rho statistics\\nBEST\\t1\\tDOB = 1\\t(-0.001, \\'1\\')\\n')\r\n obs = format_best_results({'method_name': 'BEST', 'num_vars': 1,\r\n 'vars': ['DOB = 1'],\r\n 'rho_vals': [(-0.0010, '1')]})\r\n self.assertEqual(obs, exp)\r\n\r\n # Multiple categories.\r\n exp = ('Method name\\tNumber of categories\\tCategories\\t'\r\n 'rho statistics\\nBEST\\t2\\tDOB = 1, pH = 2\\t(-0.001, \\'1\\'), '\r\n '(0.99909, \\'1,2\\')\\n')\r\n obs = format_best_results({'method_name': 'BEST', 'num_vars': 2,\r\n 'vars': ['DOB = 1', 'pH = 2'],\r\n 'rho_vals': [(-0.0010, '1'),\r\n (0.99909, '1,2')]})\r\n self.assertEqual(obs, exp)","def test_nested_format_fields():\n '{0:>{1}}'.format(42, 24)\n '{0:{a[1]}} {a}'.format(1, a=[1, 2])\n '{:>{}}'.format(42, 24)\n '{0:>{1}}'.format(42)\n '{0:>{1}}'.format(42, 24, 54)\n ##Warn: W1303\n '{0:{a[1]}}'.format(1)\n ##Warn: W1306\n '{0:{a.x}}'.format(1, a=2)","def fp_config_formatting(info):\n # From: OpenCL/AMDAPPSDK-3.0/include/CL/cl.h\n options = [((1 << 0), 'CL_FP_DENORM'),\n ((1 << 1), 'CL_FP_INF_NAN'),\n ((1 << 2), 'CL_FP_ROUND_TO_NEAREST'),\n ((1 << 3), 'CL_FP_ROUND_TO_ZERO'),\n ((1 << 4), 'CL_FP_ROUND_TO_INF'),\n ((1 << 5), 'CL_FP_FMA'),\n ((1 << 6), 'CL_FP_SOFT_FLOAT'),\n ((1 << 7), 'CL_FP_CORRECTLY_ROUNDED_DIVIDE_SQRT')]\n # The initial line shows the bitmap, following lines\n # explicitly show the meaning and availability.\n option_breakdown = [bin(info)]\n for bitfield, option in options:\n is_available = bool(bitfield & info)\n option_breakdown.append('{}={}'.format(option, is_available))\n return ('\\n\\t'+' '*(device_maxwidth+3)).join(option_breakdown)","def test_format_info():\n data = grp.struct_group((\"wheel\", \"*\", 0, [\"root\"]))\n ret = {\"passwd\": \"*\", \"gid\": 0, \"name\": \"wheel\", \"members\": [\"root\"]}\n assert mac_group._format_info(data) == ret","def test_printdiff(self):\n\n # Testing different string input options\n assert printdiff(self.data(\"arange.fits\"), self.data(\"blank.fits\")) is None\n assert (\n printdiff(self.data(\"arange.fits\"), self.data(\"blank.fits\"), ext=0) is None\n )\n assert (\n printdiff(\n self.data(\"o4sp040b0_raw.fits\"),\n self.data(\"o4sp040b0_raw.fits\"),\n extname=\"sci\",\n )\n is None\n )\n\n # This may seem weird, but check printdiff to see, need to test\n # incorrect second file\n with pytest.raises(OSError):\n printdiff(\"o4sp040b0_raw.fits\", \"fakefile.fits\", extname=\"sci\")\n\n # Test HDU object inputs\n with fits.open(self.data(\"stddata.fits\"), mode=\"readonly\") as in1:\n with fits.open(self.data(\"checksum.fits\"), mode=\"readonly\") as in2:\n assert printdiff(in1[0], in2[0]) is None\n\n with pytest.raises(ValueError):\n printdiff(in1[0], in2[0], ext=0)\n\n assert printdiff(in1, in2) is None\n\n with pytest.raises(NotImplementedError):\n printdiff(in1, in2, 0)","def test_printdiff(self):\n\n # Testing different string input options\n assert printdiff(self.data('arange.fits'),\n self.data('blank.fits')) is None\n assert printdiff(self.data('arange.fits'),\n self.data('blank.fits'), ext=0) is None\n assert printdiff(self.data('o4sp040b0_raw.fits'),\n self.data('o4sp040b0_raw.fits'),\n extname='sci') is None\n\n # This may seem weird, but check printdiff to see, need to test\n # incorrect second file\n with pytest.raises(IOError):\n printdiff('o4sp040b0_raw.fits', 'fakefile.fits', extname='sci')\n\n # Test HDU object inputs\n with fits.open(self.data('stddata.fits'), mode='readonly') as in1:\n with fits.open(self.data('checksum.fits'), mode='readonly') as in2:\n\n assert printdiff(in1[0], in2[0]) is None\n\n with pytest.raises(ValueError):\n printdiff(in1[0], in2[0], ext=0)\n\n assert printdiff(in1, in2) is None\n\n with pytest.raises(NotImplementedError):\n printdiff(in1, in2, 0)","def test_sequence_info(self):\n self.t(\"1,2 info\")\n code, out, err = self.t(\"_get 1.description 2.description\")\n self.assertEqual(out.count(\"miss\"), 2)","def handle_full_info(files, directories, args):\n result_info = []\n if not files and len(directories) == 1:\n d = list(directories.keys())[0]\n result_info.extend(full_info(directories[d], args, d))\n log.debug(result_info)\n return result_info\n\n if files:\n result_info.extend(full_info(files, args))\n for d in directories:\n result_info.append(f'{d}:')\n result_info.extend(full_info(directories[d], args, d))\n log.debug(result_info)\n return result_info","def _test_parts(self):\n\n message = []\n\n if self._year is None:\n message.append(\"No year\")\n else:\n try:\n int(self._year)\n except:\n message.append(\"Bad year {}\".format(self._year))\n\n if not self._release:\n message.append(\"No release\")\n else:\n try:\n assert (int(self._release) in [1, 5])\n except:\n message.append(\"Bad release {}\".format(self._release))\n\n if not self._state:\n message.append(\"No state\")\n elif len(self._state) != 2:\n message.append(\"Bad state {}\".format(self._state))\n\n if not self._record_type:\n message.append(\"No record_type\")\n else:\n try:\n assert(self._record_type.upper()[0] in ['H','P'])\n except:\n message.append(\"Bad record type {}\".format(self._record_type))\n\n return message","def _test_output_formatting_func(self, sample: Any):\n try:\n if not type(sample) == iter:\n self._formatting_func_return_types(format=sample)\n return True\n except Exception:\n raise ValueError(\n f\"formatting_func must return {self._formatting_func_return_types.__annotations__['format']}, not {type(sample)}\"\n )","def test_input_conversion(self):\n data = [dict(A=0.1, C=0.2), dict(A=0.1, C=0.2)]\n base = [(\"A\", 0.1), (\"C\", 0.2)]\n expect = [base, base]\n got = _char_hts_as_lists(data)\n self.assertEqual(got, expect)\n #\n data = [dict(A=0.1, C=0.2), {}]\n base = [(\"A\", 0.1), (\"C\", 0.2)]\n expect = [base, None]\n got = _char_hts_as_lists(data)\n self.assertEqual(got, expect)\n data = [dict(A=0.1, C=0.2), None]\n base = [(\"A\", 0.1), (\"C\", 0.2)]\n expect = [base, None]\n got = _char_hts_as_lists(data)\n self.assertEqual(got, expect)","def print_pairing_info(melon_types):\n\n # Fill in the rest","def test_plain_flat_json(\n before_json_flat: str,\n after_json_flat: str,\n plain_flat_res: str,\n):\n assert gendiff(\n before_json_flat,\n after_json_flat,\n form=PLAIN_FORMAT,\n ) == plain_flat_res","def test_available_output_formats():\n assert set([\"GTiff\", \"PNG\", \"PNG_hillshade\", \"GeoJSON\"]).issubset(\n set(available_output_formats())\n )","def test_print_formatter():\n tuple_1 = (\"test\", \"me\", 1.22, 1.42)\n tuple_2 = (\"test2\", 4.20, 1.2)\n tuple_3 = (1.2, \"test3\", 4.20)\n assert print_formatter(tuple_1) == (\"me\", '1.22', '1.42')\n with pytest.raises(IndexError):\n print_formatter(tuple_2)\n print_formatter(tuple_3)","def individual_info(self, ctx: commands.Context, format: str) -> str:\n\t\tformat = self.__normalize(ctx, format)\n\t\ttip = self.formats[format]\n\t\theader_text = self.__header(format, tip)\n\t\thow_to = blockquote(tip.escaped)\n\t\tfooter_text = self.__footer(format)\n\t\treturn f\"{header_text}\\n\\n{how_to}\\n\\n{footer_text}\"","def iter_format(nitems, testobj='ndarray'):\n for t in iter_mode(nitems, testobj):\n yield t\n if testobj != 'ndarray':\n return\n yield struct_items(nitems, testobj)","def iter_format(nitems, testobj='ndarray'):\n for t in iter_mode(nitems, testobj):\n yield t\n if testobj != 'ndarray':\n return\n yield struct_items(nitems, testobj)","def test_basic(self):\r\n self.validate((3, 2, 8, 8), (4, 2, 5, 5), 'valid', verify_grad=False)\r\n self.validate((3, 2, 7, 5), (5, 2, 2, 3), 'valid')\r\n self.validate((3, 2, 7, 5), (5, 2, 3, 2), 'valid', verify_grad=False)\r\n self.validate((3, 2, 8, 8), (4, 2, 5, 5), 'full', verify_grad=False)\r\n self.validate((3, 2, 7, 5), (5, 2, 2, 3), 'full')\r\n # test filter same size as input\r","def test_duplicate_manual_position_arguments():\n '{0} {1} {0}'.format(1, 2)\n '{0} {1} {0}'.format(1)","def data_format(self):\n # Run without arguments\n if len(sys.argv) == 1:\n sys.exit(usage(None))\n # Test input file argument\n if self.input and not os.path.isfile(self.input):\n print(self.input)\n print(os.path.isfile(self.input))","def info(capsys, format_str, format_args=None):\n\n if format_args is not None:\n msg = (format_str % format_args)\n else:\n msg = format_str\n\n with capsys.disabled():\n print(msg)","def test_function_output(self):\n \n for integer, stringValue in self.knownIfPrime: # Check each tuple in knownIfPrime\n result = fizzbuzz_correct.fizzbuzz(integer)\n \n self.assertEquals(stringValue, result, \"This doesn't seem to work with %d\" % (integer))","def check_all(self, output_information=True):\r\n self.check_balance(output_information)\r\n self.check_color(output_information)","def test_format_taxa_summary(self):\r\n # More than one sample.\r\n taxa_summary = (['Even7', 'Even8'], ['Eukarya'], array([[1.0, 1.0]]))\r\n exp = 'Taxon\\tEven7\\tEven8\\nEukarya\\t1.0\\t1.0\\n'\r\n obs = format_taxa_summary(taxa_summary)\r\n self.assertEqual(obs, exp)\r\n\r\n # More than one taxon.\r\n taxa_summary = (['Expected'], ['Eukarya', 'Bacteria', 'Archaea'],\r\n array([[0.5], [0.6], [0.4]]))\r\n exp = 'Taxon\\tExpected\\nEukarya\\t0.5\\nBacteria\\t0.6\\nArchaea\\t0.4\\n'\r\n obs = format_taxa_summary(taxa_summary)\r\n self.assertEqual(obs, exp)","def test_print_info(clarisse):\n info = \"test print info\"\n assert bool(clarisse.print_info(info)) is False","def _info(self, N):\n IDs = self.chemicals.IDs\n data = self.data\n IDs, data = nonzeros(IDs, data)\n N_IDs = len(IDs)\n if N_IDs == 0:\n return f\"{type(self).__name__}: (empty)\"\n elif self.units:\n basic_info = f\"{type(self).__name__} ({self.units}):\\n\"\n else:\n basic_info = f\"{type(self).__name__}:\\n\"\n beginning = f'({self.phase}) ' if self.phase else \" \"\n new_line = '\\n' + len(beginning) * ' '\n data_info = ''\n lengths = [len(i) for i in IDs]\n maxlen = max(lengths) + 1\n N_max = N or tmo.Stream.display_units.N\n too_many_chemicals = N_IDs > N_max\n N = N_max if too_many_chemicals else N_IDs\n for i in range(N):\n spaces = ' ' * (maxlen - lengths[i])\n if i != 0:\n data_info += new_line\n data_info += IDs[i] + spaces + f' {data[i]:.3g}'\n if too_many_chemicals:\n data_info += new_line + '...'\n return (basic_info\n + beginning\n + data_info)","def test_format_throughput_for_two_inputs(self):\n actual = format_throughput(20, 10)\n self.assertEqual(actual, \"10/20 (50%)\")","async def test_expanded_user_infraction_counts_returns_correct_strings(self):\n test_values = (\n {\n \"api response\": [],\n \"expected_lines\": [\"No infractions\"],\n },\n # Shows non-hidden inactive infraction as expected\n {\n \"api response\": [{\"type\": \"kick\", \"active\": False, \"hidden\": False}],\n \"expected_lines\": [\"Kicks: 1\"],\n },\n # Shows non-hidden active infraction as expected\n {\n \"api response\": [{\"type\": \"mute\", \"active\": True, \"hidden\": False}],\n \"expected_lines\": [\"Mutes: 1 (1 active)\"],\n },\n # Shows hidden inactive infraction as expected\n {\n \"api response\": [{\"type\": \"superstar\", \"active\": False, \"hidden\": True}],\n \"expected_lines\": [\"Superstars: 1\"],\n },\n # Shows hidden active infraction as expected\n {\n \"api response\": [{\"type\": \"ban\", \"active\": True, \"hidden\": True}],\n \"expected_lines\": [\"Bans: 1 (1 active)\"],\n },\n # Correctly displays tally of multiple infractions of mixed properties in alphabetical order\n {\n \"api response\": [\n {\"type\": \"kick\", \"active\": False, \"hidden\": True},\n {\"type\": \"ban\", \"active\": True, \"hidden\": True},\n {\"type\": \"superstar\", \"active\": True, \"hidden\": True},\n {\"type\": \"mute\", \"active\": True, \"hidden\": True},\n {\"type\": \"ban\", \"active\": False, \"hidden\": False},\n {\"type\": \"note\", \"active\": False, \"hidden\": True},\n {\"type\": \"note\", \"active\": False, \"hidden\": True},\n {\"type\": \"warn\", \"active\": False, \"hidden\": False},\n {\"type\": \"note\", \"active\": False, \"hidden\": True},\n ],\n \"expected_lines\": [\n \"Bans: 2 (1 active)\",\n \"Kicks: 1\",\n \"Mutes: 1 (1 active)\",\n \"Notes: 3\",\n \"Superstars: 1 (1 active)\",\n \"Warns: 1\",\n ],\n },\n )\n\n header = \"Infractions\"\n\n await self._method_subtests(self.cog.expanded_user_infraction_counts, test_values, header)","def test_headless_tabulate_format():\n formatter = TabularOutputFormatter(format_name=\"minimal\")\n headers = [\"text\", \"numeric\"]\n data = [[\"a\"], [\"b\"], [\"c\"]]\n expected = \"a\\nb\\nc\"\n assert expected == \"\\n\".join(\n TabularOutputFormatter().format_output(\n iter(data),\n headers,\n format_name=\"minimal\",\n )\n )","def print_full(self):# pragma: no cover\n print('Will now print all optional output arrays - ')\n print(' yint_seg: ')\n print((self.yint_seg))\n print(' ')\n print(' slope_seg: ')\n print(self.slope_seg)\n print(' ')\n print(' sigyint_seg: ')\n print(self.sigyint_seg)\n print(' ')\n print(' sigslope_seg: ')\n print(self.sigslope_seg)\n print(' ')\n print(' inv_var_2d: ')\n print((self.inv_var_2d))\n print(' ')\n print(' firstf_int: ')\n print((self.firstf_int))\n print(' ')\n print(' ped_int: ')\n print((self.ped_int))\n print(' ')\n print(' cr_mag_seg: ')\n print((self.cr_mag_seg))","def complete_opt_format(self, text, *_):\n return [t + \" \" for t in FORMATTERS if t.startswith(text)]","def test_formatResult(self):\r\n x = self.FWP({'x': 3})\r\n self.assertEqual(x.formatResult(3), '3')","def test_basics(key_formats, template, expected, fields, errors):\n\n format_product = FormatTemplate(key_formats=key_formats)\n statement = partial(format_product, template, **fields)\n\n if errors is None:\n result = statement()\n assert result == expected\n else:\n with pytest.raises(errors):\n result = statement()","def test_make_sampled_format(self):\n for num_inputs in [1, 3]:\n for num_outputs in [1, 2, 4]:\n for num_time_steps in [4, 10, 12]:\n # Generate data\n # P=2 format [0, 1, 2, 3, ...]\n sample_interval = 2\n dt_system = np.random.random()\n dt_sample = sample_interval * dt_system\n outputs = np.random.random(\n (num_time_steps, num_outputs, num_inputs))\n time_steps = make_time_steps(\n num_time_steps, sample_interval)\n time_values = time_steps * dt_system\n\n # Compute using modred\n my_ERA = era.ERA()\n time_steps_computed, outputs_computed =\\\n era.make_sampled_format(time_values, outputs)\n #self.assertEqual(dt_system_computed, dt_system)\n\n # Reference values\n num_time_steps_true = (num_time_steps - 1) * 2\n time_steps_true = make_time_steps(num_time_steps_true, 1)\n outputs_true = np.zeros(\n (num_time_steps_true, num_outputs, num_inputs))\n outputs_true[::2] = outputs[:-1]\n outputs_true[1::2] = outputs[1:]\n\n # Compare values\n np.testing.assert_equal(\n time_steps_computed, time_steps_true)\n np.testing.assert_equal(outputs_computed, outputs_true)\n\n # Test that if there is a wrong time value, get an error\n time_values[num_time_steps // 2] = -1\n self.assertRaises(\n ValueError, era.make_sampled_format, time_values,\n outputs)","def test_all_pairs_t_test(self):\r\n # We aren't testing the numeric values here, as they've already been\r\n # tested in the functions that compute them. We are interested in the\r\n # format of the returned string.\r\n exp = \"\"\"# The tests of significance were performed using a two-sided Student's two-sample t-test.\r\n# Alternative hypothesis: Group 1 mean != Group 2 mean\r\n# The nonparametric p-values were calculated using 999 Monte Carlo permutations.\r\n# The nonparametric p-values contain the correct number of significant digits.\r\n# Entries marked with \"N/A\" could not be calculated because at least one of the groups\r\n# of distances was empty, both groups each contained only a single distance, or\r\n# the test could not be performed (e.g. no variance in groups with the same mean).\r\nGroup 1\tGroup 2\tt statistic\tParametric p-value\tParametric p-value (Bonferroni-corrected)\tNonparametric p-value\tNonparametric p-value (Bonferroni-corrected)\r\nfoo\tbar\t-6.6\t0.00708047956412\t0.0212414386924\t0.095\t0.285\r\nfoo\tbaz\t-9.79795897113\t0.000608184944463\t0.00182455483339\t0.101\t0.303\r\nbar\tbaz\t-3.0\t0.0576688856224\t0.173006656867\t0.217\t0.651\r\n\"\"\"\r\n obs = all_pairs_t_test(self.labels2, self.dists2)\r\n self.assertEqual(self.remove_nums(obs), self.remove_nums(exp))","def test_format_phone_formatted(self):\n number1 = '809.555.1234'\n self.assertEqual(format_phone(number1), '(809) 555-1234')\n number2 = '(888) 555-3456'\n self.assertEqual(format_phone(number2), '(888) 555-3456')","def extract_format_results_test(self):\n assert len(self.results.keys()) != 0\n TESTS = [\n {\n \"output\": [\n {\n \"file_name\": \"BSA1.mzML\",\n \"spec_id\": 1337,\n \"formula\": \"C(37)H(59)N(9)O(16)\",\n \"scaling_factor\": 100,\n \"score\": 1,\n \"charge\": 2,\n },\n {\n \"file_name\": \"BSA1.mzML\",\n \"spec_id\": 1338,\n \"formula\": \"C(37)H(59)N(9)O(16)\",\n \"scaling_factor\": 100,\n \"score\": 0.9,\n \"charge\": 2,\n },\n {\n \"file_name\": \"BSA2.mzML\",\n \"spec_id\": 1337,\n \"formula\": \"C(43)H(75)N(15)O(17)S(2)\",\n \"scaling_factor\": 10,\n \"score\": 1,\n \"charge\": 3,\n },\n ]\n }\n ]\n for test_dict in TESTS:\n values = self.results.format_all_results()\n\n assert isinstance(values, pd.DataFrame)\n\n for out_data in test_dict[\"output\"]:\n result = values.loc[\n (values[\"file_name\"] == out_data[\"file_name\"])\n & (values[\"spec_id\"] == out_data[\"spec_id\"])\n ]\n assert (result[\"formula\"] == out_data[\"formula\"]).all()\n assert (result[\"scaling_factor\"] == out_data[\"scaling_factor\"]).all()\n assert (result[\"score\"] == out_data[\"score\"]).all()\n assert (result[\"charge\"] == out_data[\"charge\"]).all()","def _does_output_dict_contain_info(self):\n for species_output_dict in self.output.values():\n for key0, val0 in species_output_dict.items():\n if key0 in ['paths', 'job_types']:\n for key1, val1 in species_output_dict[key0].items():\n if val1 and key1 not in ['rotors', 'bde']:\n return True\n else:\n if val0:\n return True\n return False","def test_print_result(capsys):\n assert \"\"\"Total 5 hands solved\nTotal 4 hands solved with hint\nTotal 4 hands failed to solve\"\"\" in hl.test_help_print_result(capsys)","def test_CLINTOX_2_erroneous_data_INFO_structural(self, mock_print):\n Plotter.from_smiles(self.data_CLINTOX_2_erroneous_smiles[\"smiles\"], target=self.data_CLINTOX_2_erroneous_smiles[\"target\"], target_type=\"C\", sim_type=\"structural\")\n mock_print.assert_called_once_with('The following erroneous SMILES have been found in the data:\\n[NH4][Pt]([NH4])(Cl)Cl\\nc1ccc(cc1)n2c(=O)c(c(=O)n2c3ccccc3)CCS(=O)c4ccccc4\\nCc1cc2c(cc1C)N3C=N2[Co+]456(N7=C8[C@H](C(C7=CC9=N4C(=C(C1=N5[C@@]([C@@H]2N6C(=C8C)[C@@]([C@H]2CC(=O)N)(CCC(=O)NC[C@H](OP(=O)(O[C@@H]2[C@H](O[C@H]3[C@@H]2O)CO)[O-])C)C)([C@@]([C@@H]1CCC(=O)N)(C)CC(=O)N)C)C)[C@@]([C@@H]9CCC(=O)N)(C)CC(=O)N)(C)C)CCC(=O)N)O\\n' + \n 'Cc1cc2c(cc1C)N3C=N2[Co]456(N7=C8[C@H](C(C7=CC9=N4C(=C(C1=N5[C@@]([C@@H]2N6C(=C8C)[C@@]([C@H]2CC(=O)N)(CCC(=O)NC[C@H](OP(=O)(O[C@@H]2[C@H](O[C@H]3[C@@H]2O)CO)O)C)C)([C@@]([C@@H]1CCC(=O)N)(C)CC(=O)N)C)C)[C@@]([C@@H]9CCC(=O)N)(C)CC(=O)N)(C)C)CCC(=O)N)C#N\\n'+\n 'CCCCc1c(=O)n(n(c1=O)c2ccc(cc2)O)c3ccccc3\\nCCCCc1c(=O)n(n(c1=O)c2ccccc2)c3ccccc3.\\n' +\n 'The erroneous SMILES will be removed from the data.')","def format_comparison(objs):\n def formatter(comp):\n if not isinstance(comp, tuple):\n return str(comp)\n output = []\n return \"\\n\".join([comp.type] + [\" \"+errmessage for errmessage in output])\n\n results = map(formatter,objs)\n return \"\\n\".join(results)\n \n #obj1,obj2 = comp\n\n\n ### Sections\n #for i,s1,s2 in diffs:\n # if s1 and s2:\n # output.append(f\"Section {i} does not match:\")\n # result = compare_sections(s1,s2)\n # output.extend(almethods.linepadder(result))\n # else:\n # if s1:\n # output.append(f\"Door 2 missing Section {i}\")\n # else:\n # output.append(f\"Door 1 missing Section {i}\")","def test_available_input_formats():\n assert set([\"Mapchete\", \"raster_file\", \"vector_file\"]).issubset(\n set(available_input_formats())\n )","def test_output(self):\n good_value_pairs = STR_VALUE_PAIRS\n for pair in good_value_pairs:\n output = to_cardinal_trio(pair[0])\n self.assertEqual(output, pair[1],\n f\"{pair[0]} should be {pair[1]}, not {output}\")","def test_get_info(self):\n pass","def test_unsupported_format():\n formatter = TabularOutputFormatter()\n\n with pytest.raises(ValueError):\n formatter.format_name = \"foobar\"\n\n with pytest.raises(ValueError):\n formatter.format_output((), (), format_name=\"foobar\")","def test_full_mode(self):\r\n self.validate((3, 2, 5, 5), (4, 2, 8, 8), 'full')\r\n\r\n def f():\r\n self.validate((3, 2, 5, 5), (4, 2, 8, 8), 'valid')\r\n self.assertRaises(Exception, f)","def test_get_cell_info(self):\n expected = { 'Experiment': \"20220101_EGS1_12345AA\",\n 'Cell': '12345AA0018/20220101_1234_1-A1-A1_AAA66666_deadbeef',\n 'Pool': '12345AA0018',\n 'Date': '20220101',\n 'Number': '1234',\n 'Slot': '1-A1-A1',\n 'CellID': 'AAA66666',\n 'Checksum': 'deadbeef',\n 'Project': '12345',\n 'Base': '12345AA0018/20220101_1234_1-A1-A1_AAA66666_deadbeef/'\n '20220101_EGS1_12345AA_12345AA0018_AAA66666_deadbeef',\n 'Files in pass': 'unknown',\n 'Files in fail': 1,\n 'Files in fast5 fail': 1,\n '_counts': [\n {'_barcode': '.', '_label': 'All passed reads', '_part': 'pass', 'total_reads': 200},\n {'_barcode': '.', '_label': 'Passed and lambda-filtered reads', '_part': 'nolambda'},\n {'_barcode': '.', '_label': 'All failed reads', '_part': 'fail'} ],\n '_blobs': ['../../__blob__'],\n '_duplex' : [ ['Duplex pairs', 1],\n ['from total passing reads', 200],\n ['% of passing reads', '1.00%'] ],\n '_filter_type': 'none',\n '_final_summary': {'is_rna': False},\n '_nanoplot': '../../__nanoplot__',\n }\n\n\n got = get_cell_info( experiment = \"20220101_EGS1_12345AA\",\n cell = \"12345AA0018/20220101_1234_1-A1-A1_AAA66666_deadbeef\",\n cell_content = { '.': dict( fast5_pass = ['x.fast5'],\n fastq_fail = ['y.fastq'],\n fast5_fail = ['y.fast5'] ) },\n counts = { ('.','pass'): dict(total_reads = 200),\n ('.','fail'): dict(),\n ('.','nolambda'): dict() },\n fin_summary = dict(is_rna = False),\n blobs = ['__blob__'],\n nanoplot = '__nanoplot__',\n duplex = 1,\n fast5_meta = dict() )\n\n if VERBOSE:\n pprint(got)\n\n self.assertEqual( type(got), OrderedDict )\n self.assertEqual( dict(got), expected )","def test_standardForm(self):\n\n a, b, t, M = self.cs.standardForm\n self.assertEqual((a, b, t[0, 0], t[1, 0]), (1., 1., 0., 0.))","def test_format_args(self):\n for format_func, formatted in [(lambda: \"1\", \"1\"), (lambda: 2, 2), (lambda: \"foo\", \"foo\")]:\n # These return values are used by TimeIt in order: start, end, start, end, ... So the first time the\n # duration will be 1 second, then 2 seconds, and 3 seconds.\n MockDatetimeNow.RETURN_VALUES = [datetime(1970, 1, 1, 0, 0, 0, 0),\n datetime(1970, 1, 1, 0, 0, 1, 0),\n datetime(1970, 1, 1, 0, 0, 0, 0),\n datetime(1970, 1, 1, 0, 0, 2, 0),\n datetime(1970, 1, 1, 0, 0, 0, 0),\n datetime(1970, 1, 1, 0, 0, 3, 0)]\n MockDatetimeNow.CURRENT_IDX = 0\n with self.subTest(format_func=format_func), patch('mpire.utils.datetime', new=MockDatetimeNow):\n cum_time_array = [0]\n max_time_array = [(0, ''), (0, '')]\n for _ in range(3):\n with TimeIt(cum_time_array, 0, max_time_array, format_func):\n pass\n\n # The heapq only had room for two entries. The highest durations should be kept\n self.assertListEqual(max_time_array, [(2.0, formatted), (3.0, formatted)])","def test_missing_info(self):\r\n self.validate(None, None,\r\n N_image_shape=(3, 2, 8, 8),\r\n N_filter_shape=(4, 2, 5, 5))\r\n self.validate((3, 2, None, None), None,\r\n N_image_shape=(3, 2, 8, 8),\r\n N_filter_shape=(4, 2, 5, 5))\r\n self.validate((None, 2, None, None), (None, 2, 5, 5),\r\n N_image_shape=(3, 2, 8, 8),\r\n N_filter_shape=(4, 2, 5, 5))","def test_format_emperor_autograph(self):\n\n autograph = format_emperor_autograph('mapping_file.txt',\n 'pcoa_unweighted_unifrac.txt')\n\n # check for comment open and comment close\n self.assertTrue('<!--' in autograph)\n self.assertTrue('-->' in autograph)\n # check for fields since we cannot check for the specifics\n self.assertTrue(\"*Summary of Emperor's Information*\" in autograph)\n self.assertTrue('Metadata:' in autograph)\n self.assertTrue('Coordinates:' in autograph)\n self.assertTrue('HostName:' in autograph)\n self.assertTrue(\"Command:\" in autograph)\n self.assertTrue(\"Emperor Version: \" in autograph)\n self.assertTrue(\"QIIME Version: \" in autograph)\n self.assertTrue(\"Command executed on \" in autograph)\n\n autograph = format_emperor_autograph('mapping_file.txt',\n 'pcoa_unweighted_unifrac.txt',\n 'Python')\n # check for comment open and comment close\n self.assertTrue('\"\"\"' in autograph)\n self.assertTrue('\"\"\"' in autograph)\n # check for fields since we cannot check for the specifics\n self.assertTrue(\"*Summary of Emperor's Information*\" in autograph)\n self.assertTrue('Metadata:' in autograph)\n self.assertTrue('Coordinates:' in autograph)\n self.assertTrue('HostName:' in autograph)\n self.assertTrue(\"Command:\" in autograph)\n self.assertTrue(\"Emperor Version: \" in autograph)\n self.assertTrue(\"QIIME Version: \" in autograph)\n self.assertTrue(\"Command executed on \" in autograph)\n\n autograph = format_emperor_autograph('mapping_file.txt',\n 'pcoa_unweighted_unifrac.txt',\n 'C')\n # check for comment open and comment close\n self.assertTrue('/*' in autograph)\n self.assertTrue('*/' in autograph)\n # check for fields since we cannot check for the specifics\n self.assertTrue(\"*Summary of Emperor's Information*\" in autograph)\n self.assertTrue('Metadata:' in autograph)\n self.assertTrue('Coordinates:' in autograph)\n self.assertTrue('HostName:' in autograph)\n self.assertTrue(\"Command:\" in autograph)\n self.assertTrue(\"Emperor Version: \" in autograph)\n self.assertTrue(\"QIIME Version: \" in autograph)\n self.assertTrue(\"Command executed on \" in autograph)\n\n autograph = format_emperor_autograph('mapping_file.txt',\n 'pcoa_unweighted_unifrac.txt',\n 'Bash')\n # check for comment open and comment close\n self.assertTrue('<<COMMENT' in autograph)\n self.assertTrue('COMMENT' in autograph)\n # check for fields since we cannot check for the specifics\n self.assertTrue(\"*Summary of Emperor's Information*\" in autograph)\n self.assertTrue('Metadata:' in autograph)\n self.assertTrue('Coordinates:' in autograph)\n self.assertTrue('HostName:' in autograph)\n self.assertTrue(\"Command:\" in autograph)\n self.assertTrue(\"Emperor Version: \" in autograph)\n self.assertTrue(\"QIIME Version: \" in autograph)\n self.assertTrue(\"Command executed on \" in autograph)\n\n # haskell and cobol are ... not supported\n self.assertRaises(AssertionError, format_emperor_autograph,\n 'mapping_file.txt', 'pcoa.txt', 'Haskell')\n self.assertRaises(AssertionError, format_emperor_autograph,\n 'mapping_file.txt', 'pcoa.txt', 'Cobol')","def _build_summary(\n val1: str | None = None, val2: str | None = None, val3: str | None = None\n ) -> str:\n return ' : '.join([value for value in [val1, val2, val3] if value is not None])","def print(self, failed_tests=True, passed_tests=True, json_format=False):\n # TODO: Do we need the json option?\n if json_format:\n passed = self.passed\n if (passed and passed_tests) or (not passed and failed_tests):\n print(json.dumps(self, indent=4, cls=MyEncoder))\n else:\n separator = \"\"\n\n filtered_output = \"\"\n passed = self.passed\n if passed and passed_tests:\n filtered_output += \"Parser Name = {}\\n\".format(self.parser)\n if self.input_file_path and self.input_file_path != \"N/A\":\n filtered_output += \"Input Filename = {}\\n\".format(self.input_file_path)\n filtered_output += \"Tests Passed = {}\\n\".format(self.passed)\n elif not passed and failed_tests:\n filtered_output += \"Parser Name = {}\\n\".format(self.parser)\n if self.input_file_path and self.input_file_path != \"N/A\":\n filtered_output += \"Input Filename = {}\\n\".format(self.input_file_path)\n filtered_output += \"Tests Passed = {}\\n\".format(self.passed)\n filtered_output += \"Errors = {}\".format(\"\\n\" if self.errors else \"None\\n\")\n if self.errors:\n for entry in self.errors:\n filtered_output += \"\\t{0}\\n\".format(entry)\n filtered_output += \"Debug Logs = {}\".format(\"\\n\" if self.debug else \"None\\n\")\n if self.debug:\n for entry in self.debug:\n filtered_output += \"\\t{0}\\n\".format(entry)\n if self.results:\n filtered_output += \"Results =\\n\"\n for result in self.results:\n if not result.passed:\n filtered_output += \"{0}\\n\".format(result)\n\n if filtered_output:\n filtered_output += \"{0}\\n\".format(separator)\n print(filtered_output.encode(\"ascii\", \"backslashreplace\").decode())","def match_info(info_dict):\n return True","def print_usage():\n print 'USAGE: %s [options]' % os.path.abspath(__file__)\n print 'EXAMPLE1: %s # FOR DEFAULTS' % os.path.abspath(__file__)\n print 'EXAMPLE2: %s 121f03=tweek hirap=towelie details=False # TWO SMALL SETS' % os.path.abspath(__file__)\n print 'EXAMPLE3: %s 121f03=tweek details=True # ONE DETAILED SET' % os.path.abspath(__file__)\n print 'EXAMPLE4: %s details=True # SHOWS MAX INFO' % os.path.abspath(__file__)","def formatted_locator_information(self):\n info = 'May not follow-up.'\n if self.may_follow_up == 'Yes':\n info = (\n '{may_sms_follow_up}\\n'\n 'Cell: {subject_cell} {alt_subject_cell}\\n'\n 'Phone: {subject_phone} {alt_subject_phone}\\n'\n '').format(\n may_sms_follow_up='SMS permitted' if self.may_sms_follow_up == 'Yes' else 'NO SMS!',\n subject_cell='{} (primary)'.format(self.subject_cell) if self.subject_cell else '(none)',\n alt_subject_cell=self.subject_cell_alt,\n subject_phone=self.subject_phone or '(none)', alt_subject_phone=self.subject_phone_alt\n )\n if self.may_call_work == 'Yes':\n info = (\n '{info}\\n Work Contacts:\\n'\n '{subject_work_place}\\n'\n 'Work Phone: {subject_work_phone}\\n'\n '').format(\n info=info,\n subject_work_place=self.subject_work_place or '(work place not known)',\n subject_work_phone=self.subject_work_phone)\n if self.may_contact_someone == 'Yes':\n info = (\n '{info}\\n Contacts of someone else:\\n'\n '{contact_name} - {contact_rel}\\n'\n '{contact_cell} (cell), {contact_phone} (phone)\\n'\n '').format(\n info=info,\n contact_name=self.contact_name or '(name?)',\n contact_rel=self.contact_rel or '(relation?)',\n contact_cell=self.contact_cell or '(----)',\n contact_phone=self.contact_phone or '(----)'\n )\n if info:\n info = ('{info}'\n 'Physical Address:\\n{physical_address}').format(\n info=info, physical_address=self.physical_address)\n return info","def test_plain_flat_yaml(\n before_yaml_flat: str,\n after_yaml_flat: str,\n plain_flat_res: str,\n):\n assert gendiff(\n before_yaml_flat,\n after_yaml_flat,\n form=PLAIN_FORMAT,\n ) == plain_flat_res","def info() -> None:","def test_str_fac():\n structure = Material(input)\n assert (np.abs(structure.calc_nuc_str_fac((2., 0., 0.))) ** 2 - 1702170.4663405998 < 1e-6)\n assert (np.abs(structure.calc_nuc_str_fac((2, 0, 0))) ** 2 - 1702170.4663405998 < 1e-6)\n assert (np.abs(structure.calc_nuc_str_fac((0, 2., 0))) ** 2 - 1702170.4663405998 < 1e-6)\n assert (np.abs(structure.calc_nuc_str_fac((0, 2, 0))) ** 2 - 1702170.4663405998 < 1e-6)\n\n ndarray_example = np.linspace(0.5, 1.5, 21)\n assert (np.sum(abs(structure.calc_nuc_str_fac((ndarray_example, 0, 0))) ** 2) - 7058726.6759794801 < 1e-6)\n assert (np.sum(abs(structure.calc_nuc_str_fac((0, ndarray_example, 0))) ** 2) - 7058726.6759794801 < 1e-6)\n assert (np.sum(abs(structure.calc_nuc_str_fac((0, 0, ndarray_example))) ** 2) - 16831011.814390473 < 1e-6)\n assert (\n np.sum(abs(structure.calc_nuc_str_fac((ndarray_example, ndarray_example, 0))) ** 2) - 10616602.544519115 < 1e-6)\n\n list_example = list(ndarray_example)\n assert (np.sum(abs(structure.calc_nuc_str_fac((list_example, 0, 0))) ** 2) - 7058726.6759794801 < 1e-6)\n assert (np.sum(abs(structure.calc_nuc_str_fac((0, list_example, 0))) ** 2) - 7058726.6759794801 < 1e-6)\n assert (np.sum(abs(structure.calc_nuc_str_fac((0, 0, list_example))) ** 2) - 16831011.814390473 < 1e-6)\n\n tuple_example = tuple(ndarray_example)\n assert (np.sum(abs(structure.calc_nuc_str_fac((tuple_example, 0, 0))) ** 2) - 7058726.6759794801 < 1e-6)\n assert (np.sum(abs(structure.calc_nuc_str_fac((0, tuple_example, 0))) ** 2) - 7058726.6759794801 < 1e-6)\n assert (np.sum(abs(structure.calc_nuc_str_fac((0, 0, tuple_example))) ** 2) - 16831011.814390473 < 1e-6)","def test_output(self):\n good_value_pairs = INT_VALUE_PAIRS\n for pair in good_value_pairs:\n output = to_cardinal_number(pair[0])\n self.assertEqual(output, pair[1],\n f\"{pair[0]} should be {pair[1]}, not {output}\")","def getopt_format(self):\n self._print_enum_opt(\"format\", FORMATTERS)","def test_major_pretty_table(self) -> None:\n rep:Repository = Repository(r\"C:\\Users\\harsh\\OneDrive\\Desktop\\My Files\\Assignment\")\n expected: Dict[str] = {\n 'SFEN': ['SFEN', ['SSW 540', 'SSW 555', 'SSW 810'], ['CS 501', 'CS 546']],\n 'CS': ['CS', ['CS 546', 'CS 570'], ['SSW 565', 'SSW 810']]\n }\n \n res = {m: mj.major_info() for m, mj in rep._majors.items()}\n \n self.assertEqual(expected, res)","def check_and_print_if_error(self): # pragma: no cover\n dupes, empties, not_detected = self._get_aberrations()\n if dupes:\n print 'duplicate entries for:'\n for dup, matches in dupes:\n print ' %s: %s' % (dup, [f.func_name for f in matches])\n if empties:\n print 'empty entries for:'\n for empty in empties:\n print ' ' + str(empty)\n if not_detected:\n print 'dimensions not detected:'\n for n_d in not_detected:\n print ' ' + str(n_d)\n return self.is_correct","def _processOutfmtArg(outfmt, stderr, gb_record_fmtdict, gb_cds_fmtdict) :\n outfmt_keys = outfmt.split(\",\")\n records_keys = set(gb_record_fmtdict.keys())\n cds_keys = set(gb_cds_fmtdict.keys())\n assert records_keys & cds_keys == set()\n if not all([x in records_keys | cds_keys for x in outfmt_keys]) :\n wrong_keys = [x for x in outfmt_keys if x not in records_keys | cds_keys]\n stderr.write(\"Bad outfmt specifier. You provided:\\n\")\n stderr.write(str(sorted(outfmt_keys)) + \"\\n\")\n stderr.write(\"Wrong specifier(s):\\n\")\n stderr.write(str(sorted(wrong_keys)) + \"\\n\")\n stderr.write(\"Allowed values are:\\n\")\n stderr.write(str(sorted(list(records_keys | cds_keys))) + \"\\n\")\n return outfmt_keys","def test_context_data_info_message_for_multiple_result(self):\n factories.SourceTraitFactory.create(\n i_description='lorem ipsum',\n source_dataset__source_study_version__study=self.study)\n factories.SourceTraitFactory.create(\n i_description='lorem ipsum 2',\n source_dataset__source_study_version__study=self.study)\n response = self.client.get(self.get_url(self.study.pk), {'description': 'lorem'})\n messages = list(response.wsgi_request._messages)\n self.assertEqual(len(messages), 1)\n self.assertEqual(str(messages[0]), '2 results found.')","def report_full(*args, **kwargs): # real signature unknown\n pass","def missing_info(**kwargs) -> str:\n func = kwargs.pop('func', 'unknown')\n if 'ticker' in kwargs: kwargs['ticker'] = kwargs['ticker'].replace('/', '_')\n for dt in ['dt', 'start_dt', 'end_dt', 'start_date', 'end_date']:\n if dt not in kwargs: continue\n kwargs[dt] = utils.fmt_dt(kwargs[dt])\n info = utils.to_str(kwargs, fmt='{value}', sep='/')[1:-1]\n return f'{func}/{info}'","def info(obj):\n if obj is None:\n return 'None.'\n elif isinstance(obj, list):\n if obj:\n return 'List of %d... %s' % (len(obj), info(obj[0]))\n else:\n return 'Empty list.'\n elif isinstance(obj, tuple):\n if obj:\n return 'Tuple of %d... %s' % (len(obj), info(obj[0]))\n else:\n return 'Empty tuple.'\n else:\n if is_a_numpy_array(obj):\n return 'Array with shape: %s, dtype: %s' % (obj.shape, obj.dtype)\n else:\n return str(obj)","def info_to_fits(obs_info: ObservationInfo) -> tuple[dict[str, Any], dict[str, str]]:\n cards = {}\n comments = {}\n\n if obs_info.instrument is not None:\n cards[\"INSTRUME\"] = obs_info.instrument\n comments[\"INSTRUME\"] = \"Name of instrument\"\n\n cards.update(dates_to_fits(obs_info.datetime_begin, obs_info.datetime_end))\n\n return cards, comments","def show_help():\n messagebox.showinfo('Data entering', \"\"\"\n Enter equal arrays of x and y values\n Separate values with space < >, tab < > or coma <,>\n Separate fraction using dot <.>\n \"\"\")","def getInfo(self, formatted=False):\n\n\t\tinfo = {}\n\t\tinfo['Python'] = \"%d.%d.%d\" %(sys.version_info[0], sys.version_info[1], sys.version_info[2])\n\t\tinfo[__binding__] = __binding_version__\n\t\tinfo['Qt'] = QtCore.qVersion()\n\t\tinfo['OS'] = platform.system()\n\t\tinfo['Environment'] = HOST\n\n\t\tif formatted:\n\t\t\tinfo_ls = []\n\t\t\tfor key, value in info.items():\n\t\t\t\tinfo_ls.append(\"{} {}\".format(key, value))\n\t\t\tinfo_str = \" | \".join(info_ls)\n\t\t\treturn info_str\n\n\t\telse:\n\t\t\treturn info","def print_exact_res():\n\n print(\"************************************************************\")\n print(\"EXACT RESULT FOR THE VALUES THAT MINIMIZE THE FUNCTION:\\n\")\n f_str = \"The value of x_{:d} is {:f}\"\n for i in range(1, cfg.n + 1):\n print(f_str.format(i, float(i)))\n print(\"************************************************************\\n\")","def test_workload_get_command_human_readable(\n workload_get_success, workload_get_success_hr\n):\n hr_output = prepare_workload_get_output(workload_get_success)\n assert hr_output == workload_get_success_hr","def test_validate_fasta(self):\r\n\r\n validate_fasta(self.sample_fasta_fp, self.sample_mapping_fp,\r\n self.output_dir)\r\n\r\n expected_log_fp = join(self.output_dir,\r\n split(self.sample_fasta_fp)[1] + \"_report.log\")\r\n\r\n log_f = open(expected_log_fp, \"U\")\r\n actual_log_lines = [line.strip() for line in log_f][1:]\r\n\r\n expected_log_lines = \"\"\"Percent duplicate labels: 0.000\r\nPercent QIIME-incompatible fasta labels: 0.000\r\nPercent of labels that fail to map to SampleIDs: 0.000\r\nPercent of sequences with invalid characters: 0.000\r\nPercent of sequences with barcodes detected: 0.000\r\nPercent of sequences with barcodes detected at the beginning of the sequence: 0.000\r\nPercent of sequences with primers detected: 0.000\"\"\".split('\\n')\r\n\r\n self.assertEqual(actual_log_lines, expected_log_lines)\r\n\r\n # Check with all optional values included\r\n\r\n validate_fasta(self.sample_fasta_fp, self.sample_mapping_fp,\r\n self.output_dir, tree_fp=self.sample_tree_5tips_fp, tree_subset=True,\r\n tree_exact_match=True, same_seq_lens=True, all_ids_found=True)\r\n\r\n expected_log_fp = join(self.output_dir,\r\n split(self.sample_fasta_fp)[1] + \"_report.log\")\r\n\r\n log_f = open(expected_log_fp, \"U\")\r\n actual_log_lines = [line.strip() for line in log_f][1:]\r\n\r\n expected_log_lines = \"\"\"Percent duplicate labels: 0.000\r\nPercent QIIME-incompatible fasta labels: 0.000\r\nPercent of labels that fail to map to SampleIDs: 0.000\r\nPercent of sequences with invalid characters: 0.000\r\nPercent of sequences with barcodes detected: 0.000\r\nPercent of sequences with barcodes detected at the beginning of the sequence: 0.000\r\nPercent of sequences with primers detected: 0.000\r\nSequence lengths report\r\nCounts of sequences, followed by their sequence lengths:\r\n1\\t35\r\n1\\t32\r\n1\\t27\r\nSample ID in fasta sequences report\r\nThe following SampleIDs were not found:\r\nseq2\r\nFasta label subset in tree tips report\r\nAll fasta labels were a subset of tree tips.\r\nFasta label/tree tip exact match report\r\nAll fasta labels found in tree tips.\r\nThe following tips were not in fasta labels:\r\nseq2\r\nseq5\r\nseq4\"\"\".split('\\n')\r\n\r\n self.assertEqual(actual_log_lines, expected_log_lines)","def get_valid_output_format(self, idx, virt_format_list, explicit_format_list, specified_image_format):\n output_image_format = \"\"\n if self.debug_mode:\n print \"\\nwanted output image format is: \" + str(specified_image_format)\n if specified_image_format == \"VIRT\":\n virt_image_format = virt_format_list[0][idx] #Should be reduced to a unique list now (so we can index by 0)\n if self.debug_mode:\n print \"output virt resulting image format is: \" + virt_image_format\n output_image_format = virt_image_format.strip('VIRT->')\n if self.debug_mode:\n print \"output image format is: \" + output_image_format\n else:\n for image_format in explicit_format_list:\n if specified_image_format == image_format[idx]:\n output_image_format = specified_image_format #Should be unique value in the list\n if self.debug_mode:\n print \"(explicit) output image format is: \" + str(output_image_format)\n\n return output_image_format","def test_stack_info(self):\n self.assertEqual(DiscordReportFormatter().format(self.record(sinfo=\"stack\")), \":warning: **test**\\n\" + \\\n \"**stack**\\n\" + \\\n \"```\\n\" + \\\n \"stack\\n\" + \\\n \"```\")","def test_format_variations(test_format, expect_format):\n format_schema = sd.DeploymentFormat()\n try:\n result_format = format_schema.deserialize(test_format)\n result_format.pop(\"$schema\", None)\n assert result_format == expect_format\n except colander.Invalid:\n pytest.fail(f\"Expected format to be valid: [{test_format}]\")","def test_get_structure_fmt(self):\n fmt, block_size = get_structure_fmt(SlotHeaderStructure)\n self.assertEqual(fmt, self.fmt_slot_header)\n self.assertEqual(block_size, self.block_size_slot_header)","def test_algorithm_info_fine(self):\n\t\ti = self.algo.algorithmInfo()\n\t\tself.assertIsNotNone(i)"],"string":"[\n \"def test_format_correlation_info(self):\\r\\n # With 999 permutations.\\r\\n exp = 'Correlation coefficient\\\\tParametric p-value\\\\tNonparametric ' + \\\\\\r\\n 'p-value\\\\tCI (lower)\\\\tCI (upper)\\\\n0.7778\\\\t0.0000\\\\t' + \\\\\\r\\n '0.000\\\\t0.0000\\\\t1.0000\\\\n'\\r\\n obs = format_correlation_info(0.7778, 0, 0, (0, 1), 999)\\r\\n self.assertEqual(obs, exp)\\r\\n\\r\\n # With 0 permutations.\\r\\n exp = 'Correlation coefficient\\\\tParametric p-value\\\\tNonparametric ' + \\\\\\r\\n 'p-value\\\\tCI (lower)\\\\tCI (upper)\\\\n0.7778\\\\t0.0000\\\\t' + \\\\\\r\\n 'N/A\\\\t0.0000\\\\t1.0000\\\\n'\\r\\n obs = format_correlation_info(0.7778, 0, 0, (0, 1), 0)\\r\\n self.assertEqual(obs, exp)\\r\\n\\r\\n # With a small number of permutations.\\r\\n exp = 'Correlation coefficient\\\\tParametric p-value\\\\tNonparametric ' + \\\\\\r\\n 'p-value\\\\tCI (lower)\\\\tCI (upper)\\\\n0.7778\\\\t0.0000\\\\t' + \\\\\\r\\n 'Too few iters to compute p-value (num_iters=1)\\\\t' + \\\\\\r\\n '0.0000\\\\t1.0000\\\\n'\\r\\n obs = format_correlation_info(0.7778, 0, 0, (0, 1), 1)\\r\\n self.assertEqual(obs, exp)\\r\\n\\r\\n # With undefined confidence interval.\\r\\n exp = 'Correlation coefficient\\\\tParametric p-value\\\\tNonparametric ' + \\\\\\r\\n 'p-value\\\\tCI (lower)\\\\tCI (upper)\\\\n0.7778\\\\t0.0000\\\\t' + \\\\\\r\\n 'N/A\\\\tN/A\\\\tN/A\\\\n'\\r\\n obs = format_correlation_info(0.7778, 0, 0, (None, None), 0)\\r\\n self.assertEqual(obs, exp)\",\n \"def test_is_entry_formatted(self):\\n\\n valid_formats = test_case_data.get('valid_formats')\\n for i, valid_entry in enumerate(test_case_data.get('valid_entries')):\\n entry = [value.strip() for value in valid_entry.split(',')]\\n format_fields = valid_formats[i].split(',')\\n valid = self.parser._is_entry_formatted(entry, format_fields)\\n self.assertTrue(valid, f'{entry} is not of a valid format')\\n\\n # fails with invalid entries\\n for invalid_entry in test_case_data.get('invalid_entries'):\\n entry = [value.strip() for value in invalid_entry.split(',')]\\n for f in valid_formats:\\n format_fields = f.split(',')\\n entry_dict = self.parser._is_entry_formatted(entry, format_fields)\\n self.assertFalse(entry_dict, f'{entry} is not of a valid format')\",\n \"def PrintDetailedE(GaussE, TinkE, sumE, result_format):\\n ## Force to lowercase for search\\n result_format = [each_form.lower() for each_form in result_format]\\n if 'all' in result_format:\\n print(\\\"\\\\n\\\")\\n print(f\\\"Gaussian Energy (au): {GaussE/har2ev:.10f} +\\\")\\n print(f\\\"Tinker Energy (au): {TinkE/har2ev:.10f}\\\")\\n print(\\\"===========================================\\\")\\n print(f\\\"QM/MM Energy (au): {sumE/har2ev:.10f}\\\\n\\\")\\n print(\\\"\\\\n\\\")\\n print(f\\\"Gaussian Energy (kcal/mol): {GaussE/kcal2ev:.10f} +\\\")\\n print(f\\\"Tinker Energy (kcal/mol): {TinkE/kcal2ev:.10f}\\\")\\n print(\\\"====================================================\\\")\\n print(f\\\"QM/MM Energy (kcal/mol): {sumE/kcal2ev:.10f}\\\\n\\\")\\n print(\\\"\\\\n\\\")\\n print(f\\\"Gaussian Energy (eV): {GaussE:.10f} +\\\")\\n print(f\\\"Tinker Energy (eV): {TinkE:.10f}\\\")\\n print(\\\"============================================\\\")\\n print(f\\\"QM/MM Energy (eV): {sumE:.10f}\\\\n\\\")\\n else:\\n one_printed = False\\n print(\\\"\\\")\\n for form in result_format:\\n if form.lower() == 'au':\\n print(f\\\"Gaussian Energy (au): {GaussE/har2ev:.10f} +\\\")\\n print(f\\\"Tinker Energy (au): {TinkE/har2ev:.10f}\\\")\\n print(\\\"==========================================\\\")\\n print(f\\\"QM/MM Energy (au): {sumE/har2ev:.10f}\\\\n\\\")\\n one_printed = True\\n elif form.lower() in ('hartree', 'hartrees', 'hartree(s)'):\\n print(f\\\"Gaussian Energy (Hartrees): {GaussE/har2ev:.10f} +\\\")\\n print(f\\\"Tinker Energy (Hartrees): {TinkE/har2ev:.10f}\\\")\\n print(\\\"================================================\\\")\\n print(f\\\"QM/MM Energy (Hartrees): {sumE/har2ev:.10f}\\\\n\\\")\\n one_printed = True\\n elif form.lower() in ('kcal', 'kcal/mol'):\\n print(f\\\"Gaussian Energy (kcal/mol): {GaussE/kcal2ev:.10f} +\\\")\\n print(f\\\"Tinker Energy (kcal/mol): {TinkE/kcal2ev:.10f}\\\")\\n print(\\\"====================================================\\\")\\n print(f\\\"QM/MM Energy (kcal/mol): {sumE/kcal2ev:.10f}\\\\n\\\")\\n one_printed = True\\n elif form.lower() == 'ev':\\n print(f\\\"Gaussian Energy (eV): {GaussE:.10f} +\\\")\\n print(f\\\"Tinker Energy (eV): {TinkE:.10f}\\\")\\n print(\\\"============================================\\\")\\n print(f\\\"QM/MM Energy (eV): {sumE:.10f}\\\\n\\\")\\n one_printed = True\\n else:\\n if one_printed == True:\\n print(f\\\"I can't parse your requested result_format, '{form}'.\\\")\\n print(\\\"I only accept a list of values, such as:\\\")\\n print(\\\" 'au', 'hartrees', 'ev', 'kcal', 'all'\\\")\\n else:\\n print(f\\\"I can't parse your requested result_format, '{form}'.\\\")\\n print(\\\"I only accept a list of values, such as:\\\")\\n print(\\\" 'au', 'hartrees', 'ev', 'kcal', 'all'\\\")\\n print(\\\"Printing au instead...\\\\n\\\")\\n print(f\\\"Gaussian Energy (au): {GaussE/har2ev:.10f} +\\\")\\n print(f\\\"Tinker Energy (au): {TinkE/har2ev:.10f}\\\")\\n print(\\\"============================================\\\")\\n print(f\\\"QM/MM Energy (au): {sumE/har2ev:.10f}\\\\n\\\")\",\n \"def helper():\\n for mode in PackingMode:\\n for bin_algo in PackingBin:\\n for size, w, h in ('big_enough', 50, 50), ('too_small', 5, 5):\\n name = '_'.join(('test', mode, bin_algo, size))\\n print(\\\"\\\"\\\"\\\\\\n def %s(self):\\n # create bins that are %s to hold the rectangles\\n p = self._common(PackingMode.%s, PackingBin.%s, %s, %s)\\\"\\\"\\\" %\\n (name, size.replace('_', ' '), mode, bin_algo, w, h))\\n if size == 'big_enough':\\n print(\\\"\\\"\\\"\\\\\\n # check that bins were created\\n self.assertGreater(len(p.bin_list()), 0)\\n # check that all of the rectangles made it in\\n self.assertEqual(len(p.rect_list()), len(self.rectangles))\\n\\\"\\\"\\\")\\n else:\\n print(\\\"\\\"\\\"\\\\\\n # check that none of the rectangles made it in\\n self.assertEqual(len(p.rect_list()), 0)\\n\\\"\\\"\\\")\",\n \"def test_buoy_format1():\\n with pytest.raises(AssertionError) as err_info:\\n Check_BuoyDC.check_buoy_format(buoy_format_fail_1)\\n assert str(err_info.value) == 'Input formatted incorrectly, see instructions'\",\n \"def test_enforce_iterable():\\n formatter = TabularOutputFormatter()\\n loremipsum = (\\n \\\"lorem ipsum dolor sit amet consectetur adipiscing elit sed do eiusmod\\\".split(\\n \\\" \\\"\\n )\\n )\\n\\n for format_name in formatter.supported_formats:\\n formatter.format_name = format_name\\n try:\\n formatted = next(formatter.format_output(zip(loremipsum), [\\\"lorem\\\"]))\\n except TypeError:\\n assert False, \\\"{0} doesn't return iterable\\\".format(format_name)\",\n \"def test_match_entry_to_format(self):\\n\\n # matches valid entries with valid formats\\n for valid_entry in test_case_data.get('valid_entries'):\\n entry = [e.strip() for e in valid_entry.split(',')]\\n entry_dict = self.parser._match_entry_to_format(entry)\\n\\n self.assertTrue(entry_dict, f'{entry} is not of a valid format')\\n\\n # fails with invalid entries\\n for invalid_entry in test_case_data.get('invalid_entries'):\\n entry = [e.strip() for e in invalid_entry.split(',')]\\n entry_dict = self.parser._match_entry_to_format(entry)\\n\\n self.assertFalse(entry_dict, f'{entry} is not of a valid format')\",\n \"def checkMTSinfoCompliance(info):\\n if len(info) != 3:\\n print(\\\"MTS INFO DOES NOT ADHERE TO MY STANDARD: processingUnit_machine_order\\\")\\n exit(5)\",\n \"def test_build_format_map(all_sets: dict, expected: dict) -> None:\\n result = build_format_map(all_sets, regular=False)\\n assert result == expected\",\n \"def test_reponse_format(y):\\r\\n print(\\\"test_response_format()...\\\", end = \\\"\\\")\\r\\n for item in y:\\r\\n assert (item == 0 or item == 1)\\r\\n print(\\\"Passed!\\\")\",\n \"def test_buoy_format2():\\n with pytest.raises(AssertionError) as err_info:\\n Check_BuoyDC.check_buoy_format(buoy_format_fail_2)\\n assert str(err_info.value) == 'Input length incorrect, see instructions'\",\n \"def get_format_opts(cls, format_=\\\"value\\\", fields=[]):\\n return \\\" -f {0} {1}\\\".format(format_, \\\" \\\".join([\\\"-c \\\" + it for it in fields]))\",\n \"def handle_short_info(files, directories, args):\\n result_info = []\\n # Define the width of columns\\n max_length = 0\\n if directories:\\n max_length = max(max(len(item) for item in directories[d])\\n for d in directories)\\n if files:\\n max_length = max(max_length, max(len(item) for item in files))\\n col_width = max_length + 1\\n terminal_width = shutil.get_terminal_size().columns\\n if args.format == 'single-column' or args.one:\\n columns = 1\\n else:\\n columns = terminal_width // (max_length + 1) or 1\\n\\n if not files and len(directories) == 1:\\n d = list(directories.keys())[0]\\n result_info.extend(handle_files_group(directories[d],\\n columns, col_width, args))\\n log.debug(result_info)\\n return result_info\\n\\n if files:\\n result_info.extend(handle_files_group(files, columns, col_width, args))\\n for d in directories:\\n result_info.append(f'{d}:')\\n result_info.extend(handle_files_group(directories[d],\\n columns, col_width, args))\\n log.debug(result_info)\\n return result_info\",\n \"def format_info(self, *args):\\n if self._pretty:\\n return self.format_multiline_message(*args, color='cyan', start='[INFO] ', multiline=' ~~ ')\\n return self.format_multiline_message(*args)\",\n \"def test_feature_format(X):\\r\\n print(\\\"test_feature_format()...\\\", end = \\\"\\\")\\r\\n for row in range(len(X)):\\r\\n for col in range(len(X[0])):\\r\\n assert (isinstance(X[row][col], float) == True)\\r\\n print(\\\"Passed!\\\")\",\n \"def test_supported_formats_interpolations(self):\\n params_82 = {\\n 'ReQuEsT': \\\"DescribeCoverage\\\",\\n 'SeRvIcE': \\\"WCS\\\",\\n \\\"BOGUS\\\": \\\"SSS\\\",\\n 'Version': \\\"1.0.0\\\",\\n \\\"COVERAGE\\\": self.names[0]\\n }\\n response = self.query_server(params_82)\\n soup = BeautifulSoup(response.text, 'xml')\\n formats = list(map(lambda f: f.text, soup.find_all('formats')))\\n self.assertTrue(\\n len(set([\\\"GeoTIFF\\\", \\\"HDF-EOS\\\", \\\"DTED\\\", \\\"NITF\\\", \\\"GML\\\"]).intersection(formats)) > 0,\\n msg=\\\"The first format returned in a coverage description should be one of the five defined in the spec.\\\")\\n interpolations = list(map(lambda f: f.text, soup.find_all('interpolationMethod')))\\n self.assertTrue(\\n len(\\n set([\\\"nearest neighbor\\\", \\\"bilinear\\\", \\\"bicubic\\\", \\\"lost area\\\", \\\"barycentric\\\"]).intersection(\\n interpolations)) > 0,\\n msg=\\\"Supported interpolations must be one of the five defined in the spec.\\\")\",\n \"def test_tabular_format_output_wrapper():\\n data = [[\\\"1\\\", None], [\\\"2\\\", \\\"Sam\\\"], [\\\"3\\\", \\\"Joe\\\"]]\\n headers = [\\\"id\\\", \\\"name\\\"]\\n expected = dedent(\\n \\\"\\\"\\\"\\\\\\n +----+------+\\n | id | name |\\n +----+------+\\n | 1 | N/A |\\n | 2 | Sam |\\n | 3 | Joe |\\n +----+------+\\\"\\\"\\\"\\n )\\n\\n assert expected == \\\"\\\\n\\\".join(\\n format_output(iter(data), headers, format_name=\\\"ascii\\\", missing_value=\\\"N/A\\\")\\n )\",\n \"def test_nothing_fits():\\n freetimes, _ = free([], 9, 0, 17, 0, day_range, 600)\\n fmt_freetime = output_format(freetimes)\\n for i in fmt_freetime:\\n print(i)\\n assert fmt_freetime == []\",\n \"def testFormatLabelAndValue(self):\\n\\n self.assertEqual('Abc: xyz', self.inv._FormatLabelAndValue('abc', 'xyz', 1))\\n self.assertEqual('ABc: xyz', self.inv._FormatLabelAndValue('abc', 'xyz', 2))\\n self.assertEqual('ABC: xyz', self.inv._FormatLabelAndValue('abc', 'xyz', 4))\",\n \"def _info(self, N):\\n IDs = self.chemicals.IDs\\n data = self.data\\n IDs, data = nonzeros(IDs, data)\\n N_IDs = len(IDs)\\n if N_IDs == 0:\\n return f\\\"{type(self).__name__}: (all zeros)\\\"\\n else:\\n basic_info = f\\\"{type(self).__name__}:\\\\n\\\"\\n new_line = '\\\\n'\\n data_info = ''\\n lengths = [len(i) for i in IDs]\\n maxlen = max(lengths) + 1\\n N_max = N or tmo.Stream.display_units.N\\n too_many_chemicals = N_IDs > N_max\\n N = N_max if too_many_chemicals else N_IDs\\n for i in range(N):\\n spaces = ' ' * (maxlen - lengths[i])\\n if i != 0:\\n data_info += new_line\\n data_info += IDs[i] + spaces + f' {data[i]:.3g}'\\n if too_many_chemicals:\\n data_info += new_line + '...'\\n return (basic_info\\n + data_info)\",\n \"def test_format_best_results(self):\\r\\n # Single category.\\r\\n exp = ('Method name\\\\tNumber of categories\\\\tCategories\\\\t'\\r\\n 'rho statistics\\\\nBEST\\\\t1\\\\tDOB = 1\\\\t(-0.001, \\\\'1\\\\')\\\\n')\\r\\n obs = format_best_results({'method_name': 'BEST', 'num_vars': 1,\\r\\n 'vars': ['DOB = 1'],\\r\\n 'rho_vals': [(-0.0010, '1')]})\\r\\n self.assertEqual(obs, exp)\\r\\n\\r\\n # Multiple categories.\\r\\n exp = ('Method name\\\\tNumber of categories\\\\tCategories\\\\t'\\r\\n 'rho statistics\\\\nBEST\\\\t2\\\\tDOB = 1, pH = 2\\\\t(-0.001, \\\\'1\\\\'), '\\r\\n '(0.99909, \\\\'1,2\\\\')\\\\n')\\r\\n obs = format_best_results({'method_name': 'BEST', 'num_vars': 2,\\r\\n 'vars': ['DOB = 1', 'pH = 2'],\\r\\n 'rho_vals': [(-0.0010, '1'),\\r\\n (0.99909, '1,2')]})\\r\\n self.assertEqual(obs, exp)\",\n \"def test_nested_format_fields():\\n '{0:>{1}}'.format(42, 24)\\n '{0:{a[1]}} {a}'.format(1, a=[1, 2])\\n '{:>{}}'.format(42, 24)\\n '{0:>{1}}'.format(42)\\n '{0:>{1}}'.format(42, 24, 54)\\n ##Warn: W1303\\n '{0:{a[1]}}'.format(1)\\n ##Warn: W1306\\n '{0:{a.x}}'.format(1, a=2)\",\n \"def fp_config_formatting(info):\\n # From: OpenCL/AMDAPPSDK-3.0/include/CL/cl.h\\n options = [((1 << 0), 'CL_FP_DENORM'),\\n ((1 << 1), 'CL_FP_INF_NAN'),\\n ((1 << 2), 'CL_FP_ROUND_TO_NEAREST'),\\n ((1 << 3), 'CL_FP_ROUND_TO_ZERO'),\\n ((1 << 4), 'CL_FP_ROUND_TO_INF'),\\n ((1 << 5), 'CL_FP_FMA'),\\n ((1 << 6), 'CL_FP_SOFT_FLOAT'),\\n ((1 << 7), 'CL_FP_CORRECTLY_ROUNDED_DIVIDE_SQRT')]\\n # The initial line shows the bitmap, following lines\\n # explicitly show the meaning and availability.\\n option_breakdown = [bin(info)]\\n for bitfield, option in options:\\n is_available = bool(bitfield & info)\\n option_breakdown.append('{}={}'.format(option, is_available))\\n return ('\\\\n\\\\t'+' '*(device_maxwidth+3)).join(option_breakdown)\",\n \"def test_format_info():\\n data = grp.struct_group((\\\"wheel\\\", \\\"*\\\", 0, [\\\"root\\\"]))\\n ret = {\\\"passwd\\\": \\\"*\\\", \\\"gid\\\": 0, \\\"name\\\": \\\"wheel\\\", \\\"members\\\": [\\\"root\\\"]}\\n assert mac_group._format_info(data) == ret\",\n \"def test_printdiff(self):\\n\\n # Testing different string input options\\n assert printdiff(self.data(\\\"arange.fits\\\"), self.data(\\\"blank.fits\\\")) is None\\n assert (\\n printdiff(self.data(\\\"arange.fits\\\"), self.data(\\\"blank.fits\\\"), ext=0) is None\\n )\\n assert (\\n printdiff(\\n self.data(\\\"o4sp040b0_raw.fits\\\"),\\n self.data(\\\"o4sp040b0_raw.fits\\\"),\\n extname=\\\"sci\\\",\\n )\\n is None\\n )\\n\\n # This may seem weird, but check printdiff to see, need to test\\n # incorrect second file\\n with pytest.raises(OSError):\\n printdiff(\\\"o4sp040b0_raw.fits\\\", \\\"fakefile.fits\\\", extname=\\\"sci\\\")\\n\\n # Test HDU object inputs\\n with fits.open(self.data(\\\"stddata.fits\\\"), mode=\\\"readonly\\\") as in1:\\n with fits.open(self.data(\\\"checksum.fits\\\"), mode=\\\"readonly\\\") as in2:\\n assert printdiff(in1[0], in2[0]) is None\\n\\n with pytest.raises(ValueError):\\n printdiff(in1[0], in2[0], ext=0)\\n\\n assert printdiff(in1, in2) is None\\n\\n with pytest.raises(NotImplementedError):\\n printdiff(in1, in2, 0)\",\n \"def test_printdiff(self):\\n\\n # Testing different string input options\\n assert printdiff(self.data('arange.fits'),\\n self.data('blank.fits')) is None\\n assert printdiff(self.data('arange.fits'),\\n self.data('blank.fits'), ext=0) is None\\n assert printdiff(self.data('o4sp040b0_raw.fits'),\\n self.data('o4sp040b0_raw.fits'),\\n extname='sci') is None\\n\\n # This may seem weird, but check printdiff to see, need to test\\n # incorrect second file\\n with pytest.raises(IOError):\\n printdiff('o4sp040b0_raw.fits', 'fakefile.fits', extname='sci')\\n\\n # Test HDU object inputs\\n with fits.open(self.data('stddata.fits'), mode='readonly') as in1:\\n with fits.open(self.data('checksum.fits'), mode='readonly') as in2:\\n\\n assert printdiff(in1[0], in2[0]) is None\\n\\n with pytest.raises(ValueError):\\n printdiff(in1[0], in2[0], ext=0)\\n\\n assert printdiff(in1, in2) is None\\n\\n with pytest.raises(NotImplementedError):\\n printdiff(in1, in2, 0)\",\n \"def test_sequence_info(self):\\n self.t(\\\"1,2 info\\\")\\n code, out, err = self.t(\\\"_get 1.description 2.description\\\")\\n self.assertEqual(out.count(\\\"miss\\\"), 2)\",\n \"def handle_full_info(files, directories, args):\\n result_info = []\\n if not files and len(directories) == 1:\\n d = list(directories.keys())[0]\\n result_info.extend(full_info(directories[d], args, d))\\n log.debug(result_info)\\n return result_info\\n\\n if files:\\n result_info.extend(full_info(files, args))\\n for d in directories:\\n result_info.append(f'{d}:')\\n result_info.extend(full_info(directories[d], args, d))\\n log.debug(result_info)\\n return result_info\",\n \"def _test_parts(self):\\n\\n message = []\\n\\n if self._year is None:\\n message.append(\\\"No year\\\")\\n else:\\n try:\\n int(self._year)\\n except:\\n message.append(\\\"Bad year {}\\\".format(self._year))\\n\\n if not self._release:\\n message.append(\\\"No release\\\")\\n else:\\n try:\\n assert (int(self._release) in [1, 5])\\n except:\\n message.append(\\\"Bad release {}\\\".format(self._release))\\n\\n if not self._state:\\n message.append(\\\"No state\\\")\\n elif len(self._state) != 2:\\n message.append(\\\"Bad state {}\\\".format(self._state))\\n\\n if not self._record_type:\\n message.append(\\\"No record_type\\\")\\n else:\\n try:\\n assert(self._record_type.upper()[0] in ['H','P'])\\n except:\\n message.append(\\\"Bad record type {}\\\".format(self._record_type))\\n\\n return message\",\n \"def _test_output_formatting_func(self, sample: Any):\\n try:\\n if not type(sample) == iter:\\n self._formatting_func_return_types(format=sample)\\n return True\\n except Exception:\\n raise ValueError(\\n f\\\"formatting_func must return {self._formatting_func_return_types.__annotations__['format']}, not {type(sample)}\\\"\\n )\",\n \"def test_input_conversion(self):\\n data = [dict(A=0.1, C=0.2), dict(A=0.1, C=0.2)]\\n base = [(\\\"A\\\", 0.1), (\\\"C\\\", 0.2)]\\n expect = [base, base]\\n got = _char_hts_as_lists(data)\\n self.assertEqual(got, expect)\\n #\\n data = [dict(A=0.1, C=0.2), {}]\\n base = [(\\\"A\\\", 0.1), (\\\"C\\\", 0.2)]\\n expect = [base, None]\\n got = _char_hts_as_lists(data)\\n self.assertEqual(got, expect)\\n data = [dict(A=0.1, C=0.2), None]\\n base = [(\\\"A\\\", 0.1), (\\\"C\\\", 0.2)]\\n expect = [base, None]\\n got = _char_hts_as_lists(data)\\n self.assertEqual(got, expect)\",\n \"def print_pairing_info(melon_types):\\n\\n # Fill in the rest\",\n \"def test_plain_flat_json(\\n before_json_flat: str,\\n after_json_flat: str,\\n plain_flat_res: str,\\n):\\n assert gendiff(\\n before_json_flat,\\n after_json_flat,\\n form=PLAIN_FORMAT,\\n ) == plain_flat_res\",\n \"def test_available_output_formats():\\n assert set([\\\"GTiff\\\", \\\"PNG\\\", \\\"PNG_hillshade\\\", \\\"GeoJSON\\\"]).issubset(\\n set(available_output_formats())\\n )\",\n \"def test_print_formatter():\\n tuple_1 = (\\\"test\\\", \\\"me\\\", 1.22, 1.42)\\n tuple_2 = (\\\"test2\\\", 4.20, 1.2)\\n tuple_3 = (1.2, \\\"test3\\\", 4.20)\\n assert print_formatter(tuple_1) == (\\\"me\\\", '1.22', '1.42')\\n with pytest.raises(IndexError):\\n print_formatter(tuple_2)\\n print_formatter(tuple_3)\",\n \"def individual_info(self, ctx: commands.Context, format: str) -> str:\\n\\t\\tformat = self.__normalize(ctx, format)\\n\\t\\ttip = self.formats[format]\\n\\t\\theader_text = self.__header(format, tip)\\n\\t\\thow_to = blockquote(tip.escaped)\\n\\t\\tfooter_text = self.__footer(format)\\n\\t\\treturn f\\\"{header_text}\\\\n\\\\n{how_to}\\\\n\\\\n{footer_text}\\\"\",\n \"def iter_format(nitems, testobj='ndarray'):\\n for t in iter_mode(nitems, testobj):\\n yield t\\n if testobj != 'ndarray':\\n return\\n yield struct_items(nitems, testobj)\",\n \"def iter_format(nitems, testobj='ndarray'):\\n for t in iter_mode(nitems, testobj):\\n yield t\\n if testobj != 'ndarray':\\n return\\n yield struct_items(nitems, testobj)\",\n \"def test_basic(self):\\r\\n self.validate((3, 2, 8, 8), (4, 2, 5, 5), 'valid', verify_grad=False)\\r\\n self.validate((3, 2, 7, 5), (5, 2, 2, 3), 'valid')\\r\\n self.validate((3, 2, 7, 5), (5, 2, 3, 2), 'valid', verify_grad=False)\\r\\n self.validate((3, 2, 8, 8), (4, 2, 5, 5), 'full', verify_grad=False)\\r\\n self.validate((3, 2, 7, 5), (5, 2, 2, 3), 'full')\\r\\n # test filter same size as input\\r\",\n \"def test_duplicate_manual_position_arguments():\\n '{0} {1} {0}'.format(1, 2)\\n '{0} {1} {0}'.format(1)\",\n \"def data_format(self):\\n # Run without arguments\\n if len(sys.argv) == 1:\\n sys.exit(usage(None))\\n # Test input file argument\\n if self.input and not os.path.isfile(self.input):\\n print(self.input)\\n print(os.path.isfile(self.input))\",\n \"def info(capsys, format_str, format_args=None):\\n\\n if format_args is not None:\\n msg = (format_str % format_args)\\n else:\\n msg = format_str\\n\\n with capsys.disabled():\\n print(msg)\",\n \"def test_function_output(self):\\n \\n for integer, stringValue in self.knownIfPrime: # Check each tuple in knownIfPrime\\n result = fizzbuzz_correct.fizzbuzz(integer)\\n \\n self.assertEquals(stringValue, result, \\\"This doesn't seem to work with %d\\\" % (integer))\",\n \"def check_all(self, output_information=True):\\r\\n self.check_balance(output_information)\\r\\n self.check_color(output_information)\",\n \"def test_format_taxa_summary(self):\\r\\n # More than one sample.\\r\\n taxa_summary = (['Even7', 'Even8'], ['Eukarya'], array([[1.0, 1.0]]))\\r\\n exp = 'Taxon\\\\tEven7\\\\tEven8\\\\nEukarya\\\\t1.0\\\\t1.0\\\\n'\\r\\n obs = format_taxa_summary(taxa_summary)\\r\\n self.assertEqual(obs, exp)\\r\\n\\r\\n # More than one taxon.\\r\\n taxa_summary = (['Expected'], ['Eukarya', 'Bacteria', 'Archaea'],\\r\\n array([[0.5], [0.6], [0.4]]))\\r\\n exp = 'Taxon\\\\tExpected\\\\nEukarya\\\\t0.5\\\\nBacteria\\\\t0.6\\\\nArchaea\\\\t0.4\\\\n'\\r\\n obs = format_taxa_summary(taxa_summary)\\r\\n self.assertEqual(obs, exp)\",\n \"def test_print_info(clarisse):\\n info = \\\"test print info\\\"\\n assert bool(clarisse.print_info(info)) is False\",\n \"def _info(self, N):\\n IDs = self.chemicals.IDs\\n data = self.data\\n IDs, data = nonzeros(IDs, data)\\n N_IDs = len(IDs)\\n if N_IDs == 0:\\n return f\\\"{type(self).__name__}: (empty)\\\"\\n elif self.units:\\n basic_info = f\\\"{type(self).__name__} ({self.units}):\\\\n\\\"\\n else:\\n basic_info = f\\\"{type(self).__name__}:\\\\n\\\"\\n beginning = f'({self.phase}) ' if self.phase else \\\" \\\"\\n new_line = '\\\\n' + len(beginning) * ' '\\n data_info = ''\\n lengths = [len(i) for i in IDs]\\n maxlen = max(lengths) + 1\\n N_max = N or tmo.Stream.display_units.N\\n too_many_chemicals = N_IDs > N_max\\n N = N_max if too_many_chemicals else N_IDs\\n for i in range(N):\\n spaces = ' ' * (maxlen - lengths[i])\\n if i != 0:\\n data_info += new_line\\n data_info += IDs[i] + spaces + f' {data[i]:.3g}'\\n if too_many_chemicals:\\n data_info += new_line + '...'\\n return (basic_info\\n + beginning\\n + data_info)\",\n \"def test_format_throughput_for_two_inputs(self):\\n actual = format_throughput(20, 10)\\n self.assertEqual(actual, \\\"10/20 (50%)\\\")\",\n \"async def test_expanded_user_infraction_counts_returns_correct_strings(self):\\n test_values = (\\n {\\n \\\"api response\\\": [],\\n \\\"expected_lines\\\": [\\\"No infractions\\\"],\\n },\\n # Shows non-hidden inactive infraction as expected\\n {\\n \\\"api response\\\": [{\\\"type\\\": \\\"kick\\\", \\\"active\\\": False, \\\"hidden\\\": False}],\\n \\\"expected_lines\\\": [\\\"Kicks: 1\\\"],\\n },\\n # Shows non-hidden active infraction as expected\\n {\\n \\\"api response\\\": [{\\\"type\\\": \\\"mute\\\", \\\"active\\\": True, \\\"hidden\\\": False}],\\n \\\"expected_lines\\\": [\\\"Mutes: 1 (1 active)\\\"],\\n },\\n # Shows hidden inactive infraction as expected\\n {\\n \\\"api response\\\": [{\\\"type\\\": \\\"superstar\\\", \\\"active\\\": False, \\\"hidden\\\": True}],\\n \\\"expected_lines\\\": [\\\"Superstars: 1\\\"],\\n },\\n # Shows hidden active infraction as expected\\n {\\n \\\"api response\\\": [{\\\"type\\\": \\\"ban\\\", \\\"active\\\": True, \\\"hidden\\\": True}],\\n \\\"expected_lines\\\": [\\\"Bans: 1 (1 active)\\\"],\\n },\\n # Correctly displays tally of multiple infractions of mixed properties in alphabetical order\\n {\\n \\\"api response\\\": [\\n {\\\"type\\\": \\\"kick\\\", \\\"active\\\": False, \\\"hidden\\\": True},\\n {\\\"type\\\": \\\"ban\\\", \\\"active\\\": True, \\\"hidden\\\": True},\\n {\\\"type\\\": \\\"superstar\\\", \\\"active\\\": True, \\\"hidden\\\": True},\\n {\\\"type\\\": \\\"mute\\\", \\\"active\\\": True, \\\"hidden\\\": True},\\n {\\\"type\\\": \\\"ban\\\", \\\"active\\\": False, \\\"hidden\\\": False},\\n {\\\"type\\\": \\\"note\\\", \\\"active\\\": False, \\\"hidden\\\": True},\\n {\\\"type\\\": \\\"note\\\", \\\"active\\\": False, \\\"hidden\\\": True},\\n {\\\"type\\\": \\\"warn\\\", \\\"active\\\": False, \\\"hidden\\\": False},\\n {\\\"type\\\": \\\"note\\\", \\\"active\\\": False, \\\"hidden\\\": True},\\n ],\\n \\\"expected_lines\\\": [\\n \\\"Bans: 2 (1 active)\\\",\\n \\\"Kicks: 1\\\",\\n \\\"Mutes: 1 (1 active)\\\",\\n \\\"Notes: 3\\\",\\n \\\"Superstars: 1 (1 active)\\\",\\n \\\"Warns: 1\\\",\\n ],\\n },\\n )\\n\\n header = \\\"Infractions\\\"\\n\\n await self._method_subtests(self.cog.expanded_user_infraction_counts, test_values, header)\",\n \"def test_headless_tabulate_format():\\n formatter = TabularOutputFormatter(format_name=\\\"minimal\\\")\\n headers = [\\\"text\\\", \\\"numeric\\\"]\\n data = [[\\\"a\\\"], [\\\"b\\\"], [\\\"c\\\"]]\\n expected = \\\"a\\\\nb\\\\nc\\\"\\n assert expected == \\\"\\\\n\\\".join(\\n TabularOutputFormatter().format_output(\\n iter(data),\\n headers,\\n format_name=\\\"minimal\\\",\\n )\\n )\",\n \"def print_full(self):# pragma: no cover\\n print('Will now print all optional output arrays - ')\\n print(' yint_seg: ')\\n print((self.yint_seg))\\n print(' ')\\n print(' slope_seg: ')\\n print(self.slope_seg)\\n print(' ')\\n print(' sigyint_seg: ')\\n print(self.sigyint_seg)\\n print(' ')\\n print(' sigslope_seg: ')\\n print(self.sigslope_seg)\\n print(' ')\\n print(' inv_var_2d: ')\\n print((self.inv_var_2d))\\n print(' ')\\n print(' firstf_int: ')\\n print((self.firstf_int))\\n print(' ')\\n print(' ped_int: ')\\n print((self.ped_int))\\n print(' ')\\n print(' cr_mag_seg: ')\\n print((self.cr_mag_seg))\",\n \"def complete_opt_format(self, text, *_):\\n return [t + \\\" \\\" for t in FORMATTERS if t.startswith(text)]\",\n \"def test_formatResult(self):\\r\\n x = self.FWP({'x': 3})\\r\\n self.assertEqual(x.formatResult(3), '3')\",\n \"def test_basics(key_formats, template, expected, fields, errors):\\n\\n format_product = FormatTemplate(key_formats=key_formats)\\n statement = partial(format_product, template, **fields)\\n\\n if errors is None:\\n result = statement()\\n assert result == expected\\n else:\\n with pytest.raises(errors):\\n result = statement()\",\n \"def test_make_sampled_format(self):\\n for num_inputs in [1, 3]:\\n for num_outputs in [1, 2, 4]:\\n for num_time_steps in [4, 10, 12]:\\n # Generate data\\n # P=2 format [0, 1, 2, 3, ...]\\n sample_interval = 2\\n dt_system = np.random.random()\\n dt_sample = sample_interval * dt_system\\n outputs = np.random.random(\\n (num_time_steps, num_outputs, num_inputs))\\n time_steps = make_time_steps(\\n num_time_steps, sample_interval)\\n time_values = time_steps * dt_system\\n\\n # Compute using modred\\n my_ERA = era.ERA()\\n time_steps_computed, outputs_computed =\\\\\\n era.make_sampled_format(time_values, outputs)\\n #self.assertEqual(dt_system_computed, dt_system)\\n\\n # Reference values\\n num_time_steps_true = (num_time_steps - 1) * 2\\n time_steps_true = make_time_steps(num_time_steps_true, 1)\\n outputs_true = np.zeros(\\n (num_time_steps_true, num_outputs, num_inputs))\\n outputs_true[::2] = outputs[:-1]\\n outputs_true[1::2] = outputs[1:]\\n\\n # Compare values\\n np.testing.assert_equal(\\n time_steps_computed, time_steps_true)\\n np.testing.assert_equal(outputs_computed, outputs_true)\\n\\n # Test that if there is a wrong time value, get an error\\n time_values[num_time_steps // 2] = -1\\n self.assertRaises(\\n ValueError, era.make_sampled_format, time_values,\\n outputs)\",\n \"def test_all_pairs_t_test(self):\\r\\n # We aren't testing the numeric values here, as they've already been\\r\\n # tested in the functions that compute them. We are interested in the\\r\\n # format of the returned string.\\r\\n exp = \\\"\\\"\\\"# The tests of significance were performed using a two-sided Student's two-sample t-test.\\r\\n# Alternative hypothesis: Group 1 mean != Group 2 mean\\r\\n# The nonparametric p-values were calculated using 999 Monte Carlo permutations.\\r\\n# The nonparametric p-values contain the correct number of significant digits.\\r\\n# Entries marked with \\\"N/A\\\" could not be calculated because at least one of the groups\\r\\n# of distances was empty, both groups each contained only a single distance, or\\r\\n# the test could not be performed (e.g. no variance in groups with the same mean).\\r\\nGroup 1\\tGroup 2\\tt statistic\\tParametric p-value\\tParametric p-value (Bonferroni-corrected)\\tNonparametric p-value\\tNonparametric p-value (Bonferroni-corrected)\\r\\nfoo\\tbar\\t-6.6\\t0.00708047956412\\t0.0212414386924\\t0.095\\t0.285\\r\\nfoo\\tbaz\\t-9.79795897113\\t0.000608184944463\\t0.00182455483339\\t0.101\\t0.303\\r\\nbar\\tbaz\\t-3.0\\t0.0576688856224\\t0.173006656867\\t0.217\\t0.651\\r\\n\\\"\\\"\\\"\\r\\n obs = all_pairs_t_test(self.labels2, self.dists2)\\r\\n self.assertEqual(self.remove_nums(obs), self.remove_nums(exp))\",\n \"def test_format_phone_formatted(self):\\n number1 = '809.555.1234'\\n self.assertEqual(format_phone(number1), '(809) 555-1234')\\n number2 = '(888) 555-3456'\\n self.assertEqual(format_phone(number2), '(888) 555-3456')\",\n \"def extract_format_results_test(self):\\n assert len(self.results.keys()) != 0\\n TESTS = [\\n {\\n \\\"output\\\": [\\n {\\n \\\"file_name\\\": \\\"BSA1.mzML\\\",\\n \\\"spec_id\\\": 1337,\\n \\\"formula\\\": \\\"C(37)H(59)N(9)O(16)\\\",\\n \\\"scaling_factor\\\": 100,\\n \\\"score\\\": 1,\\n \\\"charge\\\": 2,\\n },\\n {\\n \\\"file_name\\\": \\\"BSA1.mzML\\\",\\n \\\"spec_id\\\": 1338,\\n \\\"formula\\\": \\\"C(37)H(59)N(9)O(16)\\\",\\n \\\"scaling_factor\\\": 100,\\n \\\"score\\\": 0.9,\\n \\\"charge\\\": 2,\\n },\\n {\\n \\\"file_name\\\": \\\"BSA2.mzML\\\",\\n \\\"spec_id\\\": 1337,\\n \\\"formula\\\": \\\"C(43)H(75)N(15)O(17)S(2)\\\",\\n \\\"scaling_factor\\\": 10,\\n \\\"score\\\": 1,\\n \\\"charge\\\": 3,\\n },\\n ]\\n }\\n ]\\n for test_dict in TESTS:\\n values = self.results.format_all_results()\\n\\n assert isinstance(values, pd.DataFrame)\\n\\n for out_data in test_dict[\\\"output\\\"]:\\n result = values.loc[\\n (values[\\\"file_name\\\"] == out_data[\\\"file_name\\\"])\\n & (values[\\\"spec_id\\\"] == out_data[\\\"spec_id\\\"])\\n ]\\n assert (result[\\\"formula\\\"] == out_data[\\\"formula\\\"]).all()\\n assert (result[\\\"scaling_factor\\\"] == out_data[\\\"scaling_factor\\\"]).all()\\n assert (result[\\\"score\\\"] == out_data[\\\"score\\\"]).all()\\n assert (result[\\\"charge\\\"] == out_data[\\\"charge\\\"]).all()\",\n \"def _does_output_dict_contain_info(self):\\n for species_output_dict in self.output.values():\\n for key0, val0 in species_output_dict.items():\\n if key0 in ['paths', 'job_types']:\\n for key1, val1 in species_output_dict[key0].items():\\n if val1 and key1 not in ['rotors', 'bde']:\\n return True\\n else:\\n if val0:\\n return True\\n return False\",\n \"def test_print_result(capsys):\\n assert \\\"\\\"\\\"Total 5 hands solved\\nTotal 4 hands solved with hint\\nTotal 4 hands failed to solve\\\"\\\"\\\" in hl.test_help_print_result(capsys)\",\n \"def test_CLINTOX_2_erroneous_data_INFO_structural(self, mock_print):\\n Plotter.from_smiles(self.data_CLINTOX_2_erroneous_smiles[\\\"smiles\\\"], target=self.data_CLINTOX_2_erroneous_smiles[\\\"target\\\"], target_type=\\\"C\\\", sim_type=\\\"structural\\\")\\n mock_print.assert_called_once_with('The following erroneous SMILES have been found in the data:\\\\n[NH4][Pt]([NH4])(Cl)Cl\\\\nc1ccc(cc1)n2c(=O)c(c(=O)n2c3ccccc3)CCS(=O)c4ccccc4\\\\nCc1cc2c(cc1C)N3C=N2[Co+]456(N7=C8[C@H](C(C7=CC9=N4C(=C(C1=N5[C@@]([C@@H]2N6C(=C8C)[C@@]([C@H]2CC(=O)N)(CCC(=O)NC[C@H](OP(=O)(O[C@@H]2[C@H](O[C@H]3[C@@H]2O)CO)[O-])C)C)([C@@]([C@@H]1CCC(=O)N)(C)CC(=O)N)C)C)[C@@]([C@@H]9CCC(=O)N)(C)CC(=O)N)(C)C)CCC(=O)N)O\\\\n' + \\n 'Cc1cc2c(cc1C)N3C=N2[Co]456(N7=C8[C@H](C(C7=CC9=N4C(=C(C1=N5[C@@]([C@@H]2N6C(=C8C)[C@@]([C@H]2CC(=O)N)(CCC(=O)NC[C@H](OP(=O)(O[C@@H]2[C@H](O[C@H]3[C@@H]2O)CO)O)C)C)([C@@]([C@@H]1CCC(=O)N)(C)CC(=O)N)C)C)[C@@]([C@@H]9CCC(=O)N)(C)CC(=O)N)(C)C)CCC(=O)N)C#N\\\\n'+\\n 'CCCCc1c(=O)n(n(c1=O)c2ccc(cc2)O)c3ccccc3\\\\nCCCCc1c(=O)n(n(c1=O)c2ccccc2)c3ccccc3.\\\\n' +\\n 'The erroneous SMILES will be removed from the data.')\",\n \"def format_comparison(objs):\\n def formatter(comp):\\n if not isinstance(comp, tuple):\\n return str(comp)\\n output = []\\n return \\\"\\\\n\\\".join([comp.type] + [\\\" \\\"+errmessage for errmessage in output])\\n\\n results = map(formatter,objs)\\n return \\\"\\\\n\\\".join(results)\\n \\n #obj1,obj2 = comp\\n\\n\\n ### Sections\\n #for i,s1,s2 in diffs:\\n # if s1 and s2:\\n # output.append(f\\\"Section {i} does not match:\\\")\\n # result = compare_sections(s1,s2)\\n # output.extend(almethods.linepadder(result))\\n # else:\\n # if s1:\\n # output.append(f\\\"Door 2 missing Section {i}\\\")\\n # else:\\n # output.append(f\\\"Door 1 missing Section {i}\\\")\",\n \"def test_available_input_formats():\\n assert set([\\\"Mapchete\\\", \\\"raster_file\\\", \\\"vector_file\\\"]).issubset(\\n set(available_input_formats())\\n )\",\n \"def test_output(self):\\n good_value_pairs = STR_VALUE_PAIRS\\n for pair in good_value_pairs:\\n output = to_cardinal_trio(pair[0])\\n self.assertEqual(output, pair[1],\\n f\\\"{pair[0]} should be {pair[1]}, not {output}\\\")\",\n \"def test_get_info(self):\\n pass\",\n \"def test_unsupported_format():\\n formatter = TabularOutputFormatter()\\n\\n with pytest.raises(ValueError):\\n formatter.format_name = \\\"foobar\\\"\\n\\n with pytest.raises(ValueError):\\n formatter.format_output((), (), format_name=\\\"foobar\\\")\",\n \"def test_full_mode(self):\\r\\n self.validate((3, 2, 5, 5), (4, 2, 8, 8), 'full')\\r\\n\\r\\n def f():\\r\\n self.validate((3, 2, 5, 5), (4, 2, 8, 8), 'valid')\\r\\n self.assertRaises(Exception, f)\",\n \"def test_get_cell_info(self):\\n expected = { 'Experiment': \\\"20220101_EGS1_12345AA\\\",\\n 'Cell': '12345AA0018/20220101_1234_1-A1-A1_AAA66666_deadbeef',\\n 'Pool': '12345AA0018',\\n 'Date': '20220101',\\n 'Number': '1234',\\n 'Slot': '1-A1-A1',\\n 'CellID': 'AAA66666',\\n 'Checksum': 'deadbeef',\\n 'Project': '12345',\\n 'Base': '12345AA0018/20220101_1234_1-A1-A1_AAA66666_deadbeef/'\\n '20220101_EGS1_12345AA_12345AA0018_AAA66666_deadbeef',\\n 'Files in pass': 'unknown',\\n 'Files in fail': 1,\\n 'Files in fast5 fail': 1,\\n '_counts': [\\n {'_barcode': '.', '_label': 'All passed reads', '_part': 'pass', 'total_reads': 200},\\n {'_barcode': '.', '_label': 'Passed and lambda-filtered reads', '_part': 'nolambda'},\\n {'_barcode': '.', '_label': 'All failed reads', '_part': 'fail'} ],\\n '_blobs': ['../../__blob__'],\\n '_duplex' : [ ['Duplex pairs', 1],\\n ['from total passing reads', 200],\\n ['% of passing reads', '1.00%'] ],\\n '_filter_type': 'none',\\n '_final_summary': {'is_rna': False},\\n '_nanoplot': '../../__nanoplot__',\\n }\\n\\n\\n got = get_cell_info( experiment = \\\"20220101_EGS1_12345AA\\\",\\n cell = \\\"12345AA0018/20220101_1234_1-A1-A1_AAA66666_deadbeef\\\",\\n cell_content = { '.': dict( fast5_pass = ['x.fast5'],\\n fastq_fail = ['y.fastq'],\\n fast5_fail = ['y.fast5'] ) },\\n counts = { ('.','pass'): dict(total_reads = 200),\\n ('.','fail'): dict(),\\n ('.','nolambda'): dict() },\\n fin_summary = dict(is_rna = False),\\n blobs = ['__blob__'],\\n nanoplot = '__nanoplot__',\\n duplex = 1,\\n fast5_meta = dict() )\\n\\n if VERBOSE:\\n pprint(got)\\n\\n self.assertEqual( type(got), OrderedDict )\\n self.assertEqual( dict(got), expected )\",\n \"def test_standardForm(self):\\n\\n a, b, t, M = self.cs.standardForm\\n self.assertEqual((a, b, t[0, 0], t[1, 0]), (1., 1., 0., 0.))\",\n \"def test_format_args(self):\\n for format_func, formatted in [(lambda: \\\"1\\\", \\\"1\\\"), (lambda: 2, 2), (lambda: \\\"foo\\\", \\\"foo\\\")]:\\n # These return values are used by TimeIt in order: start, end, start, end, ... So the first time the\\n # duration will be 1 second, then 2 seconds, and 3 seconds.\\n MockDatetimeNow.RETURN_VALUES = [datetime(1970, 1, 1, 0, 0, 0, 0),\\n datetime(1970, 1, 1, 0, 0, 1, 0),\\n datetime(1970, 1, 1, 0, 0, 0, 0),\\n datetime(1970, 1, 1, 0, 0, 2, 0),\\n datetime(1970, 1, 1, 0, 0, 0, 0),\\n datetime(1970, 1, 1, 0, 0, 3, 0)]\\n MockDatetimeNow.CURRENT_IDX = 0\\n with self.subTest(format_func=format_func), patch('mpire.utils.datetime', new=MockDatetimeNow):\\n cum_time_array = [0]\\n max_time_array = [(0, ''), (0, '')]\\n for _ in range(3):\\n with TimeIt(cum_time_array, 0, max_time_array, format_func):\\n pass\\n\\n # The heapq only had room for two entries. The highest durations should be kept\\n self.assertListEqual(max_time_array, [(2.0, formatted), (3.0, formatted)])\",\n \"def test_missing_info(self):\\r\\n self.validate(None, None,\\r\\n N_image_shape=(3, 2, 8, 8),\\r\\n N_filter_shape=(4, 2, 5, 5))\\r\\n self.validate((3, 2, None, None), None,\\r\\n N_image_shape=(3, 2, 8, 8),\\r\\n N_filter_shape=(4, 2, 5, 5))\\r\\n self.validate((None, 2, None, None), (None, 2, 5, 5),\\r\\n N_image_shape=(3, 2, 8, 8),\\r\\n N_filter_shape=(4, 2, 5, 5))\",\n \"def test_format_emperor_autograph(self):\\n\\n autograph = format_emperor_autograph('mapping_file.txt',\\n 'pcoa_unweighted_unifrac.txt')\\n\\n # check for comment open and comment close\\n self.assertTrue('<!--' in autograph)\\n self.assertTrue('-->' in autograph)\\n # check for fields since we cannot check for the specifics\\n self.assertTrue(\\\"*Summary of Emperor's Information*\\\" in autograph)\\n self.assertTrue('Metadata:' in autograph)\\n self.assertTrue('Coordinates:' in autograph)\\n self.assertTrue('HostName:' in autograph)\\n self.assertTrue(\\\"Command:\\\" in autograph)\\n self.assertTrue(\\\"Emperor Version: \\\" in autograph)\\n self.assertTrue(\\\"QIIME Version: \\\" in autograph)\\n self.assertTrue(\\\"Command executed on \\\" in autograph)\\n\\n autograph = format_emperor_autograph('mapping_file.txt',\\n 'pcoa_unweighted_unifrac.txt',\\n 'Python')\\n # check for comment open and comment close\\n self.assertTrue('\\\"\\\"\\\"' in autograph)\\n self.assertTrue('\\\"\\\"\\\"' in autograph)\\n # check for fields since we cannot check for the specifics\\n self.assertTrue(\\\"*Summary of Emperor's Information*\\\" in autograph)\\n self.assertTrue('Metadata:' in autograph)\\n self.assertTrue('Coordinates:' in autograph)\\n self.assertTrue('HostName:' in autograph)\\n self.assertTrue(\\\"Command:\\\" in autograph)\\n self.assertTrue(\\\"Emperor Version: \\\" in autograph)\\n self.assertTrue(\\\"QIIME Version: \\\" in autograph)\\n self.assertTrue(\\\"Command executed on \\\" in autograph)\\n\\n autograph = format_emperor_autograph('mapping_file.txt',\\n 'pcoa_unweighted_unifrac.txt',\\n 'C')\\n # check for comment open and comment close\\n self.assertTrue('/*' in autograph)\\n self.assertTrue('*/' in autograph)\\n # check for fields since we cannot check for the specifics\\n self.assertTrue(\\\"*Summary of Emperor's Information*\\\" in autograph)\\n self.assertTrue('Metadata:' in autograph)\\n self.assertTrue('Coordinates:' in autograph)\\n self.assertTrue('HostName:' in autograph)\\n self.assertTrue(\\\"Command:\\\" in autograph)\\n self.assertTrue(\\\"Emperor Version: \\\" in autograph)\\n self.assertTrue(\\\"QIIME Version: \\\" in autograph)\\n self.assertTrue(\\\"Command executed on \\\" in autograph)\\n\\n autograph = format_emperor_autograph('mapping_file.txt',\\n 'pcoa_unweighted_unifrac.txt',\\n 'Bash')\\n # check for comment open and comment close\\n self.assertTrue('<<COMMENT' in autograph)\\n self.assertTrue('COMMENT' in autograph)\\n # check for fields since we cannot check for the specifics\\n self.assertTrue(\\\"*Summary of Emperor's Information*\\\" in autograph)\\n self.assertTrue('Metadata:' in autograph)\\n self.assertTrue('Coordinates:' in autograph)\\n self.assertTrue('HostName:' in autograph)\\n self.assertTrue(\\\"Command:\\\" in autograph)\\n self.assertTrue(\\\"Emperor Version: \\\" in autograph)\\n self.assertTrue(\\\"QIIME Version: \\\" in autograph)\\n self.assertTrue(\\\"Command executed on \\\" in autograph)\\n\\n # haskell and cobol are ... not supported\\n self.assertRaises(AssertionError, format_emperor_autograph,\\n 'mapping_file.txt', 'pcoa.txt', 'Haskell')\\n self.assertRaises(AssertionError, format_emperor_autograph,\\n 'mapping_file.txt', 'pcoa.txt', 'Cobol')\",\n \"def _build_summary(\\n val1: str | None = None, val2: str | None = None, val3: str | None = None\\n ) -> str:\\n return ' : '.join([value for value in [val1, val2, val3] if value is not None])\",\n \"def print(self, failed_tests=True, passed_tests=True, json_format=False):\\n # TODO: Do we need the json option?\\n if json_format:\\n passed = self.passed\\n if (passed and passed_tests) or (not passed and failed_tests):\\n print(json.dumps(self, indent=4, cls=MyEncoder))\\n else:\\n separator = \\\"\\\"\\n\\n filtered_output = \\\"\\\"\\n passed = self.passed\\n if passed and passed_tests:\\n filtered_output += \\\"Parser Name = {}\\\\n\\\".format(self.parser)\\n if self.input_file_path and self.input_file_path != \\\"N/A\\\":\\n filtered_output += \\\"Input Filename = {}\\\\n\\\".format(self.input_file_path)\\n filtered_output += \\\"Tests Passed = {}\\\\n\\\".format(self.passed)\\n elif not passed and failed_tests:\\n filtered_output += \\\"Parser Name = {}\\\\n\\\".format(self.parser)\\n if self.input_file_path and self.input_file_path != \\\"N/A\\\":\\n filtered_output += \\\"Input Filename = {}\\\\n\\\".format(self.input_file_path)\\n filtered_output += \\\"Tests Passed = {}\\\\n\\\".format(self.passed)\\n filtered_output += \\\"Errors = {}\\\".format(\\\"\\\\n\\\" if self.errors else \\\"None\\\\n\\\")\\n if self.errors:\\n for entry in self.errors:\\n filtered_output += \\\"\\\\t{0}\\\\n\\\".format(entry)\\n filtered_output += \\\"Debug Logs = {}\\\".format(\\\"\\\\n\\\" if self.debug else \\\"None\\\\n\\\")\\n if self.debug:\\n for entry in self.debug:\\n filtered_output += \\\"\\\\t{0}\\\\n\\\".format(entry)\\n if self.results:\\n filtered_output += \\\"Results =\\\\n\\\"\\n for result in self.results:\\n if not result.passed:\\n filtered_output += \\\"{0}\\\\n\\\".format(result)\\n\\n if filtered_output:\\n filtered_output += \\\"{0}\\\\n\\\".format(separator)\\n print(filtered_output.encode(\\\"ascii\\\", \\\"backslashreplace\\\").decode())\",\n \"def match_info(info_dict):\\n return True\",\n \"def print_usage():\\n print 'USAGE: %s [options]' % os.path.abspath(__file__)\\n print 'EXAMPLE1: %s # FOR DEFAULTS' % os.path.abspath(__file__)\\n print 'EXAMPLE2: %s 121f03=tweek hirap=towelie details=False # TWO SMALL SETS' % os.path.abspath(__file__)\\n print 'EXAMPLE3: %s 121f03=tweek details=True # ONE DETAILED SET' % os.path.abspath(__file__)\\n print 'EXAMPLE4: %s details=True # SHOWS MAX INFO' % os.path.abspath(__file__)\",\n \"def formatted_locator_information(self):\\n info = 'May not follow-up.'\\n if self.may_follow_up == 'Yes':\\n info = (\\n '{may_sms_follow_up}\\\\n'\\n 'Cell: {subject_cell} {alt_subject_cell}\\\\n'\\n 'Phone: {subject_phone} {alt_subject_phone}\\\\n'\\n '').format(\\n may_sms_follow_up='SMS permitted' if self.may_sms_follow_up == 'Yes' else 'NO SMS!',\\n subject_cell='{} (primary)'.format(self.subject_cell) if self.subject_cell else '(none)',\\n alt_subject_cell=self.subject_cell_alt,\\n subject_phone=self.subject_phone or '(none)', alt_subject_phone=self.subject_phone_alt\\n )\\n if self.may_call_work == 'Yes':\\n info = (\\n '{info}\\\\n Work Contacts:\\\\n'\\n '{subject_work_place}\\\\n'\\n 'Work Phone: {subject_work_phone}\\\\n'\\n '').format(\\n info=info,\\n subject_work_place=self.subject_work_place or '(work place not known)',\\n subject_work_phone=self.subject_work_phone)\\n if self.may_contact_someone == 'Yes':\\n info = (\\n '{info}\\\\n Contacts of someone else:\\\\n'\\n '{contact_name} - {contact_rel}\\\\n'\\n '{contact_cell} (cell), {contact_phone} (phone)\\\\n'\\n '').format(\\n info=info,\\n contact_name=self.contact_name or '(name?)',\\n contact_rel=self.contact_rel or '(relation?)',\\n contact_cell=self.contact_cell or '(----)',\\n contact_phone=self.contact_phone or '(----)'\\n )\\n if info:\\n info = ('{info}'\\n 'Physical Address:\\\\n{physical_address}').format(\\n info=info, physical_address=self.physical_address)\\n return info\",\n \"def test_plain_flat_yaml(\\n before_yaml_flat: str,\\n after_yaml_flat: str,\\n plain_flat_res: str,\\n):\\n assert gendiff(\\n before_yaml_flat,\\n after_yaml_flat,\\n form=PLAIN_FORMAT,\\n ) == plain_flat_res\",\n \"def info() -> None:\",\n \"def test_str_fac():\\n structure = Material(input)\\n assert (np.abs(structure.calc_nuc_str_fac((2., 0., 0.))) ** 2 - 1702170.4663405998 < 1e-6)\\n assert (np.abs(structure.calc_nuc_str_fac((2, 0, 0))) ** 2 - 1702170.4663405998 < 1e-6)\\n assert (np.abs(structure.calc_nuc_str_fac((0, 2., 0))) ** 2 - 1702170.4663405998 < 1e-6)\\n assert (np.abs(structure.calc_nuc_str_fac((0, 2, 0))) ** 2 - 1702170.4663405998 < 1e-6)\\n\\n ndarray_example = np.linspace(0.5, 1.5, 21)\\n assert (np.sum(abs(structure.calc_nuc_str_fac((ndarray_example, 0, 0))) ** 2) - 7058726.6759794801 < 1e-6)\\n assert (np.sum(abs(structure.calc_nuc_str_fac((0, ndarray_example, 0))) ** 2) - 7058726.6759794801 < 1e-6)\\n assert (np.sum(abs(structure.calc_nuc_str_fac((0, 0, ndarray_example))) ** 2) - 16831011.814390473 < 1e-6)\\n assert (\\n np.sum(abs(structure.calc_nuc_str_fac((ndarray_example, ndarray_example, 0))) ** 2) - 10616602.544519115 < 1e-6)\\n\\n list_example = list(ndarray_example)\\n assert (np.sum(abs(structure.calc_nuc_str_fac((list_example, 0, 0))) ** 2) - 7058726.6759794801 < 1e-6)\\n assert (np.sum(abs(structure.calc_nuc_str_fac((0, list_example, 0))) ** 2) - 7058726.6759794801 < 1e-6)\\n assert (np.sum(abs(structure.calc_nuc_str_fac((0, 0, list_example))) ** 2) - 16831011.814390473 < 1e-6)\\n\\n tuple_example = tuple(ndarray_example)\\n assert (np.sum(abs(structure.calc_nuc_str_fac((tuple_example, 0, 0))) ** 2) - 7058726.6759794801 < 1e-6)\\n assert (np.sum(abs(structure.calc_nuc_str_fac((0, tuple_example, 0))) ** 2) - 7058726.6759794801 < 1e-6)\\n assert (np.sum(abs(structure.calc_nuc_str_fac((0, 0, tuple_example))) ** 2) - 16831011.814390473 < 1e-6)\",\n \"def test_output(self):\\n good_value_pairs = INT_VALUE_PAIRS\\n for pair in good_value_pairs:\\n output = to_cardinal_number(pair[0])\\n self.assertEqual(output, pair[1],\\n f\\\"{pair[0]} should be {pair[1]}, not {output}\\\")\",\n \"def getopt_format(self):\\n self._print_enum_opt(\\\"format\\\", FORMATTERS)\",\n \"def test_major_pretty_table(self) -> None:\\n rep:Repository = Repository(r\\\"C:\\\\Users\\\\harsh\\\\OneDrive\\\\Desktop\\\\My Files\\\\Assignment\\\")\\n expected: Dict[str] = {\\n 'SFEN': ['SFEN', ['SSW 540', 'SSW 555', 'SSW 810'], ['CS 501', 'CS 546']],\\n 'CS': ['CS', ['CS 546', 'CS 570'], ['SSW 565', 'SSW 810']]\\n }\\n \\n res = {m: mj.major_info() for m, mj in rep._majors.items()}\\n \\n self.assertEqual(expected, res)\",\n \"def check_and_print_if_error(self): # pragma: no cover\\n dupes, empties, not_detected = self._get_aberrations()\\n if dupes:\\n print 'duplicate entries for:'\\n for dup, matches in dupes:\\n print ' %s: %s' % (dup, [f.func_name for f in matches])\\n if empties:\\n print 'empty entries for:'\\n for empty in empties:\\n print ' ' + str(empty)\\n if not_detected:\\n print 'dimensions not detected:'\\n for n_d in not_detected:\\n print ' ' + str(n_d)\\n return self.is_correct\",\n \"def _processOutfmtArg(outfmt, stderr, gb_record_fmtdict, gb_cds_fmtdict) :\\n outfmt_keys = outfmt.split(\\\",\\\")\\n records_keys = set(gb_record_fmtdict.keys())\\n cds_keys = set(gb_cds_fmtdict.keys())\\n assert records_keys & cds_keys == set()\\n if not all([x in records_keys | cds_keys for x in outfmt_keys]) :\\n wrong_keys = [x for x in outfmt_keys if x not in records_keys | cds_keys]\\n stderr.write(\\\"Bad outfmt specifier. You provided:\\\\n\\\")\\n stderr.write(str(sorted(outfmt_keys)) + \\\"\\\\n\\\")\\n stderr.write(\\\"Wrong specifier(s):\\\\n\\\")\\n stderr.write(str(sorted(wrong_keys)) + \\\"\\\\n\\\")\\n stderr.write(\\\"Allowed values are:\\\\n\\\")\\n stderr.write(str(sorted(list(records_keys | cds_keys))) + \\\"\\\\n\\\")\\n return outfmt_keys\",\n \"def test_context_data_info_message_for_multiple_result(self):\\n factories.SourceTraitFactory.create(\\n i_description='lorem ipsum',\\n source_dataset__source_study_version__study=self.study)\\n factories.SourceTraitFactory.create(\\n i_description='lorem ipsum 2',\\n source_dataset__source_study_version__study=self.study)\\n response = self.client.get(self.get_url(self.study.pk), {'description': 'lorem'})\\n messages = list(response.wsgi_request._messages)\\n self.assertEqual(len(messages), 1)\\n self.assertEqual(str(messages[0]), '2 results found.')\",\n \"def report_full(*args, **kwargs): # real signature unknown\\n pass\",\n \"def missing_info(**kwargs) -> str:\\n func = kwargs.pop('func', 'unknown')\\n if 'ticker' in kwargs: kwargs['ticker'] = kwargs['ticker'].replace('/', '_')\\n for dt in ['dt', 'start_dt', 'end_dt', 'start_date', 'end_date']:\\n if dt not in kwargs: continue\\n kwargs[dt] = utils.fmt_dt(kwargs[dt])\\n info = utils.to_str(kwargs, fmt='{value}', sep='/')[1:-1]\\n return f'{func}/{info}'\",\n \"def info(obj):\\n if obj is None:\\n return 'None.'\\n elif isinstance(obj, list):\\n if obj:\\n return 'List of %d... %s' % (len(obj), info(obj[0]))\\n else:\\n return 'Empty list.'\\n elif isinstance(obj, tuple):\\n if obj:\\n return 'Tuple of %d... %s' % (len(obj), info(obj[0]))\\n else:\\n return 'Empty tuple.'\\n else:\\n if is_a_numpy_array(obj):\\n return 'Array with shape: %s, dtype: %s' % (obj.shape, obj.dtype)\\n else:\\n return str(obj)\",\n \"def info_to_fits(obs_info: ObservationInfo) -> tuple[dict[str, Any], dict[str, str]]:\\n cards = {}\\n comments = {}\\n\\n if obs_info.instrument is not None:\\n cards[\\\"INSTRUME\\\"] = obs_info.instrument\\n comments[\\\"INSTRUME\\\"] = \\\"Name of instrument\\\"\\n\\n cards.update(dates_to_fits(obs_info.datetime_begin, obs_info.datetime_end))\\n\\n return cards, comments\",\n \"def show_help():\\n messagebox.showinfo('Data entering', \\\"\\\"\\\"\\n Enter equal arrays of x and y values\\n Separate values with space < >, tab < > or coma <,>\\n Separate fraction using dot <.>\\n \\\"\\\"\\\")\",\n \"def getInfo(self, formatted=False):\\n\\n\\t\\tinfo = {}\\n\\t\\tinfo['Python'] = \\\"%d.%d.%d\\\" %(sys.version_info[0], sys.version_info[1], sys.version_info[2])\\n\\t\\tinfo[__binding__] = __binding_version__\\n\\t\\tinfo['Qt'] = QtCore.qVersion()\\n\\t\\tinfo['OS'] = platform.system()\\n\\t\\tinfo['Environment'] = HOST\\n\\n\\t\\tif formatted:\\n\\t\\t\\tinfo_ls = []\\n\\t\\t\\tfor key, value in info.items():\\n\\t\\t\\t\\tinfo_ls.append(\\\"{} {}\\\".format(key, value))\\n\\t\\t\\tinfo_str = \\\" | \\\".join(info_ls)\\n\\t\\t\\treturn info_str\\n\\n\\t\\telse:\\n\\t\\t\\treturn info\",\n \"def print_exact_res():\\n\\n print(\\\"************************************************************\\\")\\n print(\\\"EXACT RESULT FOR THE VALUES THAT MINIMIZE THE FUNCTION:\\\\n\\\")\\n f_str = \\\"The value of x_{:d} is {:f}\\\"\\n for i in range(1, cfg.n + 1):\\n print(f_str.format(i, float(i)))\\n print(\\\"************************************************************\\\\n\\\")\",\n \"def test_workload_get_command_human_readable(\\n workload_get_success, workload_get_success_hr\\n):\\n hr_output = prepare_workload_get_output(workload_get_success)\\n assert hr_output == workload_get_success_hr\",\n \"def test_validate_fasta(self):\\r\\n\\r\\n validate_fasta(self.sample_fasta_fp, self.sample_mapping_fp,\\r\\n self.output_dir)\\r\\n\\r\\n expected_log_fp = join(self.output_dir,\\r\\n split(self.sample_fasta_fp)[1] + \\\"_report.log\\\")\\r\\n\\r\\n log_f = open(expected_log_fp, \\\"U\\\")\\r\\n actual_log_lines = [line.strip() for line in log_f][1:]\\r\\n\\r\\n expected_log_lines = \\\"\\\"\\\"Percent duplicate labels: 0.000\\r\\nPercent QIIME-incompatible fasta labels: 0.000\\r\\nPercent of labels that fail to map to SampleIDs: 0.000\\r\\nPercent of sequences with invalid characters: 0.000\\r\\nPercent of sequences with barcodes detected: 0.000\\r\\nPercent of sequences with barcodes detected at the beginning of the sequence: 0.000\\r\\nPercent of sequences with primers detected: 0.000\\\"\\\"\\\".split('\\\\n')\\r\\n\\r\\n self.assertEqual(actual_log_lines, expected_log_lines)\\r\\n\\r\\n # Check with all optional values included\\r\\n\\r\\n validate_fasta(self.sample_fasta_fp, self.sample_mapping_fp,\\r\\n self.output_dir, tree_fp=self.sample_tree_5tips_fp, tree_subset=True,\\r\\n tree_exact_match=True, same_seq_lens=True, all_ids_found=True)\\r\\n\\r\\n expected_log_fp = join(self.output_dir,\\r\\n split(self.sample_fasta_fp)[1] + \\\"_report.log\\\")\\r\\n\\r\\n log_f = open(expected_log_fp, \\\"U\\\")\\r\\n actual_log_lines = [line.strip() for line in log_f][1:]\\r\\n\\r\\n expected_log_lines = \\\"\\\"\\\"Percent duplicate labels: 0.000\\r\\nPercent QIIME-incompatible fasta labels: 0.000\\r\\nPercent of labels that fail to map to SampleIDs: 0.000\\r\\nPercent of sequences with invalid characters: 0.000\\r\\nPercent of sequences with barcodes detected: 0.000\\r\\nPercent of sequences with barcodes detected at the beginning of the sequence: 0.000\\r\\nPercent of sequences with primers detected: 0.000\\r\\nSequence lengths report\\r\\nCounts of sequences, followed by their sequence lengths:\\r\\n1\\\\t35\\r\\n1\\\\t32\\r\\n1\\\\t27\\r\\nSample ID in fasta sequences report\\r\\nThe following SampleIDs were not found:\\r\\nseq2\\r\\nFasta label subset in tree tips report\\r\\nAll fasta labels were a subset of tree tips.\\r\\nFasta label/tree tip exact match report\\r\\nAll fasta labels found in tree tips.\\r\\nThe following tips were not in fasta labels:\\r\\nseq2\\r\\nseq5\\r\\nseq4\\\"\\\"\\\".split('\\\\n')\\r\\n\\r\\n self.assertEqual(actual_log_lines, expected_log_lines)\",\n \"def get_valid_output_format(self, idx, virt_format_list, explicit_format_list, specified_image_format):\\n output_image_format = \\\"\\\"\\n if self.debug_mode:\\n print \\\"\\\\nwanted output image format is: \\\" + str(specified_image_format)\\n if specified_image_format == \\\"VIRT\\\":\\n virt_image_format = virt_format_list[0][idx] #Should be reduced to a unique list now (so we can index by 0)\\n if self.debug_mode:\\n print \\\"output virt resulting image format is: \\\" + virt_image_format\\n output_image_format = virt_image_format.strip('VIRT->')\\n if self.debug_mode:\\n print \\\"output image format is: \\\" + output_image_format\\n else:\\n for image_format in explicit_format_list:\\n if specified_image_format == image_format[idx]:\\n output_image_format = specified_image_format #Should be unique value in the list\\n if self.debug_mode:\\n print \\\"(explicit) output image format is: \\\" + str(output_image_format)\\n\\n return output_image_format\",\n \"def test_stack_info(self):\\n self.assertEqual(DiscordReportFormatter().format(self.record(sinfo=\\\"stack\\\")), \\\":warning: **test**\\\\n\\\" + \\\\\\n \\\"**stack**\\\\n\\\" + \\\\\\n \\\"```\\\\n\\\" + \\\\\\n \\\"stack\\\\n\\\" + \\\\\\n \\\"```\\\")\",\n \"def test_format_variations(test_format, expect_format):\\n format_schema = sd.DeploymentFormat()\\n try:\\n result_format = format_schema.deserialize(test_format)\\n result_format.pop(\\\"$schema\\\", None)\\n assert result_format == expect_format\\n except colander.Invalid:\\n pytest.fail(f\\\"Expected format to be valid: [{test_format}]\\\")\",\n \"def test_get_structure_fmt(self):\\n fmt, block_size = get_structure_fmt(SlotHeaderStructure)\\n self.assertEqual(fmt, self.fmt_slot_header)\\n self.assertEqual(block_size, self.block_size_slot_header)\",\n \"def test_algorithm_info_fine(self):\\n\\t\\ti = self.algo.algorithmInfo()\\n\\t\\tself.assertIsNotNone(i)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.61617583","0.5618504","0.55047697","0.5475531","0.5467334","0.544068","0.5422697","0.54041266","0.5374505","0.53257984","0.5319085","0.53129464","0.5284171","0.5279987","0.52776444","0.52651304","0.52415544","0.51991093","0.51775396","0.5157071","0.51294017","0.51253223","0.5101958","0.5097684","0.50853336","0.5076196","0.50752264","0.5059222","0.5058419","0.5050697","0.50444245","0.5039777","0.5031201","0.50291723","0.50291544","0.50125724","0.5005626","0.5005626","0.5000536","0.49981147","0.49978563","0.49933383","0.49894235","0.49884713","0.49871153","0.49796474","0.49781436","0.49704674","0.49623707","0.495404","0.49467686","0.49461457","0.49318084","0.4931269","0.49304593","0.49251717","0.49147052","0.49137276","0.48953113","0.48942575","0.48934233","0.4893233","0.4891812","0.488293","0.48783726","0.48741072","0.48691455","0.48601344","0.4855075","0.48549044","0.48513085","0.48366812","0.48331025","0.48263672","0.4825452","0.4821738","0.48216724","0.48203886","0.48194152","0.48174238","0.48138157","0.48066244","0.4803151","0.48004812","0.48003832","0.47954214","0.47940648","0.4792036","0.47872788","0.47808015","0.4774147","0.47713518","0.4763222","0.47630954","0.47603515","0.47586828","0.47538835","0.4753781","0.4744714","0.47343135"],"string":"[\n \"0.61617583\",\n \"0.5618504\",\n \"0.55047697\",\n \"0.5475531\",\n \"0.5467334\",\n \"0.544068\",\n \"0.5422697\",\n \"0.54041266\",\n \"0.5374505\",\n \"0.53257984\",\n \"0.5319085\",\n \"0.53129464\",\n \"0.5284171\",\n \"0.5279987\",\n \"0.52776444\",\n \"0.52651304\",\n \"0.52415544\",\n \"0.51991093\",\n \"0.51775396\",\n \"0.5157071\",\n \"0.51294017\",\n \"0.51253223\",\n \"0.5101958\",\n \"0.5097684\",\n \"0.50853336\",\n \"0.5076196\",\n \"0.50752264\",\n \"0.5059222\",\n \"0.5058419\",\n \"0.5050697\",\n \"0.50444245\",\n \"0.5039777\",\n \"0.5031201\",\n \"0.50291723\",\n \"0.50291544\",\n \"0.50125724\",\n \"0.5005626\",\n \"0.5005626\",\n \"0.5000536\",\n \"0.49981147\",\n \"0.49978563\",\n \"0.49933383\",\n \"0.49894235\",\n \"0.49884713\",\n \"0.49871153\",\n \"0.49796474\",\n \"0.49781436\",\n \"0.49704674\",\n \"0.49623707\",\n \"0.495404\",\n \"0.49467686\",\n \"0.49461457\",\n \"0.49318084\",\n \"0.4931269\",\n \"0.49304593\",\n \"0.49251717\",\n \"0.49147052\",\n \"0.49137276\",\n \"0.48953113\",\n \"0.48942575\",\n \"0.48934233\",\n \"0.4893233\",\n \"0.4891812\",\n \"0.488293\",\n \"0.48783726\",\n \"0.48741072\",\n \"0.48691455\",\n \"0.48601344\",\n \"0.4855075\",\n \"0.48549044\",\n \"0.48513085\",\n \"0.48366812\",\n \"0.48331025\",\n \"0.48263672\",\n \"0.4825452\",\n \"0.4821738\",\n \"0.48216724\",\n \"0.48203886\",\n \"0.48194152\",\n \"0.48174238\",\n \"0.48138157\",\n \"0.48066244\",\n \"0.4803151\",\n \"0.48004812\",\n \"0.48003832\",\n \"0.47954214\",\n \"0.47940648\",\n \"0.4792036\",\n \"0.47872788\",\n \"0.47808015\",\n \"0.4774147\",\n \"0.47713518\",\n \"0.4763222\",\n \"0.47630954\",\n \"0.47603515\",\n \"0.47586828\",\n \"0.47538835\",\n \"0.4753781\",\n \"0.4744714\",\n \"0.47343135\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.72220844"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81483,"cells":{"query":{"kind":"string","value":"First test of the spin ID generation function. The function tested is pipe_control.mol_res_spin.generate_spin_id_data_array()."},"document":{"kind":"string","value":"def test_generate_spin_id_data_array1(self):\n\n # The data.\n data = ['1', 'GLY']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_generate_spin_id_data_array6(self):\n\n # The data.\n data = ['1', 'GLY', None, None]\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')","def test_generate_spin_id_data_array2(self):\n\n # The data.\n data = ['1', 'GLY', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2, spin_num_col=3, spin_name_col=4)\n\n # Test the string.\n self.assertEqual(id, ':1@234')","def test_generate_spin_id_data_array5(self):\n\n # The data.\n data = ['Ap4Aase', '1', 'GLY', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5)\n\n # Test the string.\n self.assertEqual(id, '#Ap4Aase:1@234')","def test_generate_spin_id_data_array4(self):\n\n # The data.\n data = ['Ap4Aase', '1', 'GLY']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3)\n\n # Test the string.\n self.assertEqual(id, '#Ap4Aase:1')","def test_generate_spin_id_data_array3(self):\n\n # The data.\n data = ['Ap4Aase', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=None, res_name_col=None, spin_num_col=2, spin_name_col=3)\n\n # Test the string.\n self.assertEqual(id, '#Ap4Aase@234')","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_id_array(self):\n arr = vtk.vtkIdTypeArray()\n arr.SetNumberOfTuples(10)\n for i in range(10):\n arr.SetValue(i, i)\n\n np = array_handler.vtk2array(arr)\n self.assertEqual(numpy.all(np == range(10)), True)","def test_create_template(self):\n m_size = 10\n data = ecn.IDData(m_size)\n self.assertEqual(np.shape(data.ID_MATRIX), (m_size, m_size))\n self.assertEqual(sum(sum(data.ID_MATRIX)), m_size)\n self.assertTrue((sum(data.ID_MATRIX) == np.ones(m_size)).all())\n print('Finished testing template\\n')","def test_random_id(self):\r\n ids = \\\r\n \"R27DLI_4812 R27DLI_600 R27DLI_727 U1PLI_403 U1PLI_8969\".split(\r\n )\r\n assert random_id(ids, {}) in ids\r\n # just test we got something from the list, don't add stochastic test\r","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def createArrayFunc(self):\r\n minVal = int(self.spinBoxMin_2.value())\r\n maxVal = int(self.spinBoxMax_2.value())\r\n arrayLength = int(self.spinBoxLength_2.value())\r\n different = maxVal - minVal\r\n if self.checkBoxNoRepeate_2.isChecked():\r\n if different > arrayLength:\r\n def unique_rand(initial, limit, total):\r\n data = []\r\n i = 0\r\n while i < total:\r\n number = numpy.random.randint(initial, limit)\r\n if number not in data:\r\n data.append(number)\r\n i += 1\r\n return data\r\n\r\n self.UnsortedArray_2 = unique_rand(minVal, maxVal, arrayLength)\r\n else:\r\n err = \"Array length must be greater than difference between limits\"\r\n self.labelUnsortedArray_2.setText(str(err))\r\n\r\n else:\r\n self.UnsortedArray_2 = numpy.random.randint(minVal, maxVal, arrayLength)\r\n self.labelUnsortedArray_2.setText(str(self.UnsortedArray_2))\r\n self.SortedArray_2 = Insertion.sorting(self.UnsortedArray_2)\r\n self.labelSortedArray_2.setText(str(self.SortedArray_2))\r\n binaryMax = int(self.spinBoxMax_2.value())\r\n binaryMin = int(self.spinBoxMin_2.value())\r\n self.spinBoxBinary.setMaximum(binaryMax)\r\n self.spinBoxBinary.setMinimum(binaryMin)\r\n self.spinBoxIthSmallest.setMaximum(arrayLength + 1)","def test_spin_loop(self):\n\n # Spin data.\n select = [1, 0]\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, 'N5')\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 2)","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_spin_type(get_pdos_generator_inputs):\n with pytest.raises(NotImplementedError):\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=spin_type)\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=SpinType.COLLINEAR)\n for namespace in [builder.scf, builder.nscf]:\n parameters = namespace['pw']['parameters'].get_dict()\n assert parameters['SYSTEM']['nspin'] == 2\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}","def test_scan_id_list(self):\n scan = '15,17'\n ref_idx = [0,3]\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_spin_loop_no_selection(self):\n\n # Spin data.\n select = [0, 1, 0, 0, 1, 1, 0, 1]\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 8)","def test_create_tornado_id(self):\n\n this_id_string = tornado_io.create_tornado_id(\n start_time_unix_sec=TORNADO_START_TIME_UNIX_SEC,\n start_latitude_deg=TORNADO_START_LATITUDE_DEG,\n start_longitude_deg=TORNADO_START_LONGITUDE_DEG)\n\n self.assertTrue(this_id_string == TORNADO_ID_STRING)","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_spin_type(fixture_code, generate_structure):\n code = fixture_code('quantumespresso.pw')\n structure = generate_structure()\n\n with pytest.raises(NotImplementedError):\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\n PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=spin_type)\n\n builder = PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=SpinType.COLLINEAR)\n\n for namespace in [builder.relax['base'], builder.scf, builder.bands]:\n parameters = namespace['pw']['parameters'].get_dict()\n assert parameters['SYSTEM']['nspin'] == 2\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}","def test_pol_id_list(self):\n pol = '0,1'\n ref_idx = []\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_arr2vtkIdList(self):\n a = [1, 2, 3, 4, 5]\n p = array_handler.array2vtkIdList(a)\n for i, j in enumerate(a): \n self.assertEqual(p.GetId(i), j)\n p = vtk.vtkIdList()\n ident = id(p)\n p = array_handler.array2vtkIdList(numpy.array(a), p)\n for i, j in enumerate(a): \n self.assertEqual(p.GetId(i), j)\n self.assertEqual(id(p), ident)\n \n self.assertRaises(AssertionError, array_handler.array2vtkIdList,\n [[1,2,3]])","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def _get_rand_array(self):\n pass","def test_004_init(self):\n self.assertIsInstance(rawdata.rawdata(\"id\",testRawdata.ioc,testRawdata.sam),rawdata.rawdata)","def test_generateuuids(self):\n ret1 = {\"message\": \"No Random.org api key or api version found.\", \"res\": False}\n self.assertDictEqual(random_org.generateUUIDs(), ret1)\n\n ret2 = {\"message\": \"Required argument, number is missing.\", \"res\": False}\n self.assertDictEqual(\n random_org.generateUUIDs(api_key=\"peW\", api_version=\"1\"), ret2\n )\n\n ret3 = {\"message\": \"Number of UUIDs must be between 1 and 1000\", \"res\": False}\n self.assertDictEqual(\n random_org.generateUUIDs(api_key=\"peW\", api_version=\"1\", number=\"5\"), ret3\n )\n\n ret3 = {\"message\": \"Parameter 'apiKey' is malformed\", \"res\": False}\n self.assertDictEqual(\n random_org.generateUUIDs(api_key=\"peW\", api_version=\"1\", number=5), ret3\n )","def test_scan_id_range(self):\n scan = '16~17'\n ref_idx = [1,2,3]\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def test_random_integers(self):\r\n # Check over two calls to see if the random state is correctly updated.\r\n m = Module()\r\n m.random = RandomStreams(utt.fetch_seed())\r\n m.fn = Method([], m.random.random_integers((20,20), -5, 5))\r\n\r\n made = m.make()\r\n made.random.initialize()\r\n fn_val0 = made.fn()\r\n fn_val1 = made.fn()\r\n\r\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\r\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\r\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\r\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\r\n\r\n assert numpy.all(fn_val0 == numpy_val0)\r\n assert numpy.all(fn_val1 == numpy_val1)","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_id_rot():\n assert_array_almost_equal(pr.R_id, pr.matrix_from_axis_angle(pr.a_id))\n assert_array_almost_equal(pr.R_id, pr.matrix_from_quaternion(pr.q_id))\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_xyz(pr.e_xyz_id))\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_zyx(pr.e_zyx_id))","def gen_data(min_coord, max_coord, size):\r\n data = np.random.randint(min_coord, max_coord, size)\r\n return data","def test_init():\n mesh = CuboidMesh(nx=100, ny=1, nz=1)\n sim = Sim(mesh)\n sim.set_m(init_m)\n\n expected = np.array([0, 0, 1,\n 0, np.sin(0.1), np.cos(0.1)])\n\n assert max(abs(sim.spin[:6] - expected)) < 1e-15","def _spin_sequence(self):\n self.return_position = self.motor.position\n \n for spin_num in range(self.num_spins):\n self.taxi()\n\n det_pre_acquire(self.detector)\n self.fly()\n det_post_acquire(self.detector)\n\n while self.detector.hdf1.write_file.value:\n time.sleep(0.01) # wait for file to be written\n\n event = OrderedDict()\n event[\"time\"] = time.time()\n event[\"seq_num\"] = spin_num + 1\n event[\"data\"] = {}\n event[\"timestamps\"] = {}\n for d_item in (self.detector.hdf1.full_file_name,):\n d = d_item.read()\n for k, v in d.items():\n event['data'][k] = v['value']\n event['timestamps'][k] = v['timestamp']\n\n self._data.append(event)\n\n self.set(\"Return\")\n self._completion_status._finished(success=True)","def _apply_array_spin123(self,\n h1e: 'Nparray',\n h2e: 'Nparray',\n h3e: 'Nparray',\n dvec: Optional[Tuple['Nparray', 'Nparray']] = None,\n evec: Optional[Tuple['Nparray', 'Nparray', 'Nparray', 'Nparray']] \\\n = None) -> 'Nparray':\n norb = self.norb()\n assert h3e.shape == (norb * 2,) * 6\n assert not (dvec is None) ^ (evec is None)\n\n from1234 = (dvec is not None) and (evec is not None)\n\n nh1e = numpy.copy(h1e)\n nh2e = numpy.copy(h2e)\n\n for i in range(norb * 2):\n for j in range(norb * 2):\n for k in range(norb * 2):\n nh2e[j, k, :, :] += (-h3e[k, j, i, i, :, :] -\n h3e[j, i, k, i, :, :] -\n h3e[j, k, i, :, i, :])\n\n nh1e[:, :] += h3e[:, i, j, i, j, :]\n\n out = self._apply_array_spin12_halffilling(nh1e, nh2e)\n\n n = norb # This is just shorter\n if not from1234:\n symfac = 2.0\n axes = ((1, 3), (0, 1))\n (odveca, odvecb) = self.calculate_dvec_spin()\n dveca = numpy.zeros_like(odveca)\n dvecb = numpy.zeros_like(odvecb)\n\n for i in range(norb):\n for j in range(norb):\n evecaa, _ = self._calculate_dvec_spin_with_coeff(\n odveca[i, j, :, :])\n evecab, evecbb = self._calculate_dvec_spin_with_coeff(\n odvecb[i, j, :, :])\n\n dveca += numpy.tensordot(h3e[:n, :n, i, :n, :n, j],\n evecaa,\n axes=axes)\n dveca += numpy.tensordot(h3e[:n, :n, n + i, :n, :n, n + j],\n evecab,\n axes=axes) * symfac\n dveca += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\n evecbb,\n axes=axes)\n\n dvecb += numpy.tensordot(h3e[n:, :n, i, n:, :n, j],\n evecaa,\n axes=axes)\n dvecb += numpy.tensordot(h3e[n:, :n, n + i, n:, :n, n + j],\n evecab,\n axes=axes) * symfac\n dvecb += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\n evecbb,\n axes=axes)\n else:\n symfac = 1.0\n axes = ((1, 4, 2, 5), (0, 1, 2, 3)) # type: ignore\n dveca, dvecb = dvec # type: ignore\n evecaa, evecab, evecba, evecbb = evec # type: ignore\n\n dveca = numpy.tensordot(h3e[:n, :n, :n, :n, :n, :n],\n evecaa, axes=axes) \\\n + numpy.tensordot(h3e[:n, :n, n:, :n, :n, n:],\n evecab, axes=axes) * symfac \\\n + numpy.tensordot(h3e[:n, n:, n:, :n, n:, n:],\n evecbb, axes=axes) + \\\n + numpy.tensordot(h3e[:n, n:, :n, :n, n:, :n],\n evecba, axes=axes)\n\n dvecb = numpy.tensordot(h3e[n:, :n, :n, n:, :n, :n],\n evecaa, axes=axes) \\\n + numpy.tensordot(h3e[n:, :n, n:, n:, :n, n:],\n evecab, axes=axes) * symfac \\\n + numpy.tensordot(h3e[n:, n:, n:, n:, n:, n:],\n evecbb, axes=axes) + \\\n + numpy.tensordot(h3e[n:, n:, :n, n:, n:, :n],\n evecba, axes=axes)\n\n out -= self._calculate_coeff_spin_with_dvec((dveca, dvecb))\n return out","def test_id_get(mocker):\n mocker.patch('serial.Serial.open')\n mocker.patch('serial.Serial.flushInput')\n css = mocker.patch('pysds011.driver.SDS011.cmd_set_sleep')\n css.return_value = True\n cfv = mocker.patch('pysds011.driver.SDS011.cmd_firmware_ver')\n cfv.return_value = {'id': b'\\x12\\x34', 'paperino': 'maciomicio'}\n runner = CliRunner()\n result = runner.invoke(main, ['id'])\n\n calls = [call(0, id=b'\\xff\\xff'), call(1, id=b'\\xff\\xff')]\n css.assert_has_calls(calls, any_order=False)\n\n assert '12' in result.output and '34' in result.output\n assert result.exit_code == 0","def test_CreateROI1(self):\r\n\r\n self.delayDisplay(\"Starting the test\")\r\n #\r\n # first, get some data\r\n #\r\n import urllib\r\n downloads = (\r\n ('http://slicer.kitware.com/midas3/download?items=5767', 'FA.nrrd', slicer.util.loadVolume),\r\n )\r\n\r\n for url,name,loader in downloads:\r\n filePath = slicer.app.temporaryPath + '/' + name\r\n if not os.path.exists(filePath) or os.stat(filePath).st_size == 0:\r\n logging.info('Requesting download %s from %s...\\n' % (name, url))\r\n urllib.urlretrieve(url, filePath)\r\n if loader:\r\n logging.info('Loading %s...' % (name,))\r\n loader(filePath)\r\n self.delayDisplay('Finished with download and loading')\r\n\r\n volumeNode = slicer.util.getNode(pattern=\"FA\")\r\n logic = CreateROILogic()\r\n self.assertIsNotNone( logic.hasImageData(volumeNode) )\r\n self.delayDisplay('Test passed!')","def test_main(data, tmp_path):\n\n main(data, tmp_path)\n\n FILES = (\n \"gd32f888x(0-1)xx-pinctrl.h\",\n \"gd32f888x(2-3)xx-pinctrl.h\",\n \"gd32f888y(0-1)xx-pinctrl.h\",\n \"gd32f999x(0-1)xx-pinctrl.h\",\n \"gd32f999x(2-3)xx-pinctrl.h\",\n \"gd32f999y(0-1)xx-pinctrl.h\",\n )\n\n for file in FILES:\n ref_file = data / file\n gen_file = tmp_path / file\n\n assert gen_file.exists()\n\n with open(ref_file) as ref, open(gen_file) as gen:\n assert ref.read() == gen.read()","def test_split_id_otp(self):\n public_id, otp, = pyhsm.yubikey.split_id_otp(\"ft\" * 16)\n self.assertEqual(public_id, '')\n self.assertEqual(otp, \"ft\" * 16)\n\n public_id, otp, = pyhsm.yubikey.split_id_otp(\"cc\" + \"ft\" * 16)\n self.assertEqual(public_id, 'cc')\n self.assertEqual(otp, \"ft\" * 16)","def test_brains_id_get(self):\n pass","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def test_uuid():\n for _ in range(1000):\n uuid = uuid_generator()\n assert len(uuid) == 36\n assert uuid.count('-') == 4","def _generate_id() -> str:\n return \"\".join(sample(\"abcdefghjkmopqrstuvqxyz\", 16))","def generate_raiz():\n\treturn os.urandom(12)","def test_random_integers(self):\r\n # Check over two calls to see if the random state is correctly updated.\r\n random = RandomStreams(utt.fetch_seed())\r\n fn = function([], random.random_integers((20, 20), -5, 5))\r\n fn_val0 = fn()\r\n fn_val1 = fn()\r\n\r\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\r\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\r\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\r\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\r\n\r\n assert numpy.all(fn_val0 == numpy_val0)\r\n assert numpy.all(fn_val1 == numpy_val1)","def test_pol_id_range(self):\n pol = '0~1'\n ref_idx = []\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_run_sim():\n rnd = rand.Arrivals(31, 40)\n sim.run_sim(2, 1, 3, 4, 24, rnd)","def test_run_sim_1():\n rnd = rand.Arrivals(36, 41)\n sim.run_sim(3, 2, 5, 6, 22, rnd)","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_get_ids(civic, main_data, updated_data):\n assert len(civic._get_ids(main_data['assertions'])) == 0\n assert len(civic._get_ids(main_data['variants'])) == 1\n assert len(civic._get_ids(main_data['genes'])) == 2\n assert len(civic._get_ids(main_data['evidence'])) == 1\n\n assert len(civic._get_ids(updated_data['assertions'])) == 1\n assert len(civic._get_ids(updated_data['variants'])) == 1\n assert len(civic._get_ids(updated_data['genes'])) == 1\n assert len(civic._get_ids(updated_data['evidence'])) == 1","def test_seqgen(fprime_test_api):\n sequence = Path(__file__).parent / \"test_seq.seq\"\n assert (\n subprocess.run(\n [\n \"fprime-seqgen\",\n \"-d\",\n str(fprime_test_api.pipeline.dictionary_path),\n str(sequence),\n \"/tmp/ref_test_int.bin\",\n ]\n ).returncode\n == 0\n ), \"Failed to run fprime-seqgen\"\n fprime_test_api.send_and_assert_command(\n \"cmdSeq.CS_RUN\", args=[\"/tmp/ref_test_int.bin\", \"BLOCK\"], max_delay=5\n )","def test_id_set(mocker):\n mocker.patch('serial.Serial.open')\n mocker.patch('serial.Serial.flushInput')\n css = mocker.patch('pysds011.driver.SDS011.cmd_set_sleep')\n css.return_value = True\n csi = mocker.patch('pysds011.driver.SDS011.cmd_set_id')\n runner = CliRunner()\n result = runner.invoke(main, ['--id', 'cccc', 'id', 'abcd'])\n\n # Two calls to cmd_set_sleep:\n # the first use original address\n # at the second one, the sensor has a new address: so sleep\n # has the use the new one\n calls = [call(0, id=b'\\xcc\\xcc'), call(1, id=b'\\xab\\xcd')]\n css.assert_has_calls(calls, any_order=False)\n csi.assert_called_once_with(id=b'\\xcc\\xcc', new_id=b'\\xab\\xcd')\n assert result.exit_code == 0","def test_first_id(self):\r\n ids = \\\r\n \"R27DLI_4812 R27DLI_600 R27DLI_727 U1PLI_403 U1PLI_8969\".split(\r\n )\r\n self.assertEqual(first_id(ids, {}), 'R27DLI_4812')","def test_generate(self):\n cant_interations = int(random()*100)\n for i in range(cant_interations):\n number = self.sudoku.generate() # Generate number\n self.assertGreaterEqual(number, 0) # number >= 0\n self.assertLessEqual(number, 8) # number <= 8","def myID() -> np.int:\r\n return 304976335","def myID() -> np.int:\r\n return 304976335","def test_get_tid():\n tids = []\n def _foo():\n mytid = yield GetTid()\n tids.append(mytid)\n for i in range(5):\n yield i\n\n scheduler = Scheduler()\n scheduler.new(_foo())\n scheduler.new(_foo())\n scheduler.mainloop()\n\n # can we do better than hard code?\n assert tids == [4, 5]","def test_return_spin_pipe_fail(self):\n\n # Try to get a spin from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')","def test_ipam_rirs_create(self):\n pass","def test_start_ids_10(self):\n\n\t\texpected_num_layers = 11\n\t\texpected_ids = np.arange(10,21)\n\t\t# test describe\n\t\tdetails = self.watcher.describe(start_ids=10)\n\t\tprint(\"start id = 10\", details)\n\t\tactual_ids = details.layer_id.to_numpy().tolist()\n\t\tself.assertTrue(np.array_equal(actual_ids, expected_ids))\n\t\tself.assertEqual(len(expected_ids), expected_num_layers)\n\t\t\t\t\n\t\treturn","def test_periodic_boundary_one_ring_rod():\n\n n_elems = 5\n ring_rod = MockRingRod(n_elems)\n block_structure = MemoryBlockCosseratRod([ring_rod], [0])\n\n correct_periodic_boundary_node_idx = np.array(\n [[0, 6, 7], [5, 1, 2]], dtype=np.int64\n )\n correct_periodic_boundary_elem_idx = np.array([[0, 6], [5, 1]], dtype=np.int64)\n correct_periodic_boundary_voronoi_idx = np.array([[0], [5]], dtype=np.int64)\n\n assert_allclose(\n correct_periodic_boundary_node_idx,\n block_structure.periodic_boundary_nodes_idx,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_periodic_boundary_elem_idx,\n block_structure.periodic_boundary_elems_idx,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_periodic_boundary_voronoi_idx,\n block_structure.periodic_boundary_voronoi_idx,\n atol=Tolerance.atol(),\n )\n\n correct_start_node_idx = np.array([1], dtype=np.int64)\n correct_end_node_idx = np.array([6], dtype=np.int64)\n\n correct_start_elem_idx = np.array([1], dtype=np.int64)\n correct_end_elem_idx = np.array([6], dtype=np.int64)\n\n correct_start_voronoi_idx = np.array([1], dtype=np.int64)\n correct_end_voronoi_idx = np.array([6], dtype=np.int64)\n\n assert_allclose(\n correct_start_node_idx,\n block_structure.start_idx_in_rod_nodes,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_node_idx,\n block_structure.end_idx_in_rod_nodes,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_start_elem_idx,\n block_structure.start_idx_in_rod_elems,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_elem_idx,\n block_structure.end_idx_in_rod_elems,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_start_voronoi_idx,\n block_structure.start_idx_in_rod_voronoi,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_voronoi_idx,\n block_structure.end_idx_in_rod_voronoi,\n atol=Tolerance.atol(),\n )","def test_id(self):\n b1 = Base()\n self.assertEqual(b1.id, 1)\n b2 = Base()\n self.assertEqual(b2.id, 2)\n b3 = Base(98)\n self.assertEqual(b3.id, 98)\n b4 = Base(256)\n self.assertEqual(b4.id, 256)\n b5 = Base()\n self.assertEqual(b5.id, 3)\n b6 = Base(-98)\n self.assertEqual(b6.id, -98)\n b7 = Base(None)\n self.assertEqual(b7.id, 4)\n b8 = Base(4.4)\n self.assertEqual(b8.id, 4.4)","def generate_T(number_obeservations):\n T = np.random.randint(0, 2, (number_obeservations,1))\n return T","def test_slepp_get_at_id(mocker):\n mocker.patch('serial.Serial.open')\n mocker.patch('serial.Serial.flushInput')\n cgs = mocker.patch('pysds011.driver.SDS011.cmd_get_sleep')\n runner = CliRunner()\n result = runner.invoke(main, ['--id', 'ABCD', 'sleep'])\n cgs.assert_called_once_with(id=b'\\xab\\xcd')\n\n assert result.exit_code == 0","def generate_fake_data(t0, num_array, period=5820, data_range=[0.0, 24.0],\n cyclic=True):\n\n if cyclic:\n uts_root = np.mod(t0, period)\n data = (np.mod(uts_root + num_array, period)\n * (np.diff(data_range)[0] / np.float64(period))) + data_range[0]\n else:\n data = ((t0 + num_array) / period).astype(int)\n\n return data","def test_test_ids_request(get_interface_params):\n from sail_on_client.protocol.localinterface import LocalInterface\n\n config_directory, config_name = get_interface_params\n data_dir = f\"{os.path.dirname(__file__)}/data\"\n local_interface = LocalInterface(config_name, config_directory)\n\n assumptions_path = os.path.join(os.path.dirname(__file__), \"assumptions.json\")\n filename = local_interface.test_ids_request(\n \"OND\", \"image_classification\", \"5678\", assumptions_path\n )\n expected = os.path.join(data_dir, \"OND\", \"image_classification\", \"test_ids.csv\")\n assert os.stat(expected).st_size > 5\n assert expected == filename","def test_correct_binid(self):\n\n maps = Maps(plateifu='8485-1901', release='DR17', bintype='HYB10')\n spaxel = maps[22, 14]\n\n assert isinstance(spaxel, Spaxel)\n assert spaxel.x == 14, spaxel.y == 22\n\n bin_spaxels = spaxel.stellar_vel.bin.get_bin_spaxels()\n\n for sp in bin_spaxels:\n\n sp.load()\n assert sp.stellar_vel.bin.binid == spaxel.stellar_vel.bin.binid\n\n sp_bin = maps[sp.y, sp.x]\n assert sp_bin.stellar_vel.bin.binid == spaxel.stellar_vel.bin.binid","def test_random_generator(self):\n gen = random_data()\n data = [next(gen) for _ in range(100)]\n self.assertEqual(len(data), 100)","def test_SampleIds(self):\r\n exp = [\"PC.354\", \"PC.355\", \"PC.356\", \"PC.481\", \"PC.593\", \"PC.607\",\r\n \"PC.634\", \"PC.635\", \"PC.636\"]\r\n obs = self.overview_map.SampleIds\r\n self.assertEqual(obs, exp)\r\n\r\n obs = self.no_metadata.SampleIds\r\n self.assertEqual(obs, exp)\r\n\r\n obs = self.empty_map.SampleIds\r\n self.assertEqual(obs, [])","def test_SampleIds(self):\n exp = [\"PC.354\", \"PC.355\", \"PC.356\", \"PC.481\", \"PC.593\", \"PC.607\",\n \"PC.634\", \"PC.635\", \"PC.636\"]\n obs = self.overview_map.SampleIds\n self.assertEqual(obs, exp)\n\n obs = self.no_metadata.SampleIds\n self.assertEqual(obs, exp)\n\n obs = self.empty_map.SampleIds\n self.assertEqual(obs, [])","def next():\n iraw = 0\n run = 0\n seqno = 0\n with db_connection() as conn:\n with conn.cursor() as curs:\n try:\n curs.execute(\"\"\"SELECT rawdata.id,rawdata.run,rawdata.seqno,\n slices.block1,slices.block2,\n jobs.cluster,jobs.process\n FROM rawdata\n LEFT JOIN bindings\n ON bindings.iraw = rawdata.id\n INNER JOIN slices\n ON slices.iraw = rawdata.id\n LEFT JOIN jobs\n ON slices.ijob = jobs.id\n AND jobs.exitcode = 0\n WHERE bindings.id IS NULL\n ORDER BY rawdata.id,slices.block1\n LIMIT 2000;\n \"\"\")\n slices_missing = 1\n for row in curs.fetchall():\n i = int(row[0])\n if i != iraw:\n if slices_missing == 0:\n break\n else:\n run = int(row[1])\n seqno = int(row[2])\n slices_missing = 0\n slices = []\n iraw = i\n block1 = int(row[3])\n block2 = int(row[4])\n if row[5] is not None and row[6] is not None:\n cluster = int(row[5])\n process = int(row[6])\n slices.append((block1,block2,cluster,process))\n else:\n print(\"slices missing on\", row[5], row[6])\n slices_missing += 1\n if slices_missing:\n return 0\n else:\n curs.execute(\"SELECT TIMEZONE('GMT', NOW());\")\n now = curs.fetchone()[0]\n curs.execute(\"\"\"INSERT INTO bindings\n (iraw,starttime)\n VALUES (%s,%s)\n RETURNING id;\n \"\"\", (iraw, now))\n row = curs.fetchone()\n if row:\n ibind = int(row[0])\n else:\n return 0\n except:\n iraw = 0\n if iraw == 0:\n time.sleep(random.randint(1,30))\n return -9 # collision\n\n workdir = str(iraw)\n os.mkdir(workdir)\n os.chdir(workdir)\n badslices = []\n for sl in slices:\n sdir = str(sl[0]) + \",\" + str(sl[1])\n os.mkdir(sdir)\n tarfile = \"job_{0}_{1}.tar.gz\".format(sl[2], sl[3])\n tarpath = input_area + \"/\" + tarfile\n try:\n subprocess.check_output([\"gfal-copy\", src_url + tarpath,\n \"file://\" + os.getcwd() + \"/\" + tarfile])\n except:\n sys.stderr.write(\"Error -999 on rawdata id {0}\".format(iraw) +\n \" - job output \" + tarfile + \" is missing!\\n\")\n sys.stderr.flush()\n badslices.append(sdir)\n continue\n try:\n subprocess.check_output([\"tar\", \"zxf\", tarfile, \"-C\", sdir])\n except:\n sys.stderr.write(\"Error -999 on rawdata id {0}\".format(iraw) +\n \" - job output \" + tarfile + \" is not readable!\\n\")\n sys.stderr.flush()\n badslices.append(sdir)\n finally:\n os.remove(tarfile)\n if len(badslices) > 0:\n with db_connection() as conn:\n with conn.cursor() as curs:\n curs.execute(\"SELECT TIMEZONE('GMT', NOW());\")\n now = curs.fetchone()[0]\n curs.execute(\"\"\"UPDATE bindings\n SET endtime=%s, \n exitcode=%s,\n details=%s\n WHERE id = %s;\n \"\"\", (now, -999, \":\".join(badslices), ibind))\n os.chdir(\"..\")\n shutil.rmtree(workdir)\n return 1\n\n badslices += merge_evio_skims(run, seqno, slices)\n badslices += merge_hddm_output(run, seqno, slices)\n badslices += merge_job_info(run, seqno, slices)\n badslices += merge_root_histos(run, seqno, slices)\n exitcode = -len(badslices)\n with db_connection() as comm:\n with conn.cursor() as curs:\n curs.execute(\"SELECT TIMEZONE('GMT', NOW());\")\n now = curs.fetchone()[0]\n curs.execute(\"\"\"UPDATE bindings\n SET endtime=%s,\n exitcode=%s,\n details=%s\n WHERE id = %s;\n \"\"\", (now, exitcode, \":\".join(badslices), ibind))\n os.chdir(\"..\")\n shutil.rmtree(workdir)\n return 1","def generate_client_volgen_data(data):\n\n # No of distribute groups in a volume\n dist_grp_count = 0\n # No of storage units in a distribute group\n storage_unit_count = 0\n replica_count = 0\n arbiter_count = 0\n\n get_replica_count = {\n \"Replica1\" : 1,\n \"Replica2\" : 2,\n \"Replica3\" : 3\n }\n\n if data[\"type\"] == \"Disperse\":\n storage_unit_count = data[\"disperse\"][\"data\"] + data[\"disperse\"][\"redundancy\"]\n replica_count = 0\n elif \"Replica\" in data[\"type\"]:\n storage_unit_count = replica_count = get_replica_count.get(data[\"type\"], \"\")\n elif data[\"type\"] == \"Arbiter\":\n storage_unit_count = replica_count = 3\n arbiter_count = 1\n\n client_data = {}\n client_data[\"name\"] = data[\"volname\"]\n client_data[\"id\"] = data[\"volume_id\"]\n\n dist_grp_count = int((len(data[\"bricks\"]) / storage_unit_count))\n client_data[\"distribute_groups\"] = [{} for _ in range(dist_grp_count)]\n\n for dist_grp_idx, dist_grp in enumerate(client_data[\"distribute_groups\"]):\n if \"Replica\" in data[\"type\"]:\n dist_grp[\"type\"] = \"replicate\"\n elif \"Disperse\" in data[\"type\"]:\n dist_grp[\"type\"] = \"disperse\"\n else:\n dist_grp[\"type\"] = \"arbiter\"\n\n if replica_count:\n dist_grp[\"replica_count\"] = replica_count\n if arbiter_count:\n dist_grp[\"arbiter_count\"] = arbiter_count\n if dist_grp[\"type\"] == \"disperse\":\n dist_grp[\"disperse_count\"] = data[\"disperse\"].get(\"data\", 0)\n dist_grp[\"redundancy_count\"] = data[\"disperse\"].get(\"redundancy\", 0)\n\n dist_grp[\"storage_units\"] = [{} for _ in range(storage_unit_count)]\n\n for storage_unit_idx, storage_unit in enumerate(dist_grp[\"storage_units\"]):\n brick_idx = (dist_grp_idx * storage_unit_count + storage_unit_idx)\n storage_unit[\"path\"] = data[\"bricks\"][brick_idx].get(\"brick_path\", \"\")\n storage_unit[\"port\"] = 24007\n storage_unit[\"node\"] = {\n \"name\" : data[\"bricks\"][brick_idx].get(\"node\", \"\"),\n \"id\" : data[\"bricks\"][brick_idx].get(\"node_id\", \"\")\n }\n\n return client_data","def generateUniqueId(context):\n\n fn_normalize = getUtility(IFileNameNormalizer).normalize\n id_normalize = getUtility(IIDNormalizer).normalize\n prefixes = context.bika_setup.getPrefixes()\n\n year = context.bika_setup.getYearInPrefix() and \\\n DateTime().strftime(\"%Y\")[2:] or ''\n separator = '-'\n for e in prefixes:\n if 'separator' not in e:\n e['separator'] = ''\n if e['portal_type'] == context.portal_type:\n separator = e['separator']\n # Analysis Request IDs\n if context.portal_type == \"AnalysisRequest\":\n sample = context.getSample()\n s_prefix = fn_normalize(sample.getSampleType().getPrefix())\n sample_padding = context.bika_setup.getSampleIDPadding()\n ar_padding = context.bika_setup.getARIDPadding()\n sample_id = sample.getId()\n sample_number = sample_id.split(s_prefix)[1]\n ar_number = sample.getLastARNumber()\n ar_number = ar_number and ar_number + 1 or 1\n\n return fn_normalize(\n (\"%s%s\" + separator + \"R%s\") % (s_prefix,\n str(sample_number).zfill(sample_padding),\n str(ar_number).zfill(ar_padding))\n )\n\n # Sample Partition IDs\n if context.portal_type == \"SamplePartition\":\n # We do not use prefixes. There are actually codes that require the 'P'.\n # matches = [p for p in prefixes if p['portal_type'] == 'SamplePartition']\n # prefix = matches and matches[0]['prefix'] or 'samplepartition'\n # padding = int(matches and matches[0]['padding'] or '0')\n\n # at this time the part exists, so +1 would be 1 too many\n partnr = str(len(context.aq_parent.objectValues('SamplePartition')))\n # parent id is normalized already\n return (\"%s\" + separator + \"P%s\") % (context.aq_parent.id, partnr)\n\n if context.bika_setup.getExternalIDServer():\n\n # if using external server\n\n for d in prefixes:\n # Sample ID comes from SampleType\n if context.portal_type == \"Sample\":\n prefix = context.getSampleType().getPrefix()\n padding = context.bika_setup.getSampleIDPadding()\n new_id = str(idserver_generate_id(context, \"%s%s-\" % (prefix, year)))\n if padding:\n new_id = new_id.zfill(int(padding))\n return ('%s%s' + separator + '%s') % (prefix, year, new_id)\n elif d['portal_type'] == context.portal_type:\n prefix = d['prefix']\n padding = d['padding']\n new_id = str(idserver_generate_id(context, \"%s%s-\" % (prefix, year)))\n if padding:\n new_id = new_id.zfill(int(padding))\n return ('%s%s' + separator + '%s') % (prefix, year, new_id)\n # no prefix; use portal_type\n # year is not inserted here\n # portal_type is be normalized to lowercase\n npt = id_normalize(context.portal_type)\n new_id = str(idserver_generate_id(context, npt + \"-\"))\n return ('%s' + separator + '%s') % (npt, new_id)\n\n else:\n\n # No external id-server.\n\n def next_id(prefix):\n # normalize before anything\n prefix = fn_normalize(prefix)\n plone = context.portal_url.getPortalObject()\n # grab the first catalog we are indexed in.\n at = getToolByName(plone, 'archetype_tool')\n if context.portal_type in at.catalog_map:\n catalog_name = at.catalog_map[context.portal_type][0]\n else:\n catalog_name = 'portal_catalog'\n catalog = getToolByName(plone, catalog_name)\n\n # get all IDS that start with prefix\n # this must specifically exclude AR IDs (two -'s)\n rr = re.compile(\"^\"+prefix+separator+\"[\\d+]+$\")\n ids = [int(i.split(prefix+separator)[1]) \\\n for i in catalog.Indexes['id'].uniqueValues() \\\n if rr.match(i)]\n\n #plone_tool = getToolByName(context, 'plone_utils')\n #if not plone_tool.isIDAutoGenerated(l.id):\n ids.sort()\n _id = ids and ids[-1] or 0\n new_id = _id + 1\n\n return str(new_id)\n\n for d in prefixes:\n if context.portal_type == \"Sample\":\n # Special case for Sample IDs\n prefix = fn_normalize(context.getSampleType().getPrefix())\n padding = context.bika_setup.getSampleIDPadding()\n sequence_start = context.bika_setup.getSampleIDSequenceStart()\n new_id = next_id(prefix+year)\n # If sequence_start is greater than new_id. Set\n # sequence_start as new_id. (Jira LIMS-280)\n if sequence_start > int(new_id):\n new_id = str(sequence_start)\n if padding:\n new_id = new_id.zfill(int(padding))\n return ('%s%s' + separator + '%s') % (prefix, year, new_id)\n elif d['portal_type'] == context.portal_type:\n prefix = d['prefix']\n padding = d['padding']\n sequence_start = d.get(\"sequence_start\", None)\n new_id = next_id(prefix+year)\n # Jira-tracker LIMS-280\n if sequence_start and int(sequence_start) > int(new_id):\n new_id = str(sequence_start)\n if padding:\n new_id = new_id.zfill(int(padding))\n return ('%s%s' + separator + '%s') % (prefix, year, new_id)\n\n if context.portal_type == \"StorageUnit\":\n if context.getStorageUnitID():\n return context.getStorageUnitID()\n\n if context.portal_type == \"StorageManagement\":\n prefix = ''\n if context.getType() == \"Freeze\":\n prefix = \"FZ\"\n elif context.getType() == \"Tank\":\n prefix = \"LN\"\n\n if context.aq_parent.portal_type == \"StorageUnit\":\n padding = 3\n year = DateTime().strftime(\"%Y\")[2:]\n new_id = next_id(prefix + year)\n if padding:\n new_id = new_id.zfill(int(padding))\n return ('%s%s' + '-' + '%s') % (prefix, year, new_id)\n else:\n l = context.Title().split(' ')\n if len(l) == 2:\n return l[1]\n elif len(l) == 1:\n return l[0]\n \n return context.Title().replace(' ', '')\n\n if context.portal_type == \"StorageInventory\":\n prefix = 'INV'\n parent = context.aq_parent\n new_id = next_id(prefix)\n\n if parent.portal_type == \"StorageUnit\":\n new_id = new_id.zfill(int(3))\n return ('%s' + '-' + '%s') % (prefix, new_id)\n\n elif parent.portal_type == \"StorageInventory\":\n room = context.aq_parent.aq_parent\n return room.id + '.' + parent.id + '.' + context.Title()\n\n else:\n raise AssertionError(\"Unknown Portal type\")\n\n if context.portal_type == \"Kit\":\n prefix = context.getPrefix() and context.getPrefix() or \"KIT\"\n padding = 3\n new_id = next_id(prefix)\n if padding:\n new_id = new_id.zfill(int(padding))\n\n return ('%s' + '-' + '%s') % (prefix, new_id)\n\n if context.portal_type == \"StorageLocation\":\n return context.Title()\n\n if context.portal_type == \"Aliquot\":\n # subject = context.getSubjectID()\n # prefix = subject + '-SP' if subject else 'SP'\n prefix = 'AL'\n padding = 3\n new_id = next_id(prefix)\n if padding:\n new_id = new_id.zfill(int(padding))\n\n return ('%s' + '-' + '%s') % (prefix, new_id)\n\n if context.portal_type == \"Biospecimen\":\n prefix = \"BS\"\n padding = 3\n new_id = next_id(prefix)\n if padding:\n new_id = new_id.zfill(int(padding))\n\n return ('%s' + '-' + '%s') % (prefix, new_id)\n\n # no prefix; use portal_type\n # no year inserted here\n # use \"IID\" normalizer, because we want portal_type to be lowercased.\n prefix = id_normalize(context.portal_type)\n new_id = next_id(prefix)\n return ('%s' + separator + '%s') % (prefix, new_id)","def generateRegistrationId():\n regId = KeyHelper.getRandomSequence()\n return regId","def test_acquire_sample(self):\n self.assert_initialize_driver()\n self.assert_particle_generation(ProtocolEvent.ACQUIRE_SAMPLE, DataParticleType.METBK_PARSED, self.assert_data_particle_sample)","def test__get_slurm_jobid(self):\n \n # Mock the system calls\n subprocess.check_output = Mock(return_value='')\n # Assert that getting non-existing jobs return an empty job list\n self.assertListEqual([],sq.get_slurm_jobid(\"jobname\"),\n \"Querying for jobid of non-existing job should return an empty list\")\n # Assert that a returned job id is parsed correctly\n for jobids in [[123456789],[123456789,987654321]]:\n subprocess.check_output = Mock(return_value=\"\\n\".join([str(jid) for jid in jobids]))\n self.assertListEqual(jobids,sq.get_slurm_jobid(\"jobname\"),\n \"Querying for jobid of existing job did not return the correct value\")","def test_setup(sim):\n n = 3\n data = []\n dt = 1\n\n for i in range(n):\n sim.setup(timestep=dt, min_delay=dt)\n p = sim.Population(1, sim.IF_curr_exp(i_offset=0.1))\n p.record('v')\n print('starting run ', i)\n sim.run(10.0)\n print('finished run ', i)\n\n print('start get_data run ', i)\n data.append(p.get_data())\n print('finished get_data run ', i)\n\n print('start sim end ', i)\n sim.end()\n print('finished sim end ', i)\n\n assert len(data) == n\n for block in data:\n assert len(block.segments) == 1\n signals = block.segments[0].analogsignals\n assert len(signals) == 1\n assert_array_equal(signals[0], data[0].segments[0].analogsignals[0])","def test_returned_num_in_random_nums(self):\n self._setup_random_gen([1.], [42])\n self.assertEqual(self._random_gen.next_num(), 42)","def test_sampleId_pairs(self):\r\n # expected values\r\n dose_vps = \\\r\n [('1xDose', '2xDose'), ('1xDose', 'Control'),\r\n ('2xDose', 'Control')]\r\n ttd_vps = \\\r\n [('31', '21'), ('31', '55'), ('31', '67'), ('21', '55'),\r\n ('21', '67'), ('55', '67')]\r\n dose_sids = \\\r\n [(['Sam1', 'Sam2', 'Sam6'], ['Sam3', 'Sam4']),\r\n (['Sam1', 'Sam2', 'Sam6'], ['Sam5']),\r\n (['Sam3', 'Sam4'], ['Sam5'])]\r\n ttd_sids = \\\r\n [(['Sam1'], ['Sam3']),\r\n (['Sam1'], ['Sam4', 'Sam6']),\r\n (['Sam1'], ['Sam2', 'Sam5']),\r\n (['Sam3'], ['Sam4', 'Sam6']),\r\n (['Sam3'], ['Sam2', 'Sam5']),\r\n (['Sam4', 'Sam6'], ['Sam2', 'Sam5'])]\r\n\r\n # observed values\r\n obs_dose_sids, obs_dose_vps = sampleId_pairs(self.mapping_data,\r\n self.rarefaction_data, 'Dose')\r\n obs_ttd_sids, obs_ttd_vps = sampleId_pairs(self.mapping_data,\r\n self.rarefaction_data, 'TTD')\r\n\r\n # sort -- order is unimportant and depends on way presented in mf\r\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\r\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())\r\n self.assertEqual(ttd_vps.sort(), obs_ttd_vps.sort())\r\n self.assertEqual(ttd_sids.sort(), obs_ttd_sids.sort())\r\n\r\n # check errors when no samples had this category\r\n self.assertRaises(ValueError, sampleId_pairs, self.mapping_data,\r\n self.rarefaction_data, 'DNE')\r\n\r\n # check no error if map file has more sampleids than rarefaction data\r\n superset_mf = \\\r\n ['#SampleID\\tDose\\tLinkerPrimerSequence\\tWeight\\tTTD\\tDescription',\r\n '#Comment Line',\r\n 'Sam1\\t1xDose\\tATCG\\tHigh\\t31\\ts1_desc',\r\n 'Sam2\\t1xDose\\tACCG\\tLow\\t67\\ts2_desc',\r\n 'Sam3\\t2xDose\\tACGT\\tMed\\t21\\ts3_desc',\r\n 'Sam4\\t2xDose\\tAACG\\tLow\\t55\\ts4_desc',\r\n 'Sam5\\tControl\\tCGTC\\tLow\\t67\\ts5_desc',\r\n 'Sam6\\t1xDose\\tACCT\\tLow\\t55\\ts6_desc',\r\n 'Sam7\\t4xDose\\tACCT\\tLow\\t55\\ts7_desc',\r\n 'Sam8\\t3xDose\\tACCT\\tLow\\t55\\ts8_desc',\r\n 'Sam9\\t1xDose\\tACCT\\tLow\\t55\\ts9_desc']\r\n # (mf, comments)\r\n superset_mf = parse_mapping_file_to_dict(superset_mf)[0]\r\n obs_dose_sids, obs_dose_vps = sampleId_pairs(superset_mf,\r\n self.rarefaction_data, 'Dose')\r\n\r\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\r\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())","def test_0():\n sync.gen_multi_fake_data()#default is only one randomly selected data set\n sync.main(testing=True)","def make_row(invalid_data=[]):\n\n ### Database Identifiers ###\n \n # phac_sample_id, valid/invalid error-grid information.\n phac_sample_id, phac_sample_id_error = lib.random_phac_id(invalid_data)\n # umbrella_bioproject_accession, valid/invalid error-grid information.\n ub_accession, ub_accession_error = lib.umbrella_bioproject_accession(invalid_data)\n # bioproject_accession, valid/invalid error-grid information.\n bp_accession, bp_accession_error = lib.random_bioproject_accession(invalid_data)\n # biosample_accession, valid/invalid error-grid information.\n bs_accession, bs_accession_error = lib.random_biosample_accession(invalid_data)\n # sra_accession, valid/invalid error-grid information.\n sra_accession, sra_accession_error = lib.random_sra_accession(invalid_data)\n # genbank_accession, valid/invalid error-grid information.\n gb_accession, gb_accession_error = lib.random_genbank_accession(invalid_data)\n # gisaid_accession, valid/invalid error-grid information.\n gisaid_accession, gisaid_accession_error = lib.random_gisaid_accession(invalid_data)\n \n ### Sample Collection and Processing ###\n \n # sample_collected_by, valid/invalid error-grid information.\n samp_col_by, samp_col_by_error = lib.random_agency(invalid_data)\n # sample_collector_contact_email, valid/invalid error-grid information.\n samp_col_email, samp_col_email_error = lib.random_email(invalid_data)\n # sample_collector_contact_address, valid/invalid error-grid information.\n samp_col_address, samp_col_address_error = lib.random_address(invalid_data)\n # sequence_submitter_contact_email, valid/invalid error-grid information.\n seq_sub_email, seq_sub_email_error = lib.random_email(invalid_data)\n # sequence_submitter_contact_address, valid/invalid error-grid information.\n seq_sub_address, seq_sub_address_error = lib.random_address(invalid_data)\n # sample_collection_date, valid/invalid error-grid information.\n samp_col_date, samp_col_date_error = lib.random_date(invalid_data)\n # sample_received_date, valid/invalid error-grid information.\n samp_rec_date, samp_rec_date_error = lib.random_date(invalid_data)\n # geo_loc_name_country, valid/invalid error-grid information.\n geo_loc_country, geo_loc_country_error = lib.random_country(invalid_data)\n # geo_loc_name_province_territory, valid/invalid error-grid information.\n geo_loc_prov_ter, geo_loc_prov_ter_error = lib.random_province_territory(invalid_data)\n # geo_loc_name_city, valid/invalid error-grid information.\n geo_loc_city, geo_loc_city_error = lib.random_city(invalid_data)\n # organism, valid/invalid error-grid information.\n organism, organism_error = lib.random_organism(invalid_data)\n # purpose_of_sampling, valid/invalid error-grid information.\n p_o_sampling, p_o_sampling_error = lib.random_purpose_of_sampling(invalid_data)\n # anatomical_material, valid/invalid error-grid information.\n anat_material, anat_material_error = lib.random_anatomical_material(invalid_data)\n # anatomical_part, valid/invalid error-grid information.\n anat_part, anat_part_error = lib.random_anatomical_part(invalid_data)\n # body_product, valid/invalid error-grid information.\n body_product, body_product_error = lib.random_body_product(invalid_data)\n # environmental_material, valid/invalid error-grid information.\n envi_material, envi_material_error = lib.random_environmental_material(invalid_data)\n # environmental_site, valid/invalid error-grid information.\n envi_site, envi_site_error = lib.random_environmental_site(invalid_data)\n # collection_device, valid/invalid error-grid information.\n col_device, col_device_error = lib.random_collection_device(invalid_data)\n # collection_method, valid/invalid error-grid information.\n col_method, col_method_error = lib.random_collection_method(invalid_data)\n # collection_protocol, valid/invalid error-grid information.\n col_protocol, col_protocol_error = lib.fake_protocol(invalid_data)\n # specimen_processing, valid/invalid error-grid information.\n spec_process, spec_process_error = lib.random_specimen_processing(invalid_data)\n # lab_host, valid/invalid error-grid information.\n lab_host, lab_host_error = lib.random_lab_host(invalid_data)\n # passage_number , valid/invalid error-grid information.\n passage_num, passage_num_error = lib.random_passage_number(invalid_data)\n # passage_method, valid/invalid error-grid information.\n passage_method, passage_method_error = lib.passage_method_text(invalid_data)\n # biomaterial_extracted, valid/invalid error-grid information.\n biom_extract, biom_extract_error = lib.random_biomaterial_extracted(invalid_data)\n \n ### Host Information ###\n \n # host_common_name, valid/invalid error-grid information.\n host_com_name, host_com_name_error = lib.random_host_common_name(invalid_data)\n # host_scientific_name, valid/invalid error-grid information.\n host_sci_name, host_sci_name_error = lib.random_host_scientific_name(invalid_data)\n # host_health_state, valid/invalid error-grid information.\n host_health_state, host_health_state_error = lib.random_host_health_state(invalid_data)\n # host_health_status_details, valid/invalid error-grid information.\n host_health_status, host_health_status_error = lib.random_host_health_status_details(invalid_data)\n # host_disease, valid/invalid error-grid information.\n host_disease, host_disease_error = lib.random_host_disease(invalid_data)\n # host_age, valid/invalid error-grid information.\n host_age, host_age_error = lib.random_host_age(invalid_data)\n # host_gender, valid/invalid error-grid information.\n host_gender, host_gender_error = lib.random_host_gender(invalid_data)\n # host_origin_geo_loc_name_country, valid/invalid error-grid information.\n host_loc_country, host_loc_country_error = lib.random_country(invalid_data)\n # host_subject_id, valid/invalid error-grid information.\n host_sub_id, host_sub_id_error = lib.random_host_subject_id(invalid_data)\n # symptom_onset_date, valid/invalid error-grid information.\n symp_onset_date, symp_onset_date_error = lib.random_date(invalid_data)\n # signs_and_symptoms, valid/invalid error-grid information.\n signs_symptoms, signs_symptoms_error = lib.random_signs_symptoms(invalid_data)\n \n ### Host Exposure Information ###\n \n # location_of_exposure_geo_loc_name_country, valid/invalid error-grid information.\n loc_exp_country, loc_exp_country_error = lib.random_country(invalid_data)\n # travel_history, valid/invalid error-grid information. \n trav_history, trav_history_error = lib.random_travel_history(invalid_data)\n # exposure_event, valid/invalid error-grid information.\n exp_event, exp_event_error = lib.random_exposure_event(invalid_data)\n \n ### Sequencing ###\n \n # minion_barcode, valid/invalid error-grid information.\n minion_barcode, minion_barcode_error = lib.random_minIon_barcode(invalid_data)\n # sequencing_instrument, valid/invalid error-grid information.\n seq_instrument, seq_instrument_error = lib.random_seq_instrument(invalid_data)\n # sequencing_protocol_name, valid/invalid error-grid information.\n seq_prot_name, seq_prot_name_error = lib.fake_protocol(invalid_data)\n # sequencing_protocol_source, valid/invalid error-grid information.\n seq_prot_source, seq_prot_source_error = lib.random_seq_protocol_source(invalid_data)\n # sequencing_kit_number, valid/invalid error-grid information.\n seq_kit_num, seq_kit_num_error = lib.random_seq_kit_num(invalid_data)\n # amplicon_pcr_primers_filename, valid/invalid error-grid information.\n amp_pcr_filename, amp_pcr_filename_error = lib.random_txt_filename(invalid_data)\n \n ### Bioinformatics and QC metrics ###\n \n # raw_sequence_data_processing, valid/invalid error-grid information.\n raw_seq_process, raw_seq_process_error = lib.random_seq_process(invalid_data)\n # sequencing_depth_average, valid/invalid error-grid information.\n seq_depth_avg, seq_depth_avg_error = lib.random_seq_depth(invalid_data)\n # assembly_method, valid/invalid error-grid information.\n assemb_method, assemb_method_error = lib.random_assembly_software(invalid_data)\n # assembly_coverage_breadth, valid/invalid error-grid information.\n assemb_cov_breadth, assemb_cov_breadth_error = lib.random_assembly_coverage_breadth(invalid_data)\n # assembly_coverage_depth, valid/invalid error-grid information.\n assemb_cov_depth, assemb_cov_depth_error = lib.random_seq_depth(invalid_data)\n # r1_fastq_filename, valid/invalid error-grid information.\n r1_filename, r1_filename_error = lib.random_fastq_filename(invalid_data)\n # r2_fastq_filename, valid/invalid error-grid information.\n r2_filename, r2_filename_error = lib.random_fastq_filename(invalid_data)\n # r1_fastq_filepath, valid/invalid error-grid information.\n r1_filepath, r1_filepath_error = lib.random_filepath(r1_filename, invalid_data)\n # r2_fastq_filepath, valid/invalid error-grid information.\n r2_filepath, r2_filepath_error = lib.random_filepath(r2_filename, invalid_data)\n # fast5_filename, valid/invalid error-grid information.\n fast5_filename, fast5_filename_error = lib.random_fast5_filename(invalid_data)\n # fast5_filepath, valid/invalid error-grid information.\n fast5_filepath, fast5_filepath_error = lib.random_filepath(fast5_filename, invalid_data)\n # fasta_filename, valid/invalid error-grid information.\n fasta_filename, fasta_filename_error = lib.random_fasta_filename(invalid_data)\n # fasta_filepath, valid/invalid error-grid information.\n fasta_filepath, fasta_filepath_error = lib.random_filepath(fasta_filename, invalid_data)\n # number_base_pairs, valid/invalid error-grid information.\n num_bp, num_bp_error = lib.random_bp_num(invalid_data)\n # consensus_genome_length, valid/invalid error-grid information.\n cons_genome_len, cons_genome_len_error = lib.random_genome_length(invalid_data)\n # mean_contig_length, valid/invalid error-grid information.\n mean_contig_len, mean_contig_len_error = lib.random_contig_length(invalid_data)\n # n50, valid/invalid error-grid information.\n n50, n50_error = lib.random_n50(invalid_data)\n # ns_per_100_kbp, valid/invalid error-grid information.\n ns_100kbp, ns_100kbp_error = lib.random_ns_100kbp(invalid_data)\n # reference_genome_accession, valid/invalid error-grid information.\n ref_genome_accession, ref_genome_accession_error = lib.random_ref_genome(invalid_data)\n # consensus_sequence_id, valid/invalid error-grid information.\n cons_seq_id, cons_seq_id_error = lib.random_consensus_seq_id(invalid_data)\n # consensus_sequence_method, valid/invalid error-grid information.\n cons_seq_method, cons_seq_method_error = lib.random_consensus_seq_method(invalid_data)\n # consensus_sequence_filename, valid/invalid error-grid information.\n cons_seq_filename, cons_seq_filename_error = lib.random_fasta_filename(invalid_data)\n # consensus_sequence_filepath, valid/invalid error-grid information.\n cons_seq_filepath, cons_seq_filepath_error = lib.random_filepath(cons_seq_filename, invalid_data)\n # annotation_feature_table_filename, valid/invalid error-grid information.\n annot_table_filename, annot_table_filename_error = lib.random_feature_table_filename(invalid_data)\n # bioinformatics_protocol, valid/invalid error-grid information.\n biof_protocol, biof_protocol_error = lib.bioinformatics_protocol(invalid_data)\n \n ### Pathogen Diagnostic Testing ###\n \n # gene_name_1, valid/invalid error-grid information.\n gene_1, gene_1_error = lib.random_gene(invalid_data)\n # diagnostic_pcr_protocol_1, valid/invalid error-grid information.\n pcr_protocol_1, pcr_protocol_1_error = lib.fake_protocol(invalid_data)\n # diagnostic_pcr_ct_value_1, valid/invalid error-grid information.\n pcr_ct_1, pcr_ct_1_error = lib.random_pcr_ct_val(invalid_data)\n # gene_name_2, valid/invalid error-grid information.\n gene_2, gene_2_error = lib.random_gene(invalid_data)\n # diagnostic_pcr_protocol_2, valid/invalid error-grid information.\n pcr_protocol_2, pcr_protocol_2_error = lib.fake_protocol(invalid_data)\n # diagnostic_pcr_ct_value_2, valid/invalid error-grid information.\n pcr_ct_2, pcr_ct_2_error = lib.random_pcr_ct_val(invalid_data)\n \n ### Contributor Acknowledgement ###\n \n # authors, valid/invalid error-grid information.\n authors, authors_error = lib.authors(invalid_data)\n \n ### Dependent IDs ###\n \n # specimen_collector_sample_id.\n spec_col_sample_id, spec_col_sample_id_error = lib.random_specimen_collector_sample_id(\n geo_loc_country, \n geo_loc_prov_ter,\n geo_loc_city,\n invalid_data)\n # irida_sample_name.\n irida_sample_id = spec_col_sample_id\n # sequence_submitted_by.\n seq_sub_by = samp_col_by\n # library_id, valid/invalid error-grid information.\n library_id, library_id_error = lib.random_library_id(spec_col_sample_id, invalid_data)\n # isolate.\n isolate = spec_col_sample_id\n # assembly_name, valid/invalid error-grid information.\n assemb_name, assemb_name_error = lib.random_assembly_name(spec_col_sample_id, invalid_data)\n\n # Row of generated data organised by column.\n cols = [spec_col_sample_id,\n phac_sample_id,\n irida_sample_id,\n ub_accession,\n bp_accession,\n bs_accession,\n sra_accession,\n gb_accession,\n gisaid_accession,\n samp_col_by,\n samp_col_email,\n samp_col_address,\n seq_sub_by,\n seq_sub_email,\n seq_sub_address,\n samp_col_date,\n samp_rec_date,\n geo_loc_country,\n geo_loc_prov_ter,\n geo_loc_city,\n organism,\n isolate,\n p_o_sampling,\n anat_material,\n anat_part,\n body_product,\n envi_material,\n envi_site,\n col_device,\n col_method,\n col_protocol,\n spec_process,\n lab_host,\n passage_num,\n passage_method,\n biom_extract,\n host_com_name,\n host_sci_name,\n host_health_state,\n host_health_status,\n host_disease,\n host_age,\n host_gender,\n host_loc_country,\n host_sub_id,\n symp_onset_date,\n signs_symptoms,\n loc_exp_country,\n trav_history,\n exp_event,\n library_id,\n minion_barcode,\n seq_instrument,\n seq_prot_name,\n seq_prot_source,\n seq_kit_num,\n amp_pcr_filename,\n raw_seq_process,\n seq_depth_avg,\n assemb_name,\n assemb_method,\n assemb_cov_breadth,\n assemb_cov_depth,\n r1_filename,\n r2_filename,\n r1_filepath,\n r2_filepath,\n fast5_filename,\n fast5_filepath,\n fasta_filename,\n fasta_filepath,\n num_bp,\n cons_genome_len,\n mean_contig_len,\n n50,\n ns_100kbp,\n ref_genome_accession,\n cons_seq_id,\n cons_seq_method,\n cons_seq_filename,\n cons_seq_filepath,\n annot_table_filename,\n biof_protocol,\n gene_1,\n pcr_protocol_1,\n pcr_ct_1,\n gene_2,\n pcr_protocol_2,\n pcr_ct_2,\n authors]\n\n # Error grid valid/invalid (error specific) information.\n grid = ['-', # spec_col_sample_id_error placeholder\n phac_sample_id_error,\n '-', # irida_sample_id_error placeholder\n ub_accession_error,\n bp_accession_error,\n bs_accession_error,\n sra_accession_error,\n gb_accession_error,\n gisaid_accession_error,\n samp_col_by_error,\n samp_col_email_error,\n samp_col_address_error,\n '-', # seq_sub_by_error placeholder\n seq_sub_email_error,\n seq_sub_address_error,\n samp_col_date_error,\n samp_rec_date_error,\n geo_loc_country_error,\n geo_loc_prov_ter_error,\n geo_loc_city_error,\n organism_error,\n '-', # isolate_error placeholder\n p_o_sampling_error,\n anat_material_error,\n anat_part_error,\n body_product_error,\n envi_material_error,\n envi_site_error,\n col_device_error,\n col_method_error,\n col_protocol_error,\n spec_process_error,\n lab_host_error,\n passage_num_error,\n passage_method_error,\n biom_extract_error,\n host_com_name_error,\n host_sci_name_error,\n host_health_state_error,\n host_health_status_error,\n host_disease_error,\n host_age_error,\n host_gender_error,\n host_loc_country_error,\n host_sub_id_error,\n symp_onset_date_error,\n signs_symptoms_error,\n loc_exp_country_error,\n trav_history_error,\n exp_event_error,\n library_id_error,\n minion_barcode_error,\n seq_instrument_error,\n seq_prot_name_error,\n seq_prot_source_error,\n seq_kit_num_error,\n amp_pcr_filename_error,\n raw_seq_process_error,\n seq_depth_avg_error,\n assemb_name_error,\n assemb_method_error,\n assemb_cov_breadth_error,\n assemb_cov_depth_error,\n r1_filename_error,\n r2_filename_error,\n r1_filepath_error,\n r2_filepath_error,\n fast5_filename_error,\n fast5_filepath_error,\n fasta_filename_error,\n fasta_filepath_error,\n num_bp_error,\n cons_genome_len_error,\n mean_contig_len_error,\n n50_error,\n ns_100kbp_error,\n ref_genome_accession_error,\n cons_seq_id_error,\n cons_seq_method_error,\n cons_seq_filename_error,\n cons_seq_filepath_error,\n annot_table_filename_error,\n biof_protocol_error,\n gene_1_error,\n pcr_protocol_1_error,\n pcr_ct_1_error,\n gene_2_error,\n pcr_protocol_2_error,\n pcr_ct_2_error,\n authors_error]\n\n # return row of data for data file and row of data validity for error grid.\n return cols, grid","def test_BiplaneRegistration1(self):\n\n self.delayDisplay(\"Starting the test\")\n #\n # first, get some data\n #\n import urllib\n downloads = (\n ('http://slicer.kitware.com/midas3/download?items=5767', 'FA.nrrd', slicer.util.loadVolume),\n )\n\n for url,name,loader in downloads:\n filePath = slicer.app.temporaryPath + '/' + name\n if not os.path.exists(filePath) or os.stat(filePath).st_size == 0:\n logging.info('Requesting download %s from %s...\\n' % (name, url))\n urllib.urlretrieve(url, filePath)\n if loader:\n logging.info('Loading %s...' % (name,))\n loader(filePath)\n self.delayDisplay('Finished with download and loading')\n\n volumeNode = slicer.util.getNode(pattern=\"FA\")\n logic = BiplaneRegistrationLogic()\n self.assertIsNotNone( logic.hasImageData(volumeNode) )\n self.delayDisplay('Test passed!')","def test_spin_loop_wildcard(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N*'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def setUp(self):\r\n self.l19_data = array([\r\n [7, 1, 0, 0, 0, 0, 0, 0, 0],\r\n [4, 2, 0, 0, 0, 1, 0, 0, 0],\r\n [2, 4, 0, 0, 0, 1, 0, 0, 0],\r\n [1, 7, 0, 0, 0, 0, 0, 0, 0],\r\n [0, 8, 0, 0, 0, 0, 0, 0, 0],\r\n [0, 7, 1, 0, 0, 0, 0, 0, 0],\r\n [0, 4, 2, 0, 0, 0, 2, 0, 0],\r\n [0, 2, 4, 0, 0, 0, 1, 0, 0],\r\n [0, 1, 7, 0, 0, 0, 0, 0, 0],\r\n [0, 0, 8, 0, 0, 0, 0, 0, 0],\r\n [0, 0, 7, 1, 0, 0, 0, 0, 0],\r\n [0, 0, 4, 2, 0, 0, 0, 3, 0],\r\n [0, 0, 2, 4, 0, 0, 0, 1, 0],\r\n [0, 0, 1, 7, 0, 0, 0, 0, 0],\r\n [0, 0, 0, 8, 0, 0, 0, 0, 0],\r\n [0, 0, 0, 7, 1, 0, 0, 0, 0],\r\n [0, 0, 0, 4, 2, 0, 0, 0, 4],\r\n [0, 0, 0, 2, 4, 0, 0, 0, 1],\r\n [0, 0, 0, 1, 7, 0, 0, 0, 0]\r\n ])\r\n self.l19_sample_names = [\r\n 'sam1', 'sam2', 'sam3', 'sam4', 'sam5', 'sam6',\r\n 'sam7', 'sam8', 'sam9', 'sam_middle', 'sam11', 'sam12', 'sam13',\r\n 'sam14', 'sam15', 'sam16', 'sam17', 'sam18', 'sam19']\r\n self.l19_taxon_names = ['tax1', 'tax2', 'tax3', 'tax4', 'endbigtaxon',\r\n 'tax6', 'tax7', 'tax8', 'tax9']\r\n\r\n self.legacy_otu_table1 = legacy_otu_table1\r\n self.otu_table1 = otu_table1\r\n self.otu_table_without_leading_comment = \\\r\n otu_table_without_leading_comment\r\n self.expected_lineages1 = expected_lineages1\r\n self.taxa_summary1 = taxa_summary1\r\n self.taxa_summary1_expected = taxa_summary1_expected\r\n self.otu_table1_floats = otu_table1_floats\r\n self.files_to_remove = []\r\n self.denoiser_mapping1 = denoiser_mapping1.split('\\n')\r\n self.sam_data1 = sam_data1.split(\"\\n\")\r\n self.sam1_expected = sam1_expected","def setUp(self):\n shape = RNG.integers(5, 50)\n periods = self.periods = RNG.normal() * 3\n freq = periods / shape\n amp = RNG.normal()\n offset = RNG.normal()\n phase = (RNG.normal() - 1 / 2) * 5 / 3 * np.pi\n p_gt = self.p_gt = (amp, freq, phase, offset)\n x = self.x = np.arange(shape)\n self.data = sine(x, *p_gt)","def generate_license_plate(self, num):\n license_plate = []\n for _ in range(num):\n license_plate.append(self.fake.license_plate())\n return license_plate","def genNumID(size):\n\tid = \"\"\n\tfor i in range(size):\n\t\tid = id + selectRandomFromList(numTokens)\n\treturn id","def test_kf_id():\n\n for _ in range(1000):\n prefix = ''.join(random.sample(string.ascii_uppercase, 2))\n kf_id = kf_id_generator(prefix)()\n assert kf_id[:2] == prefix\n assert len(kf_id) == 11\n assert kf_id[2] == '_'\n\n assert 'I' not in kf_id[2:]\n assert 'L' not in kf_id[2:]\n assert 'O' not in kf_id[2:]\n assert 'U' not in kf_id[2:]\n\n assert re.search(r'^'+prefix+r'_[A-HJ-KM-NP-TV-Z0-9]{8}', kf_id)","def test_init():\n rng = NonRandom()\n seed = 5\n rng.setSeed(seed)\n wheel = Wheel(rng)\n assert len(wheel.bins) == 38\n assert wheel.rng.value == seed\n assert wheel.rng.choice(range(0, 38)) == range(\n 0, 38)[wheel.rng.value] # == seed","def test_weyl_specialize_id(self):\n a, b, c = 0.0, 0.0, 0.0\n for da, db, dc in DELTAS:\n for k1l, k1r, k2l, k2r in K1K2SB:\n k1 = np.kron(k1l.data, k1r.data)\n k2 = np.kron(k2l.data, k2r.data)\n self.check_two_qubit_weyl_specialization(\n k1 @ Ud(a + da, b + db, c + dc) @ k2,\n 0.999,\n TwoQubitWeylIdEquiv,\n {\"rz\": 4, \"ry\": 2},\n )","def test_ids(self):\n # AdapterID inherited from IOAdapter\n self.assertEqual('553713696', self.sriovs[0].id)\n self.assertEqual(1, self.sriovs[0].sriov_adap_id)\n\n self.assertEqual('553713680', self.sriovs[2].id)\n self.assertIsNone(self.sriovs[2].sriov_adap_id)","def sequence(self):\n inigen = IniGen()\n fields = algorithm_fields.algorithms['sequence']\n\n output_uuid_map = {}\n\n # set up global parameters\n algorithm_path = fields['path']\n enabled = \"True\"\n inigen.emit_global(algorithm_path, enabled)\n\n label = \"SEQ\"\n for t in ['C','L']:\n run_label = label+'_'+t\n t1Mag_label = '{0}1MAG'.format(t)\n t2Mag_label = '{0}2MAG'.format(t)\n t3Mag_label = '{0}3MAG'.format(t)\n t1Ang_label = '{0}1ANG'.format(t)\n t2Ang_label = '{0}2ANG'.format(t)\n t3Ang_label = '{0}3ANG'.format(t)\n distillate_label = \"{0}-ALL\".format(t)\n\n # header\n inigen.emit_run_header(run_label, CHUNKING, MINTIME, MAXTIME)\n\n # body\n dep_1Mag_label = t1Mag_label\n dep_1Mag_name = fields['deps'][0]\n dep_1Mag_uuid = self.uuid_map[t1Mag_label]\n\n dep_2Mag_label = t2Mag_label\n dep_2Mag_name = fields['deps'][1]\n dep_2Mag_uuid = self.uuid_map[t2Mag_label]\n\n dep_3Mag_label = t3Mag_label\n dep_3Mag_name = fields['deps'][2]\n dep_3Mag_uuid = self.uuid_map[t3Mag_label]\n\n dep_1Ang_label = t1Ang_label\n dep_1Ang_name = fields['deps'][3]\n dep_1Ang_uuid = self.uuid_map[t1Ang_label]\n\n dep_2Ang_label = t2Ang_label\n dep_2Ang_name = fields['deps'][4]\n dep_2Ang_uuid = self.uuid_map[t2Ang_label]\n\n dep_3Ang_label = t3Ang_label\n dep_3Ang_name = fields['deps'][5]\n dep_3Ang_uuid = self.uuid_map[t3Ang_label]\n \n deps = [[dep_1Mag_label, dep_1Mag_name, dep_1Mag_uuid],\n [dep_2Mag_label, dep_2Mag_name, dep_2Mag_uuid],\n [dep_3Mag_label, dep_3Mag_name, dep_3Mag_uuid],\n [dep_1Ang_label, dep_1Ang_name, dep_1Ang_uuid],\n [dep_2Ang_label, dep_2Ang_name, dep_2Ang_uuid],\n [dep_3Ang_label, dep_3Ang_name, dep_3Ang_uuid]]\n\n param_section_name = fields['params'][0]\n param_section_value = \"Production/{0}/{1}/{2}\".format(self.location, self.name, distillate_label)\n param_name_name = fields['params'][1]\n param_name_value = \"SEQ\"\n params = [[param_section_name, param_section_value], [param_name_name, param_name_value]]\n\n outputs = fields['outputs']\n\n emitted = inigen.emit_run_body(deps, params, outputs)\n\n output_uuid_map[\"ZER_{0}ANG\".format(t)] = emitted[-9][-36:]\n output_uuid_map[\"ZER_{0}MAG\".format(t)] = emitted[-8][-36:]\n output_uuid_map[\"POS_{0}ANG\".format(t)] = emitted[-7][-36:]\n output_uuid_map[\"POS_{0}MAG\".format(t)] = emitted[-6][-36:]\n output_uuid_map[\"NEG_{0}ANG\".format(t)] = emitted[-5][-36:]\n output_uuid_map[\"NEG_{0}MAG\".format(t)] = emitted[-4][-36:]\n output_uuid_map[\"UNB_{0}NEG\".format(t)] = emitted[-3][-36:]\n output_uuid_map[\"UNB_{0}ZER\".format(t)] = emitted[-2][-36:]\n\n filename = \"{0}/SEQ_{1}.ini\".format(self.dirname, self.name)\n inigen.generate_file(filename)\n return output_uuid_map","def test_periodic_boundary_two_ring_rod():\n\n n_elems = 5\n ring_rod_1 = MockRingRod(n_elems)\n ring_rod_2 = MockRingRod(n_elems)\n block_structure = MemoryBlockCosseratRod([ring_rod_1, ring_rod_2], [0, 1])\n\n correct_periodic_boundary_node_idx = np.array(\n [[0, 6, 7, 9, 15, 16], [5, 1, 2, 14, 10, 11]], dtype=np.int64\n )\n correct_periodic_boundary_elem_idx = np.array(\n [[0, 6, 9, 15], [5, 1, 14, 10]], dtype=np.int64\n )\n correct_periodic_boundary_voronoi_idx = np.array([[0, 9], [5, 14]], dtype=np.int64)\n\n assert_allclose(\n correct_periodic_boundary_node_idx,\n block_structure.periodic_boundary_nodes_idx,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_periodic_boundary_elem_idx,\n block_structure.periodic_boundary_elems_idx,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_periodic_boundary_voronoi_idx,\n block_structure.periodic_boundary_voronoi_idx,\n atol=Tolerance.atol(),\n )\n\n correct_start_node_idx = np.array([1, 10], dtype=np.int64)\n correct_end_node_idx = np.array([6, 15], dtype=np.int64)\n\n correct_start_elem_idx = np.array([1, 10], dtype=np.int64)\n correct_end_elem_idx = np.array([6, 15], dtype=np.int64)\n\n correct_start_voronoi_idx = np.array([1, 10], dtype=np.int64)\n correct_end_voronoi_idx = np.array([6, 15], dtype=np.int64)\n\n assert_allclose(\n correct_start_node_idx,\n block_structure.start_idx_in_rod_nodes,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_node_idx,\n block_structure.end_idx_in_rod_nodes,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_start_elem_idx,\n block_structure.start_idx_in_rod_elems,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_elem_idx,\n block_structure.end_idx_in_rod_elems,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_start_voronoi_idx,\n block_structure.start_idx_in_rod_voronoi,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_voronoi_idx,\n block_structure.end_idx_in_rod_voronoi,\n atol=Tolerance.atol(),\n )","def test_api_random_id(api_client, single_brew_number):\n response = api_client.get(path='/breweries' + '/' + str(single_brew_number))\n assert response.json()['id'] == single_brew_number","def generate_run_id(self):\n r_id_len = 4\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\n while r_id in self.cache:\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\n return r_id","def spinWheel():\n\tt = random.randrange(8)\n\tif t == 7:\n\t\treturn \"00\"\n\treturn str(t)","def test_periodic_boundary_one_ring_one_straight_rod():\n\n n_elems = 5\n ring_rod = MockRingRod(n_elems)\n straight_rod = MockRod(n_elems)\n block_structure = MemoryBlockCosseratRod([ring_rod, straight_rod], [0, 1])\n\n correct_periodic_boundary_node_idx = np.array(\n [[7, 13, 14], [12, 8, 9]], dtype=np.int64\n )\n correct_periodic_boundary_elem_idx = np.array([[7, 13], [12, 8]], dtype=np.int64)\n correct_periodic_boundary_voronoi_idx = np.array([[7], [12]], dtype=np.int64)\n\n assert_allclose(\n correct_periodic_boundary_node_idx,\n block_structure.periodic_boundary_nodes_idx,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_periodic_boundary_elem_idx,\n block_structure.periodic_boundary_elems_idx,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_periodic_boundary_voronoi_idx,\n block_structure.periodic_boundary_voronoi_idx,\n atol=Tolerance.atol(),\n )\n\n correct_start_node_idx = np.array([0, 8], dtype=np.int64)\n correct_end_node_idx = np.array([6, 13], dtype=np.int64)\n\n correct_start_elem_idx = np.array([0, 8], dtype=np.int64)\n correct_end_elem_idx = np.array([5, 13], dtype=np.int64)\n\n correct_start_voronoi_idx = np.array([0, 8], dtype=np.int64)\n correct_end_voronoi_idx = np.array([4, 13], dtype=np.int64)\n\n assert_allclose(\n correct_start_node_idx,\n block_structure.start_idx_in_rod_nodes,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_node_idx,\n block_structure.end_idx_in_rod_nodes,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_start_elem_idx,\n block_structure.start_idx_in_rod_elems,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_elem_idx,\n block_structure.end_idx_in_rod_elems,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_start_voronoi_idx,\n block_structure.start_idx_in_rod_voronoi,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_voronoi_idx,\n block_structure.end_idx_in_rod_voronoi,\n atol=Tolerance.atol(),\n )","def test_generate_mine_sequence(self):\n mine_list = utils.generate_mine_sequence(1)\n self.assertEqual(len(mine_list), utils.MINE_COUNT)"],"string":"[\n \"def test_generate_spin_id_data_array6(self):\\n\\n # The data.\\n data = ['1', 'GLY', None, None]\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\\n\\n # Test the string.\\n self.assertEqual(id, ':1')\",\n \"def test_generate_spin_id_data_array2(self):\\n\\n # The data.\\n data = ['1', 'GLY', '234', 'NH']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2, spin_num_col=3, spin_name_col=4)\\n\\n # Test the string.\\n self.assertEqual(id, ':1@234')\",\n \"def test_generate_spin_id_data_array5(self):\\n\\n # The data.\\n data = ['Ap4Aase', '1', 'GLY', '234', 'NH']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5)\\n\\n # Test the string.\\n self.assertEqual(id, '#Ap4Aase:1@234')\",\n \"def test_generate_spin_id_data_array4(self):\\n\\n # The data.\\n data = ['Ap4Aase', '1', 'GLY']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3)\\n\\n # Test the string.\\n self.assertEqual(id, '#Ap4Aase:1')\",\n \"def test_generate_spin_id_data_array3(self):\\n\\n # The data.\\n data = ['Ap4Aase', '234', 'NH']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=None, res_name_col=None, spin_num_col=2, spin_name_col=3)\\n\\n # Test the string.\\n self.assertEqual(id, '#Ap4Aase@234')\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_id_array(self):\\n arr = vtk.vtkIdTypeArray()\\n arr.SetNumberOfTuples(10)\\n for i in range(10):\\n arr.SetValue(i, i)\\n\\n np = array_handler.vtk2array(arr)\\n self.assertEqual(numpy.all(np == range(10)), True)\",\n \"def test_create_template(self):\\n m_size = 10\\n data = ecn.IDData(m_size)\\n self.assertEqual(np.shape(data.ID_MATRIX), (m_size, m_size))\\n self.assertEqual(sum(sum(data.ID_MATRIX)), m_size)\\n self.assertTrue((sum(data.ID_MATRIX) == np.ones(m_size)).all())\\n print('Finished testing template\\\\n')\",\n \"def test_random_id(self):\\r\\n ids = \\\\\\r\\n \\\"R27DLI_4812 R27DLI_600 R27DLI_727 U1PLI_403 U1PLI_8969\\\".split(\\r\\n )\\r\\n assert random_id(ids, {}) in ids\\r\\n # just test we got something from the list, don't add stochastic test\\r\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def createArrayFunc(self):\\r\\n minVal = int(self.spinBoxMin_2.value())\\r\\n maxVal = int(self.spinBoxMax_2.value())\\r\\n arrayLength = int(self.spinBoxLength_2.value())\\r\\n different = maxVal - minVal\\r\\n if self.checkBoxNoRepeate_2.isChecked():\\r\\n if different > arrayLength:\\r\\n def unique_rand(initial, limit, total):\\r\\n data = []\\r\\n i = 0\\r\\n while i < total:\\r\\n number = numpy.random.randint(initial, limit)\\r\\n if number not in data:\\r\\n data.append(number)\\r\\n i += 1\\r\\n return data\\r\\n\\r\\n self.UnsortedArray_2 = unique_rand(minVal, maxVal, arrayLength)\\r\\n else:\\r\\n err = \\\"Array length must be greater than difference between limits\\\"\\r\\n self.labelUnsortedArray_2.setText(str(err))\\r\\n\\r\\n else:\\r\\n self.UnsortedArray_2 = numpy.random.randint(minVal, maxVal, arrayLength)\\r\\n self.labelUnsortedArray_2.setText(str(self.UnsortedArray_2))\\r\\n self.SortedArray_2 = Insertion.sorting(self.UnsortedArray_2)\\r\\n self.labelSortedArray_2.setText(str(self.SortedArray_2))\\r\\n binaryMax = int(self.spinBoxMax_2.value())\\r\\n binaryMin = int(self.spinBoxMin_2.value())\\r\\n self.spinBoxBinary.setMaximum(binaryMax)\\r\\n self.spinBoxBinary.setMinimum(binaryMin)\\r\\n self.spinBoxIthSmallest.setMaximum(arrayLength + 1)\",\n \"def test_spin_loop(self):\\n\\n # Spin data.\\n select = [1, 0]\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, 'N5')\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 2)\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_spin_type(get_pdos_generator_inputs):\\n with pytest.raises(NotImplementedError):\\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=spin_type)\\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=SpinType.COLLINEAR)\\n for namespace in [builder.scf, builder.nscf]:\\n parameters = namespace['pw']['parameters'].get_dict()\\n assert parameters['SYSTEM']['nspin'] == 2\\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}\",\n \"def test_scan_id_list(self):\\n scan = '15,17'\\n ref_idx = [0,3]\\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_spin_loop_no_selection(self):\\n\\n # Spin data.\\n select = [0, 1, 0, 0, 1, 1, 0, 1]\\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 8)\",\n \"def test_create_tornado_id(self):\\n\\n this_id_string = tornado_io.create_tornado_id(\\n start_time_unix_sec=TORNADO_START_TIME_UNIX_SEC,\\n start_latitude_deg=TORNADO_START_LATITUDE_DEG,\\n start_longitude_deg=TORNADO_START_LONGITUDE_DEG)\\n\\n self.assertTrue(this_id_string == TORNADO_ID_STRING)\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_spin_type(fixture_code, generate_structure):\\n code = fixture_code('quantumespresso.pw')\\n structure = generate_structure()\\n\\n with pytest.raises(NotImplementedError):\\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\\n PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=spin_type)\\n\\n builder = PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=SpinType.COLLINEAR)\\n\\n for namespace in [builder.relax['base'], builder.scf, builder.bands]:\\n parameters = namespace['pw']['parameters'].get_dict()\\n assert parameters['SYSTEM']['nspin'] == 2\\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}\",\n \"def test_pol_id_list(self):\\n pol = '0,1'\\n ref_idx = []\\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_arr2vtkIdList(self):\\n a = [1, 2, 3, 4, 5]\\n p = array_handler.array2vtkIdList(a)\\n for i, j in enumerate(a): \\n self.assertEqual(p.GetId(i), j)\\n p = vtk.vtkIdList()\\n ident = id(p)\\n p = array_handler.array2vtkIdList(numpy.array(a), p)\\n for i, j in enumerate(a): \\n self.assertEqual(p.GetId(i), j)\\n self.assertEqual(id(p), ident)\\n \\n self.assertRaises(AssertionError, array_handler.array2vtkIdList,\\n [[1,2,3]])\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def _get_rand_array(self):\\n pass\",\n \"def test_004_init(self):\\n self.assertIsInstance(rawdata.rawdata(\\\"id\\\",testRawdata.ioc,testRawdata.sam),rawdata.rawdata)\",\n \"def test_generateuuids(self):\\n ret1 = {\\\"message\\\": \\\"No Random.org api key or api version found.\\\", \\\"res\\\": False}\\n self.assertDictEqual(random_org.generateUUIDs(), ret1)\\n\\n ret2 = {\\\"message\\\": \\\"Required argument, number is missing.\\\", \\\"res\\\": False}\\n self.assertDictEqual(\\n random_org.generateUUIDs(api_key=\\\"peW\\\", api_version=\\\"1\\\"), ret2\\n )\\n\\n ret3 = {\\\"message\\\": \\\"Number of UUIDs must be between 1 and 1000\\\", \\\"res\\\": False}\\n self.assertDictEqual(\\n random_org.generateUUIDs(api_key=\\\"peW\\\", api_version=\\\"1\\\", number=\\\"5\\\"), ret3\\n )\\n\\n ret3 = {\\\"message\\\": \\\"Parameter 'apiKey' is malformed\\\", \\\"res\\\": False}\\n self.assertDictEqual(\\n random_org.generateUUIDs(api_key=\\\"peW\\\", api_version=\\\"1\\\", number=5), ret3\\n )\",\n \"def test_scan_id_range(self):\\n scan = '16~17'\\n ref_idx = [1,2,3]\\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def test_random_integers(self):\\r\\n # Check over two calls to see if the random state is correctly updated.\\r\\n m = Module()\\r\\n m.random = RandomStreams(utt.fetch_seed())\\r\\n m.fn = Method([], m.random.random_integers((20,20), -5, 5))\\r\\n\\r\\n made = m.make()\\r\\n made.random.initialize()\\r\\n fn_val0 = made.fn()\\r\\n fn_val1 = made.fn()\\r\\n\\r\\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\\r\\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\\r\\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\\r\\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\\r\\n\\r\\n assert numpy.all(fn_val0 == numpy_val0)\\r\\n assert numpy.all(fn_val1 == numpy_val1)\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_id_rot():\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_axis_angle(pr.a_id))\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_quaternion(pr.q_id))\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_xyz(pr.e_xyz_id))\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_zyx(pr.e_zyx_id))\",\n \"def gen_data(min_coord, max_coord, size):\\r\\n data = np.random.randint(min_coord, max_coord, size)\\r\\n return data\",\n \"def test_init():\\n mesh = CuboidMesh(nx=100, ny=1, nz=1)\\n sim = Sim(mesh)\\n sim.set_m(init_m)\\n\\n expected = np.array([0, 0, 1,\\n 0, np.sin(0.1), np.cos(0.1)])\\n\\n assert max(abs(sim.spin[:6] - expected)) < 1e-15\",\n \"def _spin_sequence(self):\\n self.return_position = self.motor.position\\n \\n for spin_num in range(self.num_spins):\\n self.taxi()\\n\\n det_pre_acquire(self.detector)\\n self.fly()\\n det_post_acquire(self.detector)\\n\\n while self.detector.hdf1.write_file.value:\\n time.sleep(0.01) # wait for file to be written\\n\\n event = OrderedDict()\\n event[\\\"time\\\"] = time.time()\\n event[\\\"seq_num\\\"] = spin_num + 1\\n event[\\\"data\\\"] = {}\\n event[\\\"timestamps\\\"] = {}\\n for d_item in (self.detector.hdf1.full_file_name,):\\n d = d_item.read()\\n for k, v in d.items():\\n event['data'][k] = v['value']\\n event['timestamps'][k] = v['timestamp']\\n\\n self._data.append(event)\\n\\n self.set(\\\"Return\\\")\\n self._completion_status._finished(success=True)\",\n \"def _apply_array_spin123(self,\\n h1e: 'Nparray',\\n h2e: 'Nparray',\\n h3e: 'Nparray',\\n dvec: Optional[Tuple['Nparray', 'Nparray']] = None,\\n evec: Optional[Tuple['Nparray', 'Nparray', 'Nparray', 'Nparray']] \\\\\\n = None) -> 'Nparray':\\n norb = self.norb()\\n assert h3e.shape == (norb * 2,) * 6\\n assert not (dvec is None) ^ (evec is None)\\n\\n from1234 = (dvec is not None) and (evec is not None)\\n\\n nh1e = numpy.copy(h1e)\\n nh2e = numpy.copy(h2e)\\n\\n for i in range(norb * 2):\\n for j in range(norb * 2):\\n for k in range(norb * 2):\\n nh2e[j, k, :, :] += (-h3e[k, j, i, i, :, :] -\\n h3e[j, i, k, i, :, :] -\\n h3e[j, k, i, :, i, :])\\n\\n nh1e[:, :] += h3e[:, i, j, i, j, :]\\n\\n out = self._apply_array_spin12_halffilling(nh1e, nh2e)\\n\\n n = norb # This is just shorter\\n if not from1234:\\n symfac = 2.0\\n axes = ((1, 3), (0, 1))\\n (odveca, odvecb) = self.calculate_dvec_spin()\\n dveca = numpy.zeros_like(odveca)\\n dvecb = numpy.zeros_like(odvecb)\\n\\n for i in range(norb):\\n for j in range(norb):\\n evecaa, _ = self._calculate_dvec_spin_with_coeff(\\n odveca[i, j, :, :])\\n evecab, evecbb = self._calculate_dvec_spin_with_coeff(\\n odvecb[i, j, :, :])\\n\\n dveca += numpy.tensordot(h3e[:n, :n, i, :n, :n, j],\\n evecaa,\\n axes=axes)\\n dveca += numpy.tensordot(h3e[:n, :n, n + i, :n, :n, n + j],\\n evecab,\\n axes=axes) * symfac\\n dveca += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\\n evecbb,\\n axes=axes)\\n\\n dvecb += numpy.tensordot(h3e[n:, :n, i, n:, :n, j],\\n evecaa,\\n axes=axes)\\n dvecb += numpy.tensordot(h3e[n:, :n, n + i, n:, :n, n + j],\\n evecab,\\n axes=axes) * symfac\\n dvecb += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\\n evecbb,\\n axes=axes)\\n else:\\n symfac = 1.0\\n axes = ((1, 4, 2, 5), (0, 1, 2, 3)) # type: ignore\\n dveca, dvecb = dvec # type: ignore\\n evecaa, evecab, evecba, evecbb = evec # type: ignore\\n\\n dveca = numpy.tensordot(h3e[:n, :n, :n, :n, :n, :n],\\n evecaa, axes=axes) \\\\\\n + numpy.tensordot(h3e[:n, :n, n:, :n, :n, n:],\\n evecab, axes=axes) * symfac \\\\\\n + numpy.tensordot(h3e[:n, n:, n:, :n, n:, n:],\\n evecbb, axes=axes) + \\\\\\n + numpy.tensordot(h3e[:n, n:, :n, :n, n:, :n],\\n evecba, axes=axes)\\n\\n dvecb = numpy.tensordot(h3e[n:, :n, :n, n:, :n, :n],\\n evecaa, axes=axes) \\\\\\n + numpy.tensordot(h3e[n:, :n, n:, n:, :n, n:],\\n evecab, axes=axes) * symfac \\\\\\n + numpy.tensordot(h3e[n:, n:, n:, n:, n:, n:],\\n evecbb, axes=axes) + \\\\\\n + numpy.tensordot(h3e[n:, n:, :n, n:, n:, :n],\\n evecba, axes=axes)\\n\\n out -= self._calculate_coeff_spin_with_dvec((dveca, dvecb))\\n return out\",\n \"def test_id_get(mocker):\\n mocker.patch('serial.Serial.open')\\n mocker.patch('serial.Serial.flushInput')\\n css = mocker.patch('pysds011.driver.SDS011.cmd_set_sleep')\\n css.return_value = True\\n cfv = mocker.patch('pysds011.driver.SDS011.cmd_firmware_ver')\\n cfv.return_value = {'id': b'\\\\x12\\\\x34', 'paperino': 'maciomicio'}\\n runner = CliRunner()\\n result = runner.invoke(main, ['id'])\\n\\n calls = [call(0, id=b'\\\\xff\\\\xff'), call(1, id=b'\\\\xff\\\\xff')]\\n css.assert_has_calls(calls, any_order=False)\\n\\n assert '12' in result.output and '34' in result.output\\n assert result.exit_code == 0\",\n \"def test_CreateROI1(self):\\r\\n\\r\\n self.delayDisplay(\\\"Starting the test\\\")\\r\\n #\\r\\n # first, get some data\\r\\n #\\r\\n import urllib\\r\\n downloads = (\\r\\n ('http://slicer.kitware.com/midas3/download?items=5767', 'FA.nrrd', slicer.util.loadVolume),\\r\\n )\\r\\n\\r\\n for url,name,loader in downloads:\\r\\n filePath = slicer.app.temporaryPath + '/' + name\\r\\n if not os.path.exists(filePath) or os.stat(filePath).st_size == 0:\\r\\n logging.info('Requesting download %s from %s...\\\\n' % (name, url))\\r\\n urllib.urlretrieve(url, filePath)\\r\\n if loader:\\r\\n logging.info('Loading %s...' % (name,))\\r\\n loader(filePath)\\r\\n self.delayDisplay('Finished with download and loading')\\r\\n\\r\\n volumeNode = slicer.util.getNode(pattern=\\\"FA\\\")\\r\\n logic = CreateROILogic()\\r\\n self.assertIsNotNone( logic.hasImageData(volumeNode) )\\r\\n self.delayDisplay('Test passed!')\",\n \"def test_main(data, tmp_path):\\n\\n main(data, tmp_path)\\n\\n FILES = (\\n \\\"gd32f888x(0-1)xx-pinctrl.h\\\",\\n \\\"gd32f888x(2-3)xx-pinctrl.h\\\",\\n \\\"gd32f888y(0-1)xx-pinctrl.h\\\",\\n \\\"gd32f999x(0-1)xx-pinctrl.h\\\",\\n \\\"gd32f999x(2-3)xx-pinctrl.h\\\",\\n \\\"gd32f999y(0-1)xx-pinctrl.h\\\",\\n )\\n\\n for file in FILES:\\n ref_file = data / file\\n gen_file = tmp_path / file\\n\\n assert gen_file.exists()\\n\\n with open(ref_file) as ref, open(gen_file) as gen:\\n assert ref.read() == gen.read()\",\n \"def test_split_id_otp(self):\\n public_id, otp, = pyhsm.yubikey.split_id_otp(\\\"ft\\\" * 16)\\n self.assertEqual(public_id, '')\\n self.assertEqual(otp, \\\"ft\\\" * 16)\\n\\n public_id, otp, = pyhsm.yubikey.split_id_otp(\\\"cc\\\" + \\\"ft\\\" * 16)\\n self.assertEqual(public_id, 'cc')\\n self.assertEqual(otp, \\\"ft\\\" * 16)\",\n \"def test_brains_id_get(self):\\n pass\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def test_uuid():\\n for _ in range(1000):\\n uuid = uuid_generator()\\n assert len(uuid) == 36\\n assert uuid.count('-') == 4\",\n \"def _generate_id() -> str:\\n return \\\"\\\".join(sample(\\\"abcdefghjkmopqrstuvqxyz\\\", 16))\",\n \"def generate_raiz():\\n\\treturn os.urandom(12)\",\n \"def test_random_integers(self):\\r\\n # Check over two calls to see if the random state is correctly updated.\\r\\n random = RandomStreams(utt.fetch_seed())\\r\\n fn = function([], random.random_integers((20, 20), -5, 5))\\r\\n fn_val0 = fn()\\r\\n fn_val1 = fn()\\r\\n\\r\\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\\r\\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\\r\\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\\r\\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\\r\\n\\r\\n assert numpy.all(fn_val0 == numpy_val0)\\r\\n assert numpy.all(fn_val1 == numpy_val1)\",\n \"def test_pol_id_range(self):\\n pol = '0~1'\\n ref_idx = []\\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_run_sim():\\n rnd = rand.Arrivals(31, 40)\\n sim.run_sim(2, 1, 3, 4, 24, rnd)\",\n \"def test_run_sim_1():\\n rnd = rand.Arrivals(36, 41)\\n sim.run_sim(3, 2, 5, 6, 22, rnd)\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_get_ids(civic, main_data, updated_data):\\n assert len(civic._get_ids(main_data['assertions'])) == 0\\n assert len(civic._get_ids(main_data['variants'])) == 1\\n assert len(civic._get_ids(main_data['genes'])) == 2\\n assert len(civic._get_ids(main_data['evidence'])) == 1\\n\\n assert len(civic._get_ids(updated_data['assertions'])) == 1\\n assert len(civic._get_ids(updated_data['variants'])) == 1\\n assert len(civic._get_ids(updated_data['genes'])) == 1\\n assert len(civic._get_ids(updated_data['evidence'])) == 1\",\n \"def test_seqgen(fprime_test_api):\\n sequence = Path(__file__).parent / \\\"test_seq.seq\\\"\\n assert (\\n subprocess.run(\\n [\\n \\\"fprime-seqgen\\\",\\n \\\"-d\\\",\\n str(fprime_test_api.pipeline.dictionary_path),\\n str(sequence),\\n \\\"/tmp/ref_test_int.bin\\\",\\n ]\\n ).returncode\\n == 0\\n ), \\\"Failed to run fprime-seqgen\\\"\\n fprime_test_api.send_and_assert_command(\\n \\\"cmdSeq.CS_RUN\\\", args=[\\\"/tmp/ref_test_int.bin\\\", \\\"BLOCK\\\"], max_delay=5\\n )\",\n \"def test_id_set(mocker):\\n mocker.patch('serial.Serial.open')\\n mocker.patch('serial.Serial.flushInput')\\n css = mocker.patch('pysds011.driver.SDS011.cmd_set_sleep')\\n css.return_value = True\\n csi = mocker.patch('pysds011.driver.SDS011.cmd_set_id')\\n runner = CliRunner()\\n result = runner.invoke(main, ['--id', 'cccc', 'id', 'abcd'])\\n\\n # Two calls to cmd_set_sleep:\\n # the first use original address\\n # at the second one, the sensor has a new address: so sleep\\n # has the use the new one\\n calls = [call(0, id=b'\\\\xcc\\\\xcc'), call(1, id=b'\\\\xab\\\\xcd')]\\n css.assert_has_calls(calls, any_order=False)\\n csi.assert_called_once_with(id=b'\\\\xcc\\\\xcc', new_id=b'\\\\xab\\\\xcd')\\n assert result.exit_code == 0\",\n \"def test_first_id(self):\\r\\n ids = \\\\\\r\\n \\\"R27DLI_4812 R27DLI_600 R27DLI_727 U1PLI_403 U1PLI_8969\\\".split(\\r\\n )\\r\\n self.assertEqual(first_id(ids, {}), 'R27DLI_4812')\",\n \"def test_generate(self):\\n cant_interations = int(random()*100)\\n for i in range(cant_interations):\\n number = self.sudoku.generate() # Generate number\\n self.assertGreaterEqual(number, 0) # number >= 0\\n self.assertLessEqual(number, 8) # number <= 8\",\n \"def myID() -> np.int:\\r\\n return 304976335\",\n \"def myID() -> np.int:\\r\\n return 304976335\",\n \"def test_get_tid():\\n tids = []\\n def _foo():\\n mytid = yield GetTid()\\n tids.append(mytid)\\n for i in range(5):\\n yield i\\n\\n scheduler = Scheduler()\\n scheduler.new(_foo())\\n scheduler.new(_foo())\\n scheduler.mainloop()\\n\\n # can we do better than hard code?\\n assert tids == [4, 5]\",\n \"def test_return_spin_pipe_fail(self):\\n\\n # Try to get a spin from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')\",\n \"def test_ipam_rirs_create(self):\\n pass\",\n \"def test_start_ids_10(self):\\n\\n\\t\\texpected_num_layers = 11\\n\\t\\texpected_ids = np.arange(10,21)\\n\\t\\t# test describe\\n\\t\\tdetails = self.watcher.describe(start_ids=10)\\n\\t\\tprint(\\\"start id = 10\\\", details)\\n\\t\\tactual_ids = details.layer_id.to_numpy().tolist()\\n\\t\\tself.assertTrue(np.array_equal(actual_ids, expected_ids))\\n\\t\\tself.assertEqual(len(expected_ids), expected_num_layers)\\n\\t\\t\\t\\t\\n\\t\\treturn\",\n \"def test_periodic_boundary_one_ring_rod():\\n\\n n_elems = 5\\n ring_rod = MockRingRod(n_elems)\\n block_structure = MemoryBlockCosseratRod([ring_rod], [0])\\n\\n correct_periodic_boundary_node_idx = np.array(\\n [[0, 6, 7], [5, 1, 2]], dtype=np.int64\\n )\\n correct_periodic_boundary_elem_idx = np.array([[0, 6], [5, 1]], dtype=np.int64)\\n correct_periodic_boundary_voronoi_idx = np.array([[0], [5]], dtype=np.int64)\\n\\n assert_allclose(\\n correct_periodic_boundary_node_idx,\\n block_structure.periodic_boundary_nodes_idx,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_periodic_boundary_elem_idx,\\n block_structure.periodic_boundary_elems_idx,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_periodic_boundary_voronoi_idx,\\n block_structure.periodic_boundary_voronoi_idx,\\n atol=Tolerance.atol(),\\n )\\n\\n correct_start_node_idx = np.array([1], dtype=np.int64)\\n correct_end_node_idx = np.array([6], dtype=np.int64)\\n\\n correct_start_elem_idx = np.array([1], dtype=np.int64)\\n correct_end_elem_idx = np.array([6], dtype=np.int64)\\n\\n correct_start_voronoi_idx = np.array([1], dtype=np.int64)\\n correct_end_voronoi_idx = np.array([6], dtype=np.int64)\\n\\n assert_allclose(\\n correct_start_node_idx,\\n block_structure.start_idx_in_rod_nodes,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_node_idx,\\n block_structure.end_idx_in_rod_nodes,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_start_elem_idx,\\n block_structure.start_idx_in_rod_elems,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_elem_idx,\\n block_structure.end_idx_in_rod_elems,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_start_voronoi_idx,\\n block_structure.start_idx_in_rod_voronoi,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_voronoi_idx,\\n block_structure.end_idx_in_rod_voronoi,\\n atol=Tolerance.atol(),\\n )\",\n \"def test_id(self):\\n b1 = Base()\\n self.assertEqual(b1.id, 1)\\n b2 = Base()\\n self.assertEqual(b2.id, 2)\\n b3 = Base(98)\\n self.assertEqual(b3.id, 98)\\n b4 = Base(256)\\n self.assertEqual(b4.id, 256)\\n b5 = Base()\\n self.assertEqual(b5.id, 3)\\n b6 = Base(-98)\\n self.assertEqual(b6.id, -98)\\n b7 = Base(None)\\n self.assertEqual(b7.id, 4)\\n b8 = Base(4.4)\\n self.assertEqual(b8.id, 4.4)\",\n \"def generate_T(number_obeservations):\\n T = np.random.randint(0, 2, (number_obeservations,1))\\n return T\",\n \"def test_slepp_get_at_id(mocker):\\n mocker.patch('serial.Serial.open')\\n mocker.patch('serial.Serial.flushInput')\\n cgs = mocker.patch('pysds011.driver.SDS011.cmd_get_sleep')\\n runner = CliRunner()\\n result = runner.invoke(main, ['--id', 'ABCD', 'sleep'])\\n cgs.assert_called_once_with(id=b'\\\\xab\\\\xcd')\\n\\n assert result.exit_code == 0\",\n \"def generate_fake_data(t0, num_array, period=5820, data_range=[0.0, 24.0],\\n cyclic=True):\\n\\n if cyclic:\\n uts_root = np.mod(t0, period)\\n data = (np.mod(uts_root + num_array, period)\\n * (np.diff(data_range)[0] / np.float64(period))) + data_range[0]\\n else:\\n data = ((t0 + num_array) / period).astype(int)\\n\\n return data\",\n \"def test_test_ids_request(get_interface_params):\\n from sail_on_client.protocol.localinterface import LocalInterface\\n\\n config_directory, config_name = get_interface_params\\n data_dir = f\\\"{os.path.dirname(__file__)}/data\\\"\\n local_interface = LocalInterface(config_name, config_directory)\\n\\n assumptions_path = os.path.join(os.path.dirname(__file__), \\\"assumptions.json\\\")\\n filename = local_interface.test_ids_request(\\n \\\"OND\\\", \\\"image_classification\\\", \\\"5678\\\", assumptions_path\\n )\\n expected = os.path.join(data_dir, \\\"OND\\\", \\\"image_classification\\\", \\\"test_ids.csv\\\")\\n assert os.stat(expected).st_size > 5\\n assert expected == filename\",\n \"def test_correct_binid(self):\\n\\n maps = Maps(plateifu='8485-1901', release='DR17', bintype='HYB10')\\n spaxel = maps[22, 14]\\n\\n assert isinstance(spaxel, Spaxel)\\n assert spaxel.x == 14, spaxel.y == 22\\n\\n bin_spaxels = spaxel.stellar_vel.bin.get_bin_spaxels()\\n\\n for sp in bin_spaxels:\\n\\n sp.load()\\n assert sp.stellar_vel.bin.binid == spaxel.stellar_vel.bin.binid\\n\\n sp_bin = maps[sp.y, sp.x]\\n assert sp_bin.stellar_vel.bin.binid == spaxel.stellar_vel.bin.binid\",\n \"def test_random_generator(self):\\n gen = random_data()\\n data = [next(gen) for _ in range(100)]\\n self.assertEqual(len(data), 100)\",\n \"def test_SampleIds(self):\\r\\n exp = [\\\"PC.354\\\", \\\"PC.355\\\", \\\"PC.356\\\", \\\"PC.481\\\", \\\"PC.593\\\", \\\"PC.607\\\",\\r\\n \\\"PC.634\\\", \\\"PC.635\\\", \\\"PC.636\\\"]\\r\\n obs = self.overview_map.SampleIds\\r\\n self.assertEqual(obs, exp)\\r\\n\\r\\n obs = self.no_metadata.SampleIds\\r\\n self.assertEqual(obs, exp)\\r\\n\\r\\n obs = self.empty_map.SampleIds\\r\\n self.assertEqual(obs, [])\",\n \"def test_SampleIds(self):\\n exp = [\\\"PC.354\\\", \\\"PC.355\\\", \\\"PC.356\\\", \\\"PC.481\\\", \\\"PC.593\\\", \\\"PC.607\\\",\\n \\\"PC.634\\\", \\\"PC.635\\\", \\\"PC.636\\\"]\\n obs = self.overview_map.SampleIds\\n self.assertEqual(obs, exp)\\n\\n obs = self.no_metadata.SampleIds\\n self.assertEqual(obs, exp)\\n\\n obs = self.empty_map.SampleIds\\n self.assertEqual(obs, [])\",\n \"def next():\\n iraw = 0\\n run = 0\\n seqno = 0\\n with db_connection() as conn:\\n with conn.cursor() as curs:\\n try:\\n curs.execute(\\\"\\\"\\\"SELECT rawdata.id,rawdata.run,rawdata.seqno,\\n slices.block1,slices.block2,\\n jobs.cluster,jobs.process\\n FROM rawdata\\n LEFT JOIN bindings\\n ON bindings.iraw = rawdata.id\\n INNER JOIN slices\\n ON slices.iraw = rawdata.id\\n LEFT JOIN jobs\\n ON slices.ijob = jobs.id\\n AND jobs.exitcode = 0\\n WHERE bindings.id IS NULL\\n ORDER BY rawdata.id,slices.block1\\n LIMIT 2000;\\n \\\"\\\"\\\")\\n slices_missing = 1\\n for row in curs.fetchall():\\n i = int(row[0])\\n if i != iraw:\\n if slices_missing == 0:\\n break\\n else:\\n run = int(row[1])\\n seqno = int(row[2])\\n slices_missing = 0\\n slices = []\\n iraw = i\\n block1 = int(row[3])\\n block2 = int(row[4])\\n if row[5] is not None and row[6] is not None:\\n cluster = int(row[5])\\n process = int(row[6])\\n slices.append((block1,block2,cluster,process))\\n else:\\n print(\\\"slices missing on\\\", row[5], row[6])\\n slices_missing += 1\\n if slices_missing:\\n return 0\\n else:\\n curs.execute(\\\"SELECT TIMEZONE('GMT', NOW());\\\")\\n now = curs.fetchone()[0]\\n curs.execute(\\\"\\\"\\\"INSERT INTO bindings\\n (iraw,starttime)\\n VALUES (%s,%s)\\n RETURNING id;\\n \\\"\\\"\\\", (iraw, now))\\n row = curs.fetchone()\\n if row:\\n ibind = int(row[0])\\n else:\\n return 0\\n except:\\n iraw = 0\\n if iraw == 0:\\n time.sleep(random.randint(1,30))\\n return -9 # collision\\n\\n workdir = str(iraw)\\n os.mkdir(workdir)\\n os.chdir(workdir)\\n badslices = []\\n for sl in slices:\\n sdir = str(sl[0]) + \\\",\\\" + str(sl[1])\\n os.mkdir(sdir)\\n tarfile = \\\"job_{0}_{1}.tar.gz\\\".format(sl[2], sl[3])\\n tarpath = input_area + \\\"/\\\" + tarfile\\n try:\\n subprocess.check_output([\\\"gfal-copy\\\", src_url + tarpath,\\n \\\"file://\\\" + os.getcwd() + \\\"/\\\" + tarfile])\\n except:\\n sys.stderr.write(\\\"Error -999 on rawdata id {0}\\\".format(iraw) +\\n \\\" - job output \\\" + tarfile + \\\" is missing!\\\\n\\\")\\n sys.stderr.flush()\\n badslices.append(sdir)\\n continue\\n try:\\n subprocess.check_output([\\\"tar\\\", \\\"zxf\\\", tarfile, \\\"-C\\\", sdir])\\n except:\\n sys.stderr.write(\\\"Error -999 on rawdata id {0}\\\".format(iraw) +\\n \\\" - job output \\\" + tarfile + \\\" is not readable!\\\\n\\\")\\n sys.stderr.flush()\\n badslices.append(sdir)\\n finally:\\n os.remove(tarfile)\\n if len(badslices) > 0:\\n with db_connection() as conn:\\n with conn.cursor() as curs:\\n curs.execute(\\\"SELECT TIMEZONE('GMT', NOW());\\\")\\n now = curs.fetchone()[0]\\n curs.execute(\\\"\\\"\\\"UPDATE bindings\\n SET endtime=%s, \\n exitcode=%s,\\n details=%s\\n WHERE id = %s;\\n \\\"\\\"\\\", (now, -999, \\\":\\\".join(badslices), ibind))\\n os.chdir(\\\"..\\\")\\n shutil.rmtree(workdir)\\n return 1\\n\\n badslices += merge_evio_skims(run, seqno, slices)\\n badslices += merge_hddm_output(run, seqno, slices)\\n badslices += merge_job_info(run, seqno, slices)\\n badslices += merge_root_histos(run, seqno, slices)\\n exitcode = -len(badslices)\\n with db_connection() as comm:\\n with conn.cursor() as curs:\\n curs.execute(\\\"SELECT TIMEZONE('GMT', NOW());\\\")\\n now = curs.fetchone()[0]\\n curs.execute(\\\"\\\"\\\"UPDATE bindings\\n SET endtime=%s,\\n exitcode=%s,\\n details=%s\\n WHERE id = %s;\\n \\\"\\\"\\\", (now, exitcode, \\\":\\\".join(badslices), ibind))\\n os.chdir(\\\"..\\\")\\n shutil.rmtree(workdir)\\n return 1\",\n \"def generate_client_volgen_data(data):\\n\\n # No of distribute groups in a volume\\n dist_grp_count = 0\\n # No of storage units in a distribute group\\n storage_unit_count = 0\\n replica_count = 0\\n arbiter_count = 0\\n\\n get_replica_count = {\\n \\\"Replica1\\\" : 1,\\n \\\"Replica2\\\" : 2,\\n \\\"Replica3\\\" : 3\\n }\\n\\n if data[\\\"type\\\"] == \\\"Disperse\\\":\\n storage_unit_count = data[\\\"disperse\\\"][\\\"data\\\"] + data[\\\"disperse\\\"][\\\"redundancy\\\"]\\n replica_count = 0\\n elif \\\"Replica\\\" in data[\\\"type\\\"]:\\n storage_unit_count = replica_count = get_replica_count.get(data[\\\"type\\\"], \\\"\\\")\\n elif data[\\\"type\\\"] == \\\"Arbiter\\\":\\n storage_unit_count = replica_count = 3\\n arbiter_count = 1\\n\\n client_data = {}\\n client_data[\\\"name\\\"] = data[\\\"volname\\\"]\\n client_data[\\\"id\\\"] = data[\\\"volume_id\\\"]\\n\\n dist_grp_count = int((len(data[\\\"bricks\\\"]) / storage_unit_count))\\n client_data[\\\"distribute_groups\\\"] = [{} for _ in range(dist_grp_count)]\\n\\n for dist_grp_idx, dist_grp in enumerate(client_data[\\\"distribute_groups\\\"]):\\n if \\\"Replica\\\" in data[\\\"type\\\"]:\\n dist_grp[\\\"type\\\"] = \\\"replicate\\\"\\n elif \\\"Disperse\\\" in data[\\\"type\\\"]:\\n dist_grp[\\\"type\\\"] = \\\"disperse\\\"\\n else:\\n dist_grp[\\\"type\\\"] = \\\"arbiter\\\"\\n\\n if replica_count:\\n dist_grp[\\\"replica_count\\\"] = replica_count\\n if arbiter_count:\\n dist_grp[\\\"arbiter_count\\\"] = arbiter_count\\n if dist_grp[\\\"type\\\"] == \\\"disperse\\\":\\n dist_grp[\\\"disperse_count\\\"] = data[\\\"disperse\\\"].get(\\\"data\\\", 0)\\n dist_grp[\\\"redundancy_count\\\"] = data[\\\"disperse\\\"].get(\\\"redundancy\\\", 0)\\n\\n dist_grp[\\\"storage_units\\\"] = [{} for _ in range(storage_unit_count)]\\n\\n for storage_unit_idx, storage_unit in enumerate(dist_grp[\\\"storage_units\\\"]):\\n brick_idx = (dist_grp_idx * storage_unit_count + storage_unit_idx)\\n storage_unit[\\\"path\\\"] = data[\\\"bricks\\\"][brick_idx].get(\\\"brick_path\\\", \\\"\\\")\\n storage_unit[\\\"port\\\"] = 24007\\n storage_unit[\\\"node\\\"] = {\\n \\\"name\\\" : data[\\\"bricks\\\"][brick_idx].get(\\\"node\\\", \\\"\\\"),\\n \\\"id\\\" : data[\\\"bricks\\\"][brick_idx].get(\\\"node_id\\\", \\\"\\\")\\n }\\n\\n return client_data\",\n \"def generateUniqueId(context):\\n\\n fn_normalize = getUtility(IFileNameNormalizer).normalize\\n id_normalize = getUtility(IIDNormalizer).normalize\\n prefixes = context.bika_setup.getPrefixes()\\n\\n year = context.bika_setup.getYearInPrefix() and \\\\\\n DateTime().strftime(\\\"%Y\\\")[2:] or ''\\n separator = '-'\\n for e in prefixes:\\n if 'separator' not in e:\\n e['separator'] = ''\\n if e['portal_type'] == context.portal_type:\\n separator = e['separator']\\n # Analysis Request IDs\\n if context.portal_type == \\\"AnalysisRequest\\\":\\n sample = context.getSample()\\n s_prefix = fn_normalize(sample.getSampleType().getPrefix())\\n sample_padding = context.bika_setup.getSampleIDPadding()\\n ar_padding = context.bika_setup.getARIDPadding()\\n sample_id = sample.getId()\\n sample_number = sample_id.split(s_prefix)[1]\\n ar_number = sample.getLastARNumber()\\n ar_number = ar_number and ar_number + 1 or 1\\n\\n return fn_normalize(\\n (\\\"%s%s\\\" + separator + \\\"R%s\\\") % (s_prefix,\\n str(sample_number).zfill(sample_padding),\\n str(ar_number).zfill(ar_padding))\\n )\\n\\n # Sample Partition IDs\\n if context.portal_type == \\\"SamplePartition\\\":\\n # We do not use prefixes. There are actually codes that require the 'P'.\\n # matches = [p for p in prefixes if p['portal_type'] == 'SamplePartition']\\n # prefix = matches and matches[0]['prefix'] or 'samplepartition'\\n # padding = int(matches and matches[0]['padding'] or '0')\\n\\n # at this time the part exists, so +1 would be 1 too many\\n partnr = str(len(context.aq_parent.objectValues('SamplePartition')))\\n # parent id is normalized already\\n return (\\\"%s\\\" + separator + \\\"P%s\\\") % (context.aq_parent.id, partnr)\\n\\n if context.bika_setup.getExternalIDServer():\\n\\n # if using external server\\n\\n for d in prefixes:\\n # Sample ID comes from SampleType\\n if context.portal_type == \\\"Sample\\\":\\n prefix = context.getSampleType().getPrefix()\\n padding = context.bika_setup.getSampleIDPadding()\\n new_id = str(idserver_generate_id(context, \\\"%s%s-\\\" % (prefix, year)))\\n if padding:\\n new_id = new_id.zfill(int(padding))\\n return ('%s%s' + separator + '%s') % (prefix, year, new_id)\\n elif d['portal_type'] == context.portal_type:\\n prefix = d['prefix']\\n padding = d['padding']\\n new_id = str(idserver_generate_id(context, \\\"%s%s-\\\" % (prefix, year)))\\n if padding:\\n new_id = new_id.zfill(int(padding))\\n return ('%s%s' + separator + '%s') % (prefix, year, new_id)\\n # no prefix; use portal_type\\n # year is not inserted here\\n # portal_type is be normalized to lowercase\\n npt = id_normalize(context.portal_type)\\n new_id = str(idserver_generate_id(context, npt + \\\"-\\\"))\\n return ('%s' + separator + '%s') % (npt, new_id)\\n\\n else:\\n\\n # No external id-server.\\n\\n def next_id(prefix):\\n # normalize before anything\\n prefix = fn_normalize(prefix)\\n plone = context.portal_url.getPortalObject()\\n # grab the first catalog we are indexed in.\\n at = getToolByName(plone, 'archetype_tool')\\n if context.portal_type in at.catalog_map:\\n catalog_name = at.catalog_map[context.portal_type][0]\\n else:\\n catalog_name = 'portal_catalog'\\n catalog = getToolByName(plone, catalog_name)\\n\\n # get all IDS that start with prefix\\n # this must specifically exclude AR IDs (two -'s)\\n rr = re.compile(\\\"^\\\"+prefix+separator+\\\"[\\\\d+]+$\\\")\\n ids = [int(i.split(prefix+separator)[1]) \\\\\\n for i in catalog.Indexes['id'].uniqueValues() \\\\\\n if rr.match(i)]\\n\\n #plone_tool = getToolByName(context, 'plone_utils')\\n #if not plone_tool.isIDAutoGenerated(l.id):\\n ids.sort()\\n _id = ids and ids[-1] or 0\\n new_id = _id + 1\\n\\n return str(new_id)\\n\\n for d in prefixes:\\n if context.portal_type == \\\"Sample\\\":\\n # Special case for Sample IDs\\n prefix = fn_normalize(context.getSampleType().getPrefix())\\n padding = context.bika_setup.getSampleIDPadding()\\n sequence_start = context.bika_setup.getSampleIDSequenceStart()\\n new_id = next_id(prefix+year)\\n # If sequence_start is greater than new_id. Set\\n # sequence_start as new_id. (Jira LIMS-280)\\n if sequence_start > int(new_id):\\n new_id = str(sequence_start)\\n if padding:\\n new_id = new_id.zfill(int(padding))\\n return ('%s%s' + separator + '%s') % (prefix, year, new_id)\\n elif d['portal_type'] == context.portal_type:\\n prefix = d['prefix']\\n padding = d['padding']\\n sequence_start = d.get(\\\"sequence_start\\\", None)\\n new_id = next_id(prefix+year)\\n # Jira-tracker LIMS-280\\n if sequence_start and int(sequence_start) > int(new_id):\\n new_id = str(sequence_start)\\n if padding:\\n new_id = new_id.zfill(int(padding))\\n return ('%s%s' + separator + '%s') % (prefix, year, new_id)\\n\\n if context.portal_type == \\\"StorageUnit\\\":\\n if context.getStorageUnitID():\\n return context.getStorageUnitID()\\n\\n if context.portal_type == \\\"StorageManagement\\\":\\n prefix = ''\\n if context.getType() == \\\"Freeze\\\":\\n prefix = \\\"FZ\\\"\\n elif context.getType() == \\\"Tank\\\":\\n prefix = \\\"LN\\\"\\n\\n if context.aq_parent.portal_type == \\\"StorageUnit\\\":\\n padding = 3\\n year = DateTime().strftime(\\\"%Y\\\")[2:]\\n new_id = next_id(prefix + year)\\n if padding:\\n new_id = new_id.zfill(int(padding))\\n return ('%s%s' + '-' + '%s') % (prefix, year, new_id)\\n else:\\n l = context.Title().split(' ')\\n if len(l) == 2:\\n return l[1]\\n elif len(l) == 1:\\n return l[0]\\n \\n return context.Title().replace(' ', '')\\n\\n if context.portal_type == \\\"StorageInventory\\\":\\n prefix = 'INV'\\n parent = context.aq_parent\\n new_id = next_id(prefix)\\n\\n if parent.portal_type == \\\"StorageUnit\\\":\\n new_id = new_id.zfill(int(3))\\n return ('%s' + '-' + '%s') % (prefix, new_id)\\n\\n elif parent.portal_type == \\\"StorageInventory\\\":\\n room = context.aq_parent.aq_parent\\n return room.id + '.' + parent.id + '.' + context.Title()\\n\\n else:\\n raise AssertionError(\\\"Unknown Portal type\\\")\\n\\n if context.portal_type == \\\"Kit\\\":\\n prefix = context.getPrefix() and context.getPrefix() or \\\"KIT\\\"\\n padding = 3\\n new_id = next_id(prefix)\\n if padding:\\n new_id = new_id.zfill(int(padding))\\n\\n return ('%s' + '-' + '%s') % (prefix, new_id)\\n\\n if context.portal_type == \\\"StorageLocation\\\":\\n return context.Title()\\n\\n if context.portal_type == \\\"Aliquot\\\":\\n # subject = context.getSubjectID()\\n # prefix = subject + '-SP' if subject else 'SP'\\n prefix = 'AL'\\n padding = 3\\n new_id = next_id(prefix)\\n if padding:\\n new_id = new_id.zfill(int(padding))\\n\\n return ('%s' + '-' + '%s') % (prefix, new_id)\\n\\n if context.portal_type == \\\"Biospecimen\\\":\\n prefix = \\\"BS\\\"\\n padding = 3\\n new_id = next_id(prefix)\\n if padding:\\n new_id = new_id.zfill(int(padding))\\n\\n return ('%s' + '-' + '%s') % (prefix, new_id)\\n\\n # no prefix; use portal_type\\n # no year inserted here\\n # use \\\"IID\\\" normalizer, because we want portal_type to be lowercased.\\n prefix = id_normalize(context.portal_type)\\n new_id = next_id(prefix)\\n return ('%s' + separator + '%s') % (prefix, new_id)\",\n \"def generateRegistrationId():\\n regId = KeyHelper.getRandomSequence()\\n return regId\",\n \"def test_acquire_sample(self):\\n self.assert_initialize_driver()\\n self.assert_particle_generation(ProtocolEvent.ACQUIRE_SAMPLE, DataParticleType.METBK_PARSED, self.assert_data_particle_sample)\",\n \"def test__get_slurm_jobid(self):\\n \\n # Mock the system calls\\n subprocess.check_output = Mock(return_value='')\\n # Assert that getting non-existing jobs return an empty job list\\n self.assertListEqual([],sq.get_slurm_jobid(\\\"jobname\\\"),\\n \\\"Querying for jobid of non-existing job should return an empty list\\\")\\n # Assert that a returned job id is parsed correctly\\n for jobids in [[123456789],[123456789,987654321]]:\\n subprocess.check_output = Mock(return_value=\\\"\\\\n\\\".join([str(jid) for jid in jobids]))\\n self.assertListEqual(jobids,sq.get_slurm_jobid(\\\"jobname\\\"),\\n \\\"Querying for jobid of existing job did not return the correct value\\\")\",\n \"def test_setup(sim):\\n n = 3\\n data = []\\n dt = 1\\n\\n for i in range(n):\\n sim.setup(timestep=dt, min_delay=dt)\\n p = sim.Population(1, sim.IF_curr_exp(i_offset=0.1))\\n p.record('v')\\n print('starting run ', i)\\n sim.run(10.0)\\n print('finished run ', i)\\n\\n print('start get_data run ', i)\\n data.append(p.get_data())\\n print('finished get_data run ', i)\\n\\n print('start sim end ', i)\\n sim.end()\\n print('finished sim end ', i)\\n\\n assert len(data) == n\\n for block in data:\\n assert len(block.segments) == 1\\n signals = block.segments[0].analogsignals\\n assert len(signals) == 1\\n assert_array_equal(signals[0], data[0].segments[0].analogsignals[0])\",\n \"def test_returned_num_in_random_nums(self):\\n self._setup_random_gen([1.], [42])\\n self.assertEqual(self._random_gen.next_num(), 42)\",\n \"def test_sampleId_pairs(self):\\r\\n # expected values\\r\\n dose_vps = \\\\\\r\\n [('1xDose', '2xDose'), ('1xDose', 'Control'),\\r\\n ('2xDose', 'Control')]\\r\\n ttd_vps = \\\\\\r\\n [('31', '21'), ('31', '55'), ('31', '67'), ('21', '55'),\\r\\n ('21', '67'), ('55', '67')]\\r\\n dose_sids = \\\\\\r\\n [(['Sam1', 'Sam2', 'Sam6'], ['Sam3', 'Sam4']),\\r\\n (['Sam1', 'Sam2', 'Sam6'], ['Sam5']),\\r\\n (['Sam3', 'Sam4'], ['Sam5'])]\\r\\n ttd_sids = \\\\\\r\\n [(['Sam1'], ['Sam3']),\\r\\n (['Sam1'], ['Sam4', 'Sam6']),\\r\\n (['Sam1'], ['Sam2', 'Sam5']),\\r\\n (['Sam3'], ['Sam4', 'Sam6']),\\r\\n (['Sam3'], ['Sam2', 'Sam5']),\\r\\n (['Sam4', 'Sam6'], ['Sam2', 'Sam5'])]\\r\\n\\r\\n # observed values\\r\\n obs_dose_sids, obs_dose_vps = sampleId_pairs(self.mapping_data,\\r\\n self.rarefaction_data, 'Dose')\\r\\n obs_ttd_sids, obs_ttd_vps = sampleId_pairs(self.mapping_data,\\r\\n self.rarefaction_data, 'TTD')\\r\\n\\r\\n # sort -- order is unimportant and depends on way presented in mf\\r\\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\\r\\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())\\r\\n self.assertEqual(ttd_vps.sort(), obs_ttd_vps.sort())\\r\\n self.assertEqual(ttd_sids.sort(), obs_ttd_sids.sort())\\r\\n\\r\\n # check errors when no samples had this category\\r\\n self.assertRaises(ValueError, sampleId_pairs, self.mapping_data,\\r\\n self.rarefaction_data, 'DNE')\\r\\n\\r\\n # check no error if map file has more sampleids than rarefaction data\\r\\n superset_mf = \\\\\\r\\n ['#SampleID\\\\tDose\\\\tLinkerPrimerSequence\\\\tWeight\\\\tTTD\\\\tDescription',\\r\\n '#Comment Line',\\r\\n 'Sam1\\\\t1xDose\\\\tATCG\\\\tHigh\\\\t31\\\\ts1_desc',\\r\\n 'Sam2\\\\t1xDose\\\\tACCG\\\\tLow\\\\t67\\\\ts2_desc',\\r\\n 'Sam3\\\\t2xDose\\\\tACGT\\\\tMed\\\\t21\\\\ts3_desc',\\r\\n 'Sam4\\\\t2xDose\\\\tAACG\\\\tLow\\\\t55\\\\ts4_desc',\\r\\n 'Sam5\\\\tControl\\\\tCGTC\\\\tLow\\\\t67\\\\ts5_desc',\\r\\n 'Sam6\\\\t1xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts6_desc',\\r\\n 'Sam7\\\\t4xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts7_desc',\\r\\n 'Sam8\\\\t3xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts8_desc',\\r\\n 'Sam9\\\\t1xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts9_desc']\\r\\n # (mf, comments)\\r\\n superset_mf = parse_mapping_file_to_dict(superset_mf)[0]\\r\\n obs_dose_sids, obs_dose_vps = sampleId_pairs(superset_mf,\\r\\n self.rarefaction_data, 'Dose')\\r\\n\\r\\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\\r\\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())\",\n \"def test_0():\\n sync.gen_multi_fake_data()#default is only one randomly selected data set\\n sync.main(testing=True)\",\n \"def make_row(invalid_data=[]):\\n\\n ### Database Identifiers ###\\n \\n # phac_sample_id, valid/invalid error-grid information.\\n phac_sample_id, phac_sample_id_error = lib.random_phac_id(invalid_data)\\n # umbrella_bioproject_accession, valid/invalid error-grid information.\\n ub_accession, ub_accession_error = lib.umbrella_bioproject_accession(invalid_data)\\n # bioproject_accession, valid/invalid error-grid information.\\n bp_accession, bp_accession_error = lib.random_bioproject_accession(invalid_data)\\n # biosample_accession, valid/invalid error-grid information.\\n bs_accession, bs_accession_error = lib.random_biosample_accession(invalid_data)\\n # sra_accession, valid/invalid error-grid information.\\n sra_accession, sra_accession_error = lib.random_sra_accession(invalid_data)\\n # genbank_accession, valid/invalid error-grid information.\\n gb_accession, gb_accession_error = lib.random_genbank_accession(invalid_data)\\n # gisaid_accession, valid/invalid error-grid information.\\n gisaid_accession, gisaid_accession_error = lib.random_gisaid_accession(invalid_data)\\n \\n ### Sample Collection and Processing ###\\n \\n # sample_collected_by, valid/invalid error-grid information.\\n samp_col_by, samp_col_by_error = lib.random_agency(invalid_data)\\n # sample_collector_contact_email, valid/invalid error-grid information.\\n samp_col_email, samp_col_email_error = lib.random_email(invalid_data)\\n # sample_collector_contact_address, valid/invalid error-grid information.\\n samp_col_address, samp_col_address_error = lib.random_address(invalid_data)\\n # sequence_submitter_contact_email, valid/invalid error-grid information.\\n seq_sub_email, seq_sub_email_error = lib.random_email(invalid_data)\\n # sequence_submitter_contact_address, valid/invalid error-grid information.\\n seq_sub_address, seq_sub_address_error = lib.random_address(invalid_data)\\n # sample_collection_date, valid/invalid error-grid information.\\n samp_col_date, samp_col_date_error = lib.random_date(invalid_data)\\n # sample_received_date, valid/invalid error-grid information.\\n samp_rec_date, samp_rec_date_error = lib.random_date(invalid_data)\\n # geo_loc_name_country, valid/invalid error-grid information.\\n geo_loc_country, geo_loc_country_error = lib.random_country(invalid_data)\\n # geo_loc_name_province_territory, valid/invalid error-grid information.\\n geo_loc_prov_ter, geo_loc_prov_ter_error = lib.random_province_territory(invalid_data)\\n # geo_loc_name_city, valid/invalid error-grid information.\\n geo_loc_city, geo_loc_city_error = lib.random_city(invalid_data)\\n # organism, valid/invalid error-grid information.\\n organism, organism_error = lib.random_organism(invalid_data)\\n # purpose_of_sampling, valid/invalid error-grid information.\\n p_o_sampling, p_o_sampling_error = lib.random_purpose_of_sampling(invalid_data)\\n # anatomical_material, valid/invalid error-grid information.\\n anat_material, anat_material_error = lib.random_anatomical_material(invalid_data)\\n # anatomical_part, valid/invalid error-grid information.\\n anat_part, anat_part_error = lib.random_anatomical_part(invalid_data)\\n # body_product, valid/invalid error-grid information.\\n body_product, body_product_error = lib.random_body_product(invalid_data)\\n # environmental_material, valid/invalid error-grid information.\\n envi_material, envi_material_error = lib.random_environmental_material(invalid_data)\\n # environmental_site, valid/invalid error-grid information.\\n envi_site, envi_site_error = lib.random_environmental_site(invalid_data)\\n # collection_device, valid/invalid error-grid information.\\n col_device, col_device_error = lib.random_collection_device(invalid_data)\\n # collection_method, valid/invalid error-grid information.\\n col_method, col_method_error = lib.random_collection_method(invalid_data)\\n # collection_protocol, valid/invalid error-grid information.\\n col_protocol, col_protocol_error = lib.fake_protocol(invalid_data)\\n # specimen_processing, valid/invalid error-grid information.\\n spec_process, spec_process_error = lib.random_specimen_processing(invalid_data)\\n # lab_host, valid/invalid error-grid information.\\n lab_host, lab_host_error = lib.random_lab_host(invalid_data)\\n # passage_number , valid/invalid error-grid information.\\n passage_num, passage_num_error = lib.random_passage_number(invalid_data)\\n # passage_method, valid/invalid error-grid information.\\n passage_method, passage_method_error = lib.passage_method_text(invalid_data)\\n # biomaterial_extracted, valid/invalid error-grid information.\\n biom_extract, biom_extract_error = lib.random_biomaterial_extracted(invalid_data)\\n \\n ### Host Information ###\\n \\n # host_common_name, valid/invalid error-grid information.\\n host_com_name, host_com_name_error = lib.random_host_common_name(invalid_data)\\n # host_scientific_name, valid/invalid error-grid information.\\n host_sci_name, host_sci_name_error = lib.random_host_scientific_name(invalid_data)\\n # host_health_state, valid/invalid error-grid information.\\n host_health_state, host_health_state_error = lib.random_host_health_state(invalid_data)\\n # host_health_status_details, valid/invalid error-grid information.\\n host_health_status, host_health_status_error = lib.random_host_health_status_details(invalid_data)\\n # host_disease, valid/invalid error-grid information.\\n host_disease, host_disease_error = lib.random_host_disease(invalid_data)\\n # host_age, valid/invalid error-grid information.\\n host_age, host_age_error = lib.random_host_age(invalid_data)\\n # host_gender, valid/invalid error-grid information.\\n host_gender, host_gender_error = lib.random_host_gender(invalid_data)\\n # host_origin_geo_loc_name_country, valid/invalid error-grid information.\\n host_loc_country, host_loc_country_error = lib.random_country(invalid_data)\\n # host_subject_id, valid/invalid error-grid information.\\n host_sub_id, host_sub_id_error = lib.random_host_subject_id(invalid_data)\\n # symptom_onset_date, valid/invalid error-grid information.\\n symp_onset_date, symp_onset_date_error = lib.random_date(invalid_data)\\n # signs_and_symptoms, valid/invalid error-grid information.\\n signs_symptoms, signs_symptoms_error = lib.random_signs_symptoms(invalid_data)\\n \\n ### Host Exposure Information ###\\n \\n # location_of_exposure_geo_loc_name_country, valid/invalid error-grid information.\\n loc_exp_country, loc_exp_country_error = lib.random_country(invalid_data)\\n # travel_history, valid/invalid error-grid information. \\n trav_history, trav_history_error = lib.random_travel_history(invalid_data)\\n # exposure_event, valid/invalid error-grid information.\\n exp_event, exp_event_error = lib.random_exposure_event(invalid_data)\\n \\n ### Sequencing ###\\n \\n # minion_barcode, valid/invalid error-grid information.\\n minion_barcode, minion_barcode_error = lib.random_minIon_barcode(invalid_data)\\n # sequencing_instrument, valid/invalid error-grid information.\\n seq_instrument, seq_instrument_error = lib.random_seq_instrument(invalid_data)\\n # sequencing_protocol_name, valid/invalid error-grid information.\\n seq_prot_name, seq_prot_name_error = lib.fake_protocol(invalid_data)\\n # sequencing_protocol_source, valid/invalid error-grid information.\\n seq_prot_source, seq_prot_source_error = lib.random_seq_protocol_source(invalid_data)\\n # sequencing_kit_number, valid/invalid error-grid information.\\n seq_kit_num, seq_kit_num_error = lib.random_seq_kit_num(invalid_data)\\n # amplicon_pcr_primers_filename, valid/invalid error-grid information.\\n amp_pcr_filename, amp_pcr_filename_error = lib.random_txt_filename(invalid_data)\\n \\n ### Bioinformatics and QC metrics ###\\n \\n # raw_sequence_data_processing, valid/invalid error-grid information.\\n raw_seq_process, raw_seq_process_error = lib.random_seq_process(invalid_data)\\n # sequencing_depth_average, valid/invalid error-grid information.\\n seq_depth_avg, seq_depth_avg_error = lib.random_seq_depth(invalid_data)\\n # assembly_method, valid/invalid error-grid information.\\n assemb_method, assemb_method_error = lib.random_assembly_software(invalid_data)\\n # assembly_coverage_breadth, valid/invalid error-grid information.\\n assemb_cov_breadth, assemb_cov_breadth_error = lib.random_assembly_coverage_breadth(invalid_data)\\n # assembly_coverage_depth, valid/invalid error-grid information.\\n assemb_cov_depth, assemb_cov_depth_error = lib.random_seq_depth(invalid_data)\\n # r1_fastq_filename, valid/invalid error-grid information.\\n r1_filename, r1_filename_error = lib.random_fastq_filename(invalid_data)\\n # r2_fastq_filename, valid/invalid error-grid information.\\n r2_filename, r2_filename_error = lib.random_fastq_filename(invalid_data)\\n # r1_fastq_filepath, valid/invalid error-grid information.\\n r1_filepath, r1_filepath_error = lib.random_filepath(r1_filename, invalid_data)\\n # r2_fastq_filepath, valid/invalid error-grid information.\\n r2_filepath, r2_filepath_error = lib.random_filepath(r2_filename, invalid_data)\\n # fast5_filename, valid/invalid error-grid information.\\n fast5_filename, fast5_filename_error = lib.random_fast5_filename(invalid_data)\\n # fast5_filepath, valid/invalid error-grid information.\\n fast5_filepath, fast5_filepath_error = lib.random_filepath(fast5_filename, invalid_data)\\n # fasta_filename, valid/invalid error-grid information.\\n fasta_filename, fasta_filename_error = lib.random_fasta_filename(invalid_data)\\n # fasta_filepath, valid/invalid error-grid information.\\n fasta_filepath, fasta_filepath_error = lib.random_filepath(fasta_filename, invalid_data)\\n # number_base_pairs, valid/invalid error-grid information.\\n num_bp, num_bp_error = lib.random_bp_num(invalid_data)\\n # consensus_genome_length, valid/invalid error-grid information.\\n cons_genome_len, cons_genome_len_error = lib.random_genome_length(invalid_data)\\n # mean_contig_length, valid/invalid error-grid information.\\n mean_contig_len, mean_contig_len_error = lib.random_contig_length(invalid_data)\\n # n50, valid/invalid error-grid information.\\n n50, n50_error = lib.random_n50(invalid_data)\\n # ns_per_100_kbp, valid/invalid error-grid information.\\n ns_100kbp, ns_100kbp_error = lib.random_ns_100kbp(invalid_data)\\n # reference_genome_accession, valid/invalid error-grid information.\\n ref_genome_accession, ref_genome_accession_error = lib.random_ref_genome(invalid_data)\\n # consensus_sequence_id, valid/invalid error-grid information.\\n cons_seq_id, cons_seq_id_error = lib.random_consensus_seq_id(invalid_data)\\n # consensus_sequence_method, valid/invalid error-grid information.\\n cons_seq_method, cons_seq_method_error = lib.random_consensus_seq_method(invalid_data)\\n # consensus_sequence_filename, valid/invalid error-grid information.\\n cons_seq_filename, cons_seq_filename_error = lib.random_fasta_filename(invalid_data)\\n # consensus_sequence_filepath, valid/invalid error-grid information.\\n cons_seq_filepath, cons_seq_filepath_error = lib.random_filepath(cons_seq_filename, invalid_data)\\n # annotation_feature_table_filename, valid/invalid error-grid information.\\n annot_table_filename, annot_table_filename_error = lib.random_feature_table_filename(invalid_data)\\n # bioinformatics_protocol, valid/invalid error-grid information.\\n biof_protocol, biof_protocol_error = lib.bioinformatics_protocol(invalid_data)\\n \\n ### Pathogen Diagnostic Testing ###\\n \\n # gene_name_1, valid/invalid error-grid information.\\n gene_1, gene_1_error = lib.random_gene(invalid_data)\\n # diagnostic_pcr_protocol_1, valid/invalid error-grid information.\\n pcr_protocol_1, pcr_protocol_1_error = lib.fake_protocol(invalid_data)\\n # diagnostic_pcr_ct_value_1, valid/invalid error-grid information.\\n pcr_ct_1, pcr_ct_1_error = lib.random_pcr_ct_val(invalid_data)\\n # gene_name_2, valid/invalid error-grid information.\\n gene_2, gene_2_error = lib.random_gene(invalid_data)\\n # diagnostic_pcr_protocol_2, valid/invalid error-grid information.\\n pcr_protocol_2, pcr_protocol_2_error = lib.fake_protocol(invalid_data)\\n # diagnostic_pcr_ct_value_2, valid/invalid error-grid information.\\n pcr_ct_2, pcr_ct_2_error = lib.random_pcr_ct_val(invalid_data)\\n \\n ### Contributor Acknowledgement ###\\n \\n # authors, valid/invalid error-grid information.\\n authors, authors_error = lib.authors(invalid_data)\\n \\n ### Dependent IDs ###\\n \\n # specimen_collector_sample_id.\\n spec_col_sample_id, spec_col_sample_id_error = lib.random_specimen_collector_sample_id(\\n geo_loc_country, \\n geo_loc_prov_ter,\\n geo_loc_city,\\n invalid_data)\\n # irida_sample_name.\\n irida_sample_id = spec_col_sample_id\\n # sequence_submitted_by.\\n seq_sub_by = samp_col_by\\n # library_id, valid/invalid error-grid information.\\n library_id, library_id_error = lib.random_library_id(spec_col_sample_id, invalid_data)\\n # isolate.\\n isolate = spec_col_sample_id\\n # assembly_name, valid/invalid error-grid information.\\n assemb_name, assemb_name_error = lib.random_assembly_name(spec_col_sample_id, invalid_data)\\n\\n # Row of generated data organised by column.\\n cols = [spec_col_sample_id,\\n phac_sample_id,\\n irida_sample_id,\\n ub_accession,\\n bp_accession,\\n bs_accession,\\n sra_accession,\\n gb_accession,\\n gisaid_accession,\\n samp_col_by,\\n samp_col_email,\\n samp_col_address,\\n seq_sub_by,\\n seq_sub_email,\\n seq_sub_address,\\n samp_col_date,\\n samp_rec_date,\\n geo_loc_country,\\n geo_loc_prov_ter,\\n geo_loc_city,\\n organism,\\n isolate,\\n p_o_sampling,\\n anat_material,\\n anat_part,\\n body_product,\\n envi_material,\\n envi_site,\\n col_device,\\n col_method,\\n col_protocol,\\n spec_process,\\n lab_host,\\n passage_num,\\n passage_method,\\n biom_extract,\\n host_com_name,\\n host_sci_name,\\n host_health_state,\\n host_health_status,\\n host_disease,\\n host_age,\\n host_gender,\\n host_loc_country,\\n host_sub_id,\\n symp_onset_date,\\n signs_symptoms,\\n loc_exp_country,\\n trav_history,\\n exp_event,\\n library_id,\\n minion_barcode,\\n seq_instrument,\\n seq_prot_name,\\n seq_prot_source,\\n seq_kit_num,\\n amp_pcr_filename,\\n raw_seq_process,\\n seq_depth_avg,\\n assemb_name,\\n assemb_method,\\n assemb_cov_breadth,\\n assemb_cov_depth,\\n r1_filename,\\n r2_filename,\\n r1_filepath,\\n r2_filepath,\\n fast5_filename,\\n fast5_filepath,\\n fasta_filename,\\n fasta_filepath,\\n num_bp,\\n cons_genome_len,\\n mean_contig_len,\\n n50,\\n ns_100kbp,\\n ref_genome_accession,\\n cons_seq_id,\\n cons_seq_method,\\n cons_seq_filename,\\n cons_seq_filepath,\\n annot_table_filename,\\n biof_protocol,\\n gene_1,\\n pcr_protocol_1,\\n pcr_ct_1,\\n gene_2,\\n pcr_protocol_2,\\n pcr_ct_2,\\n authors]\\n\\n # Error grid valid/invalid (error specific) information.\\n grid = ['-', # spec_col_sample_id_error placeholder\\n phac_sample_id_error,\\n '-', # irida_sample_id_error placeholder\\n ub_accession_error,\\n bp_accession_error,\\n bs_accession_error,\\n sra_accession_error,\\n gb_accession_error,\\n gisaid_accession_error,\\n samp_col_by_error,\\n samp_col_email_error,\\n samp_col_address_error,\\n '-', # seq_sub_by_error placeholder\\n seq_sub_email_error,\\n seq_sub_address_error,\\n samp_col_date_error,\\n samp_rec_date_error,\\n geo_loc_country_error,\\n geo_loc_prov_ter_error,\\n geo_loc_city_error,\\n organism_error,\\n '-', # isolate_error placeholder\\n p_o_sampling_error,\\n anat_material_error,\\n anat_part_error,\\n body_product_error,\\n envi_material_error,\\n envi_site_error,\\n col_device_error,\\n col_method_error,\\n col_protocol_error,\\n spec_process_error,\\n lab_host_error,\\n passage_num_error,\\n passage_method_error,\\n biom_extract_error,\\n host_com_name_error,\\n host_sci_name_error,\\n host_health_state_error,\\n host_health_status_error,\\n host_disease_error,\\n host_age_error,\\n host_gender_error,\\n host_loc_country_error,\\n host_sub_id_error,\\n symp_onset_date_error,\\n signs_symptoms_error,\\n loc_exp_country_error,\\n trav_history_error,\\n exp_event_error,\\n library_id_error,\\n minion_barcode_error,\\n seq_instrument_error,\\n seq_prot_name_error,\\n seq_prot_source_error,\\n seq_kit_num_error,\\n amp_pcr_filename_error,\\n raw_seq_process_error,\\n seq_depth_avg_error,\\n assemb_name_error,\\n assemb_method_error,\\n assemb_cov_breadth_error,\\n assemb_cov_depth_error,\\n r1_filename_error,\\n r2_filename_error,\\n r1_filepath_error,\\n r2_filepath_error,\\n fast5_filename_error,\\n fast5_filepath_error,\\n fasta_filename_error,\\n fasta_filepath_error,\\n num_bp_error,\\n cons_genome_len_error,\\n mean_contig_len_error,\\n n50_error,\\n ns_100kbp_error,\\n ref_genome_accession_error,\\n cons_seq_id_error,\\n cons_seq_method_error,\\n cons_seq_filename_error,\\n cons_seq_filepath_error,\\n annot_table_filename_error,\\n biof_protocol_error,\\n gene_1_error,\\n pcr_protocol_1_error,\\n pcr_ct_1_error,\\n gene_2_error,\\n pcr_protocol_2_error,\\n pcr_ct_2_error,\\n authors_error]\\n\\n # return row of data for data file and row of data validity for error grid.\\n return cols, grid\",\n \"def test_BiplaneRegistration1(self):\\n\\n self.delayDisplay(\\\"Starting the test\\\")\\n #\\n # first, get some data\\n #\\n import urllib\\n downloads = (\\n ('http://slicer.kitware.com/midas3/download?items=5767', 'FA.nrrd', slicer.util.loadVolume),\\n )\\n\\n for url,name,loader in downloads:\\n filePath = slicer.app.temporaryPath + '/' + name\\n if not os.path.exists(filePath) or os.stat(filePath).st_size == 0:\\n logging.info('Requesting download %s from %s...\\\\n' % (name, url))\\n urllib.urlretrieve(url, filePath)\\n if loader:\\n logging.info('Loading %s...' % (name,))\\n loader(filePath)\\n self.delayDisplay('Finished with download and loading')\\n\\n volumeNode = slicer.util.getNode(pattern=\\\"FA\\\")\\n logic = BiplaneRegistrationLogic()\\n self.assertIsNotNone( logic.hasImageData(volumeNode) )\\n self.delayDisplay('Test passed!')\",\n \"def test_spin_loop_wildcard(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N*'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def setUp(self):\\r\\n self.l19_data = array([\\r\\n [7, 1, 0, 0, 0, 0, 0, 0, 0],\\r\\n [4, 2, 0, 0, 0, 1, 0, 0, 0],\\r\\n [2, 4, 0, 0, 0, 1, 0, 0, 0],\\r\\n [1, 7, 0, 0, 0, 0, 0, 0, 0],\\r\\n [0, 8, 0, 0, 0, 0, 0, 0, 0],\\r\\n [0, 7, 1, 0, 0, 0, 0, 0, 0],\\r\\n [0, 4, 2, 0, 0, 0, 2, 0, 0],\\r\\n [0, 2, 4, 0, 0, 0, 1, 0, 0],\\r\\n [0, 1, 7, 0, 0, 0, 0, 0, 0],\\r\\n [0, 0, 8, 0, 0, 0, 0, 0, 0],\\r\\n [0, 0, 7, 1, 0, 0, 0, 0, 0],\\r\\n [0, 0, 4, 2, 0, 0, 0, 3, 0],\\r\\n [0, 0, 2, 4, 0, 0, 0, 1, 0],\\r\\n [0, 0, 1, 7, 0, 0, 0, 0, 0],\\r\\n [0, 0, 0, 8, 0, 0, 0, 0, 0],\\r\\n [0, 0, 0, 7, 1, 0, 0, 0, 0],\\r\\n [0, 0, 0, 4, 2, 0, 0, 0, 4],\\r\\n [0, 0, 0, 2, 4, 0, 0, 0, 1],\\r\\n [0, 0, 0, 1, 7, 0, 0, 0, 0]\\r\\n ])\\r\\n self.l19_sample_names = [\\r\\n 'sam1', 'sam2', 'sam3', 'sam4', 'sam5', 'sam6',\\r\\n 'sam7', 'sam8', 'sam9', 'sam_middle', 'sam11', 'sam12', 'sam13',\\r\\n 'sam14', 'sam15', 'sam16', 'sam17', 'sam18', 'sam19']\\r\\n self.l19_taxon_names = ['tax1', 'tax2', 'tax3', 'tax4', 'endbigtaxon',\\r\\n 'tax6', 'tax7', 'tax8', 'tax9']\\r\\n\\r\\n self.legacy_otu_table1 = legacy_otu_table1\\r\\n self.otu_table1 = otu_table1\\r\\n self.otu_table_without_leading_comment = \\\\\\r\\n otu_table_without_leading_comment\\r\\n self.expected_lineages1 = expected_lineages1\\r\\n self.taxa_summary1 = taxa_summary1\\r\\n self.taxa_summary1_expected = taxa_summary1_expected\\r\\n self.otu_table1_floats = otu_table1_floats\\r\\n self.files_to_remove = []\\r\\n self.denoiser_mapping1 = denoiser_mapping1.split('\\\\n')\\r\\n self.sam_data1 = sam_data1.split(\\\"\\\\n\\\")\\r\\n self.sam1_expected = sam1_expected\",\n \"def setUp(self):\\n shape = RNG.integers(5, 50)\\n periods = self.periods = RNG.normal() * 3\\n freq = periods / shape\\n amp = RNG.normal()\\n offset = RNG.normal()\\n phase = (RNG.normal() - 1 / 2) * 5 / 3 * np.pi\\n p_gt = self.p_gt = (amp, freq, phase, offset)\\n x = self.x = np.arange(shape)\\n self.data = sine(x, *p_gt)\",\n \"def generate_license_plate(self, num):\\n license_plate = []\\n for _ in range(num):\\n license_plate.append(self.fake.license_plate())\\n return license_plate\",\n \"def genNumID(size):\\n\\tid = \\\"\\\"\\n\\tfor i in range(size):\\n\\t\\tid = id + selectRandomFromList(numTokens)\\n\\treturn id\",\n \"def test_kf_id():\\n\\n for _ in range(1000):\\n prefix = ''.join(random.sample(string.ascii_uppercase, 2))\\n kf_id = kf_id_generator(prefix)()\\n assert kf_id[:2] == prefix\\n assert len(kf_id) == 11\\n assert kf_id[2] == '_'\\n\\n assert 'I' not in kf_id[2:]\\n assert 'L' not in kf_id[2:]\\n assert 'O' not in kf_id[2:]\\n assert 'U' not in kf_id[2:]\\n\\n assert re.search(r'^'+prefix+r'_[A-HJ-KM-NP-TV-Z0-9]{8}', kf_id)\",\n \"def test_init():\\n rng = NonRandom()\\n seed = 5\\n rng.setSeed(seed)\\n wheel = Wheel(rng)\\n assert len(wheel.bins) == 38\\n assert wheel.rng.value == seed\\n assert wheel.rng.choice(range(0, 38)) == range(\\n 0, 38)[wheel.rng.value] # == seed\",\n \"def test_weyl_specialize_id(self):\\n a, b, c = 0.0, 0.0, 0.0\\n for da, db, dc in DELTAS:\\n for k1l, k1r, k2l, k2r in K1K2SB:\\n k1 = np.kron(k1l.data, k1r.data)\\n k2 = np.kron(k2l.data, k2r.data)\\n self.check_two_qubit_weyl_specialization(\\n k1 @ Ud(a + da, b + db, c + dc) @ k2,\\n 0.999,\\n TwoQubitWeylIdEquiv,\\n {\\\"rz\\\": 4, \\\"ry\\\": 2},\\n )\",\n \"def test_ids(self):\\n # AdapterID inherited from IOAdapter\\n self.assertEqual('553713696', self.sriovs[0].id)\\n self.assertEqual(1, self.sriovs[0].sriov_adap_id)\\n\\n self.assertEqual('553713680', self.sriovs[2].id)\\n self.assertIsNone(self.sriovs[2].sriov_adap_id)\",\n \"def sequence(self):\\n inigen = IniGen()\\n fields = algorithm_fields.algorithms['sequence']\\n\\n output_uuid_map = {}\\n\\n # set up global parameters\\n algorithm_path = fields['path']\\n enabled = \\\"True\\\"\\n inigen.emit_global(algorithm_path, enabled)\\n\\n label = \\\"SEQ\\\"\\n for t in ['C','L']:\\n run_label = label+'_'+t\\n t1Mag_label = '{0}1MAG'.format(t)\\n t2Mag_label = '{0}2MAG'.format(t)\\n t3Mag_label = '{0}3MAG'.format(t)\\n t1Ang_label = '{0}1ANG'.format(t)\\n t2Ang_label = '{0}2ANG'.format(t)\\n t3Ang_label = '{0}3ANG'.format(t)\\n distillate_label = \\\"{0}-ALL\\\".format(t)\\n\\n # header\\n inigen.emit_run_header(run_label, CHUNKING, MINTIME, MAXTIME)\\n\\n # body\\n dep_1Mag_label = t1Mag_label\\n dep_1Mag_name = fields['deps'][0]\\n dep_1Mag_uuid = self.uuid_map[t1Mag_label]\\n\\n dep_2Mag_label = t2Mag_label\\n dep_2Mag_name = fields['deps'][1]\\n dep_2Mag_uuid = self.uuid_map[t2Mag_label]\\n\\n dep_3Mag_label = t3Mag_label\\n dep_3Mag_name = fields['deps'][2]\\n dep_3Mag_uuid = self.uuid_map[t3Mag_label]\\n\\n dep_1Ang_label = t1Ang_label\\n dep_1Ang_name = fields['deps'][3]\\n dep_1Ang_uuid = self.uuid_map[t1Ang_label]\\n\\n dep_2Ang_label = t2Ang_label\\n dep_2Ang_name = fields['deps'][4]\\n dep_2Ang_uuid = self.uuid_map[t2Ang_label]\\n\\n dep_3Ang_label = t3Ang_label\\n dep_3Ang_name = fields['deps'][5]\\n dep_3Ang_uuid = self.uuid_map[t3Ang_label]\\n \\n deps = [[dep_1Mag_label, dep_1Mag_name, dep_1Mag_uuid],\\n [dep_2Mag_label, dep_2Mag_name, dep_2Mag_uuid],\\n [dep_3Mag_label, dep_3Mag_name, dep_3Mag_uuid],\\n [dep_1Ang_label, dep_1Ang_name, dep_1Ang_uuid],\\n [dep_2Ang_label, dep_2Ang_name, dep_2Ang_uuid],\\n [dep_3Ang_label, dep_3Ang_name, dep_3Ang_uuid]]\\n\\n param_section_name = fields['params'][0]\\n param_section_value = \\\"Production/{0}/{1}/{2}\\\".format(self.location, self.name, distillate_label)\\n param_name_name = fields['params'][1]\\n param_name_value = \\\"SEQ\\\"\\n params = [[param_section_name, param_section_value], [param_name_name, param_name_value]]\\n\\n outputs = fields['outputs']\\n\\n emitted = inigen.emit_run_body(deps, params, outputs)\\n\\n output_uuid_map[\\\"ZER_{0}ANG\\\".format(t)] = emitted[-9][-36:]\\n output_uuid_map[\\\"ZER_{0}MAG\\\".format(t)] = emitted[-8][-36:]\\n output_uuid_map[\\\"POS_{0}ANG\\\".format(t)] = emitted[-7][-36:]\\n output_uuid_map[\\\"POS_{0}MAG\\\".format(t)] = emitted[-6][-36:]\\n output_uuid_map[\\\"NEG_{0}ANG\\\".format(t)] = emitted[-5][-36:]\\n output_uuid_map[\\\"NEG_{0}MAG\\\".format(t)] = emitted[-4][-36:]\\n output_uuid_map[\\\"UNB_{0}NEG\\\".format(t)] = emitted[-3][-36:]\\n output_uuid_map[\\\"UNB_{0}ZER\\\".format(t)] = emitted[-2][-36:]\\n\\n filename = \\\"{0}/SEQ_{1}.ini\\\".format(self.dirname, self.name)\\n inigen.generate_file(filename)\\n return output_uuid_map\",\n \"def test_periodic_boundary_two_ring_rod():\\n\\n n_elems = 5\\n ring_rod_1 = MockRingRod(n_elems)\\n ring_rod_2 = MockRingRod(n_elems)\\n block_structure = MemoryBlockCosseratRod([ring_rod_1, ring_rod_2], [0, 1])\\n\\n correct_periodic_boundary_node_idx = np.array(\\n [[0, 6, 7, 9, 15, 16], [5, 1, 2, 14, 10, 11]], dtype=np.int64\\n )\\n correct_periodic_boundary_elem_idx = np.array(\\n [[0, 6, 9, 15], [5, 1, 14, 10]], dtype=np.int64\\n )\\n correct_periodic_boundary_voronoi_idx = np.array([[0, 9], [5, 14]], dtype=np.int64)\\n\\n assert_allclose(\\n correct_periodic_boundary_node_idx,\\n block_structure.periodic_boundary_nodes_idx,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_periodic_boundary_elem_idx,\\n block_structure.periodic_boundary_elems_idx,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_periodic_boundary_voronoi_idx,\\n block_structure.periodic_boundary_voronoi_idx,\\n atol=Tolerance.atol(),\\n )\\n\\n correct_start_node_idx = np.array([1, 10], dtype=np.int64)\\n correct_end_node_idx = np.array([6, 15], dtype=np.int64)\\n\\n correct_start_elem_idx = np.array([1, 10], dtype=np.int64)\\n correct_end_elem_idx = np.array([6, 15], dtype=np.int64)\\n\\n correct_start_voronoi_idx = np.array([1, 10], dtype=np.int64)\\n correct_end_voronoi_idx = np.array([6, 15], dtype=np.int64)\\n\\n assert_allclose(\\n correct_start_node_idx,\\n block_structure.start_idx_in_rod_nodes,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_node_idx,\\n block_structure.end_idx_in_rod_nodes,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_start_elem_idx,\\n block_structure.start_idx_in_rod_elems,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_elem_idx,\\n block_structure.end_idx_in_rod_elems,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_start_voronoi_idx,\\n block_structure.start_idx_in_rod_voronoi,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_voronoi_idx,\\n block_structure.end_idx_in_rod_voronoi,\\n atol=Tolerance.atol(),\\n )\",\n \"def test_api_random_id(api_client, single_brew_number):\\n response = api_client.get(path='/breweries' + '/' + str(single_brew_number))\\n assert response.json()['id'] == single_brew_number\",\n \"def generate_run_id(self):\\n r_id_len = 4\\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\\n while r_id in self.cache:\\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\\n return r_id\",\n \"def spinWheel():\\n\\tt = random.randrange(8)\\n\\tif t == 7:\\n\\t\\treturn \\\"00\\\"\\n\\treturn str(t)\",\n \"def test_periodic_boundary_one_ring_one_straight_rod():\\n\\n n_elems = 5\\n ring_rod = MockRingRod(n_elems)\\n straight_rod = MockRod(n_elems)\\n block_structure = MemoryBlockCosseratRod([ring_rod, straight_rod], [0, 1])\\n\\n correct_periodic_boundary_node_idx = np.array(\\n [[7, 13, 14], [12, 8, 9]], dtype=np.int64\\n )\\n correct_periodic_boundary_elem_idx = np.array([[7, 13], [12, 8]], dtype=np.int64)\\n correct_periodic_boundary_voronoi_idx = np.array([[7], [12]], dtype=np.int64)\\n\\n assert_allclose(\\n correct_periodic_boundary_node_idx,\\n block_structure.periodic_boundary_nodes_idx,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_periodic_boundary_elem_idx,\\n block_structure.periodic_boundary_elems_idx,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_periodic_boundary_voronoi_idx,\\n block_structure.periodic_boundary_voronoi_idx,\\n atol=Tolerance.atol(),\\n )\\n\\n correct_start_node_idx = np.array([0, 8], dtype=np.int64)\\n correct_end_node_idx = np.array([6, 13], dtype=np.int64)\\n\\n correct_start_elem_idx = np.array([0, 8], dtype=np.int64)\\n correct_end_elem_idx = np.array([5, 13], dtype=np.int64)\\n\\n correct_start_voronoi_idx = np.array([0, 8], dtype=np.int64)\\n correct_end_voronoi_idx = np.array([4, 13], dtype=np.int64)\\n\\n assert_allclose(\\n correct_start_node_idx,\\n block_structure.start_idx_in_rod_nodes,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_node_idx,\\n block_structure.end_idx_in_rod_nodes,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_start_elem_idx,\\n block_structure.start_idx_in_rod_elems,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_elem_idx,\\n block_structure.end_idx_in_rod_elems,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_start_voronoi_idx,\\n block_structure.start_idx_in_rod_voronoi,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_voronoi_idx,\\n block_structure.end_idx_in_rod_voronoi,\\n atol=Tolerance.atol(),\\n )\",\n \"def test_generate_mine_sequence(self):\\n mine_list = utils.generate_mine_sequence(1)\\n self.assertEqual(len(mine_list), utils.MINE_COUNT)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.78925526","0.7822347","0.76349664","0.7610406","0.75354004","0.6579472","0.60722893","0.5760644","0.5730065","0.5698617","0.5577793","0.55716354","0.554988","0.55279154","0.5508247","0.5425098","0.5357982","0.53330165","0.52789444","0.527686","0.527214","0.5268312","0.52163804","0.5194067","0.5179346","0.5176318","0.51564085","0.5122892","0.5117299","0.5103128","0.510082","0.5090494","0.5090219","0.50798005","0.507894","0.5075343","0.50554234","0.5050523","0.5048899","0.50474656","0.5032659","0.5017597","0.50080395","0.50057393","0.50032","0.5000263","0.49996006","0.49926984","0.49776763","0.49700373","0.4963348","0.4953122","0.4940451","0.49365178","0.49279872","0.49271482","0.49235255","0.49235255","0.4923179","0.49196634","0.4909212","0.49019378","0.48989117","0.4893592","0.48931327","0.48923245","0.48818964","0.48774952","0.48595533","0.48501563","0.4845759","0.48412576","0.4840679","0.48385945","0.4835118","0.48307422","0.48262954","0.48244327","0.48183614","0.4817891","0.48158827","0.47998947","0.47964734","0.4796047","0.47957593","0.47933728","0.47924533","0.47902986","0.4790076","0.47852185","0.4782436","0.47804448","0.47801146","0.47795898","0.47766742","0.47705022","0.47667357","0.47618693","0.47617072","0.47484848"],"string":"[\n \"0.78925526\",\n \"0.7822347\",\n \"0.76349664\",\n \"0.7610406\",\n \"0.75354004\",\n \"0.6579472\",\n \"0.60722893\",\n \"0.5760644\",\n \"0.5730065\",\n \"0.5698617\",\n \"0.5577793\",\n \"0.55716354\",\n \"0.554988\",\n \"0.55279154\",\n \"0.5508247\",\n \"0.5425098\",\n \"0.5357982\",\n \"0.53330165\",\n \"0.52789444\",\n \"0.527686\",\n \"0.527214\",\n \"0.5268312\",\n \"0.52163804\",\n \"0.5194067\",\n \"0.5179346\",\n \"0.5176318\",\n \"0.51564085\",\n \"0.5122892\",\n \"0.5117299\",\n \"0.5103128\",\n \"0.510082\",\n \"0.5090494\",\n \"0.5090219\",\n \"0.50798005\",\n \"0.507894\",\n \"0.5075343\",\n \"0.50554234\",\n \"0.5050523\",\n \"0.5048899\",\n \"0.50474656\",\n \"0.5032659\",\n \"0.5017597\",\n \"0.50080395\",\n \"0.50057393\",\n \"0.50032\",\n \"0.5000263\",\n \"0.49996006\",\n \"0.49926984\",\n \"0.49776763\",\n \"0.49700373\",\n \"0.4963348\",\n \"0.4953122\",\n \"0.4940451\",\n \"0.49365178\",\n \"0.49279872\",\n \"0.49271482\",\n \"0.49235255\",\n \"0.49235255\",\n \"0.4923179\",\n \"0.49196634\",\n \"0.4909212\",\n \"0.49019378\",\n \"0.48989117\",\n \"0.4893592\",\n \"0.48931327\",\n \"0.48923245\",\n \"0.48818964\",\n \"0.48774952\",\n \"0.48595533\",\n \"0.48501563\",\n \"0.4845759\",\n \"0.48412576\",\n \"0.4840679\",\n \"0.48385945\",\n \"0.4835118\",\n \"0.48307422\",\n \"0.48262954\",\n \"0.48244327\",\n \"0.48183614\",\n \"0.4817891\",\n \"0.48158827\",\n \"0.47998947\",\n \"0.47964734\",\n \"0.4796047\",\n \"0.47957593\",\n \"0.47933728\",\n \"0.47924533\",\n \"0.47902986\",\n \"0.4790076\",\n \"0.47852185\",\n \"0.4782436\",\n \"0.47804448\",\n \"0.47801146\",\n \"0.47795898\",\n \"0.47766742\",\n \"0.47705022\",\n \"0.47667357\",\n \"0.47618693\",\n \"0.47617072\",\n \"0.47484848\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8076779"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81484,"cells":{"query":{"kind":"string","value":"Second test of the spin ID generation function. The function tested is pipe_control.mol_res_spin.generate_spin_id_data_array()."},"document":{"kind":"string","value":"def test_generate_spin_id_data_array2(self):\n\n # The data.\n data = ['1', 'GLY', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2, spin_num_col=3, spin_name_col=4)\n\n # Test the string.\n self.assertEqual(id, ':1@234')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_generate_spin_id_data_array1(self):\n\n # The data.\n data = ['1', 'GLY']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')","def test_generate_spin_id_data_array6(self):\n\n # The data.\n data = ['1', 'GLY', None, None]\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')","def test_generate_spin_id_data_array5(self):\n\n # The data.\n data = ['Ap4Aase', '1', 'GLY', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5)\n\n # Test the string.\n self.assertEqual(id, '#Ap4Aase:1@234')","def test_generate_spin_id_data_array3(self):\n\n # The data.\n data = ['Ap4Aase', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=None, res_name_col=None, spin_num_col=2, spin_name_col=3)\n\n # Test the string.\n self.assertEqual(id, '#Ap4Aase@234')","def test_generate_spin_id_data_array4(self):\n\n # The data.\n data = ['Ap4Aase', '1', 'GLY']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3)\n\n # Test the string.\n self.assertEqual(id, '#Ap4Aase:1')","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_id_array(self):\n arr = vtk.vtkIdTypeArray()\n arr.SetNumberOfTuples(10)\n for i in range(10):\n arr.SetValue(i, i)\n\n np = array_handler.vtk2array(arr)\n self.assertEqual(numpy.all(np == range(10)), True)","def test_random_id(self):\r\n ids = \\\r\n \"R27DLI_4812 R27DLI_600 R27DLI_727 U1PLI_403 U1PLI_8969\".split(\r\n )\r\n assert random_id(ids, {}) in ids\r\n # just test we got something from the list, don't add stochastic test\r","def createArrayFunc(self):\r\n minVal = int(self.spinBoxMin_2.value())\r\n maxVal = int(self.spinBoxMax_2.value())\r\n arrayLength = int(self.spinBoxLength_2.value())\r\n different = maxVal - minVal\r\n if self.checkBoxNoRepeate_2.isChecked():\r\n if different > arrayLength:\r\n def unique_rand(initial, limit, total):\r\n data = []\r\n i = 0\r\n while i < total:\r\n number = numpy.random.randint(initial, limit)\r\n if number not in data:\r\n data.append(number)\r\n i += 1\r\n return data\r\n\r\n self.UnsortedArray_2 = unique_rand(minVal, maxVal, arrayLength)\r\n else:\r\n err = \"Array length must be greater than difference between limits\"\r\n self.labelUnsortedArray_2.setText(str(err))\r\n\r\n else:\r\n self.UnsortedArray_2 = numpy.random.randint(minVal, maxVal, arrayLength)\r\n self.labelUnsortedArray_2.setText(str(self.UnsortedArray_2))\r\n self.SortedArray_2 = Insertion.sorting(self.UnsortedArray_2)\r\n self.labelSortedArray_2.setText(str(self.SortedArray_2))\r\n binaryMax = int(self.spinBoxMax_2.value())\r\n binaryMin = int(self.spinBoxMin_2.value())\r\n self.spinBoxBinary.setMaximum(binaryMax)\r\n self.spinBoxBinary.setMinimum(binaryMin)\r\n self.spinBoxIthSmallest.setMaximum(arrayLength + 1)","def test_create_template(self):\n m_size = 10\n data = ecn.IDData(m_size)\n self.assertEqual(np.shape(data.ID_MATRIX), (m_size, m_size))\n self.assertEqual(sum(sum(data.ID_MATRIX)), m_size)\n self.assertTrue((sum(data.ID_MATRIX) == np.ones(m_size)).all())\n print('Finished testing template\\n')","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_spin_loop(self):\n\n # Spin data.\n select = [1, 0]\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, 'N5')\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 2)","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_scan_id_list(self):\n scan = '15,17'\n ref_idx = [0,3]\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_arr2vtkIdList(self):\n a = [1, 2, 3, 4, 5]\n p = array_handler.array2vtkIdList(a)\n for i, j in enumerate(a): \n self.assertEqual(p.GetId(i), j)\n p = vtk.vtkIdList()\n ident = id(p)\n p = array_handler.array2vtkIdList(numpy.array(a), p)\n for i, j in enumerate(a): \n self.assertEqual(p.GetId(i), j)\n self.assertEqual(id(p), ident)\n \n self.assertRaises(AssertionError, array_handler.array2vtkIdList,\n [[1,2,3]])","def test_split_id_otp(self):\n public_id, otp, = pyhsm.yubikey.split_id_otp(\"ft\" * 16)\n self.assertEqual(public_id, '')\n self.assertEqual(otp, \"ft\" * 16)\n\n public_id, otp, = pyhsm.yubikey.split_id_otp(\"cc\" + \"ft\" * 16)\n self.assertEqual(public_id, 'cc')\n self.assertEqual(otp, \"ft\" * 16)","def test_spin_type(get_pdos_generator_inputs):\n with pytest.raises(NotImplementedError):\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=spin_type)\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=SpinType.COLLINEAR)\n for namespace in [builder.scf, builder.nscf]:\n parameters = namespace['pw']['parameters'].get_dict()\n assert parameters['SYSTEM']['nspin'] == 2\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}","def _get_rand_array(self):\n pass","def test_spin_loop_no_selection(self):\n\n # Spin data.\n select = [0, 1, 0, 0, 1, 1, 0, 1]\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 8)","def test_get_ids(civic, main_data, updated_data):\n assert len(civic._get_ids(main_data['assertions'])) == 0\n assert len(civic._get_ids(main_data['variants'])) == 1\n assert len(civic._get_ids(main_data['genes'])) == 2\n assert len(civic._get_ids(main_data['evidence'])) == 1\n\n assert len(civic._get_ids(updated_data['assertions'])) == 1\n assert len(civic._get_ids(updated_data['variants'])) == 1\n assert len(civic._get_ids(updated_data['genes'])) == 1\n assert len(civic._get_ids(updated_data['evidence'])) == 1","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def generate_T(number_obeservations):\n T = np.random.randint(0, 2, (number_obeservations,1))\n return T","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_weyl_specialize_id(self):\n a, b, c = 0.0, 0.0, 0.0\n for da, db, dc in DELTAS:\n for k1l, k1r, k2l, k2r in K1K2SB:\n k1 = np.kron(k1l.data, k1r.data)\n k2 = np.kron(k2l.data, k2r.data)\n self.check_two_qubit_weyl_specialization(\n k1 @ Ud(a + da, b + db, c + dc) @ k2,\n 0.999,\n TwoQubitWeylIdEquiv,\n {\"rz\": 4, \"ry\": 2},\n )","def _apply_array_spin123(self,\n h1e: 'Nparray',\n h2e: 'Nparray',\n h3e: 'Nparray',\n dvec: Optional[Tuple['Nparray', 'Nparray']] = None,\n evec: Optional[Tuple['Nparray', 'Nparray', 'Nparray', 'Nparray']] \\\n = None) -> 'Nparray':\n norb = self.norb()\n assert h3e.shape == (norb * 2,) * 6\n assert not (dvec is None) ^ (evec is None)\n\n from1234 = (dvec is not None) and (evec is not None)\n\n nh1e = numpy.copy(h1e)\n nh2e = numpy.copy(h2e)\n\n for i in range(norb * 2):\n for j in range(norb * 2):\n for k in range(norb * 2):\n nh2e[j, k, :, :] += (-h3e[k, j, i, i, :, :] -\n h3e[j, i, k, i, :, :] -\n h3e[j, k, i, :, i, :])\n\n nh1e[:, :] += h3e[:, i, j, i, j, :]\n\n out = self._apply_array_spin12_halffilling(nh1e, nh2e)\n\n n = norb # This is just shorter\n if not from1234:\n symfac = 2.0\n axes = ((1, 3), (0, 1))\n (odveca, odvecb) = self.calculate_dvec_spin()\n dveca = numpy.zeros_like(odveca)\n dvecb = numpy.zeros_like(odvecb)\n\n for i in range(norb):\n for j in range(norb):\n evecaa, _ = self._calculate_dvec_spin_with_coeff(\n odveca[i, j, :, :])\n evecab, evecbb = self._calculate_dvec_spin_with_coeff(\n odvecb[i, j, :, :])\n\n dveca += numpy.tensordot(h3e[:n, :n, i, :n, :n, j],\n evecaa,\n axes=axes)\n dveca += numpy.tensordot(h3e[:n, :n, n + i, :n, :n, n + j],\n evecab,\n axes=axes) * symfac\n dveca += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\n evecbb,\n axes=axes)\n\n dvecb += numpy.tensordot(h3e[n:, :n, i, n:, :n, j],\n evecaa,\n axes=axes)\n dvecb += numpy.tensordot(h3e[n:, :n, n + i, n:, :n, n + j],\n evecab,\n axes=axes) * symfac\n dvecb += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\n evecbb,\n axes=axes)\n else:\n symfac = 1.0\n axes = ((1, 4, 2, 5), (0, 1, 2, 3)) # type: ignore\n dveca, dvecb = dvec # type: ignore\n evecaa, evecab, evecba, evecbb = evec # type: ignore\n\n dveca = numpy.tensordot(h3e[:n, :n, :n, :n, :n, :n],\n evecaa, axes=axes) \\\n + numpy.tensordot(h3e[:n, :n, n:, :n, :n, n:],\n evecab, axes=axes) * symfac \\\n + numpy.tensordot(h3e[:n, n:, n:, :n, n:, n:],\n evecbb, axes=axes) + \\\n + numpy.tensordot(h3e[:n, n:, :n, :n, n:, :n],\n evecba, axes=axes)\n\n dvecb = numpy.tensordot(h3e[n:, :n, :n, n:, :n, :n],\n evecaa, axes=axes) \\\n + numpy.tensordot(h3e[n:, :n, n:, n:, :n, n:],\n evecab, axes=axes) * symfac \\\n + numpy.tensordot(h3e[n:, n:, n:, n:, n:, n:],\n evecbb, axes=axes) + \\\n + numpy.tensordot(h3e[n:, n:, :n, n:, n:, :n],\n evecba, axes=axes)\n\n out -= self._calculate_coeff_spin_with_dvec((dveca, dvecb))\n return out","def test_pol_id_list(self):\n pol = '0,1'\n ref_idx = []\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_scan_id_range(self):\n scan = '16~17'\n ref_idx = [1,2,3]\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_sampleId_pairs(self):\r\n # expected values\r\n dose_vps = \\\r\n [('1xDose', '2xDose'), ('1xDose', 'Control'),\r\n ('2xDose', 'Control')]\r\n ttd_vps = \\\r\n [('31', '21'), ('31', '55'), ('31', '67'), ('21', '55'),\r\n ('21', '67'), ('55', '67')]\r\n dose_sids = \\\r\n [(['Sam1', 'Sam2', 'Sam6'], ['Sam3', 'Sam4']),\r\n (['Sam1', 'Sam2', 'Sam6'], ['Sam5']),\r\n (['Sam3', 'Sam4'], ['Sam5'])]\r\n ttd_sids = \\\r\n [(['Sam1'], ['Sam3']),\r\n (['Sam1'], ['Sam4', 'Sam6']),\r\n (['Sam1'], ['Sam2', 'Sam5']),\r\n (['Sam3'], ['Sam4', 'Sam6']),\r\n (['Sam3'], ['Sam2', 'Sam5']),\r\n (['Sam4', 'Sam6'], ['Sam2', 'Sam5'])]\r\n\r\n # observed values\r\n obs_dose_sids, obs_dose_vps = sampleId_pairs(self.mapping_data,\r\n self.rarefaction_data, 'Dose')\r\n obs_ttd_sids, obs_ttd_vps = sampleId_pairs(self.mapping_data,\r\n self.rarefaction_data, 'TTD')\r\n\r\n # sort -- order is unimportant and depends on way presented in mf\r\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\r\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())\r\n self.assertEqual(ttd_vps.sort(), obs_ttd_vps.sort())\r\n self.assertEqual(ttd_sids.sort(), obs_ttd_sids.sort())\r\n\r\n # check errors when no samples had this category\r\n self.assertRaises(ValueError, sampleId_pairs, self.mapping_data,\r\n self.rarefaction_data, 'DNE')\r\n\r\n # check no error if map file has more sampleids than rarefaction data\r\n superset_mf = \\\r\n ['#SampleID\\tDose\\tLinkerPrimerSequence\\tWeight\\tTTD\\tDescription',\r\n '#Comment Line',\r\n 'Sam1\\t1xDose\\tATCG\\tHigh\\t31\\ts1_desc',\r\n 'Sam2\\t1xDose\\tACCG\\tLow\\t67\\ts2_desc',\r\n 'Sam3\\t2xDose\\tACGT\\tMed\\t21\\ts3_desc',\r\n 'Sam4\\t2xDose\\tAACG\\tLow\\t55\\ts4_desc',\r\n 'Sam5\\tControl\\tCGTC\\tLow\\t67\\ts5_desc',\r\n 'Sam6\\t1xDose\\tACCT\\tLow\\t55\\ts6_desc',\r\n 'Sam7\\t4xDose\\tACCT\\tLow\\t55\\ts7_desc',\r\n 'Sam8\\t3xDose\\tACCT\\tLow\\t55\\ts8_desc',\r\n 'Sam9\\t1xDose\\tACCT\\tLow\\t55\\ts9_desc']\r\n # (mf, comments)\r\n superset_mf = parse_mapping_file_to_dict(superset_mf)[0]\r\n obs_dose_sids, obs_dose_vps = sampleId_pairs(superset_mf,\r\n self.rarefaction_data, 'Dose')\r\n\r\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\r\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())","def test_random_integers(self):\r\n # Check over two calls to see if the random state is correctly updated.\r\n random = RandomStreams(utt.fetch_seed())\r\n fn = function([], random.random_integers((20, 20), -5, 5))\r\n fn_val0 = fn()\r\n fn_val1 = fn()\r\n\r\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\r\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\r\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\r\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\r\n\r\n assert numpy.all(fn_val0 == numpy_val0)\r\n assert numpy.all(fn_val1 == numpy_val1)","def test_id_rot():\n assert_array_almost_equal(pr.R_id, pr.matrix_from_axis_angle(pr.a_id))\n assert_array_almost_equal(pr.R_id, pr.matrix_from_quaternion(pr.q_id))\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_xyz(pr.e_xyz_id))\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_zyx(pr.e_zyx_id))","def test_random_integers(self):\r\n # Check over two calls to see if the random state is correctly updated.\r\n m = Module()\r\n m.random = RandomStreams(utt.fetch_seed())\r\n m.fn = Method([], m.random.random_integers((20,20), -5, 5))\r\n\r\n made = m.make()\r\n made.random.initialize()\r\n fn_val0 = made.fn()\r\n fn_val1 = made.fn()\r\n\r\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\r\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\r\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\r\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\r\n\r\n assert numpy.all(fn_val0 == numpy_val0)\r\n assert numpy.all(fn_val1 == numpy_val1)","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def test_create_tornado_id(self):\n\n this_id_string = tornado_io.create_tornado_id(\n start_time_unix_sec=TORNADO_START_TIME_UNIX_SEC,\n start_latitude_deg=TORNADO_START_LATITUDE_DEG,\n start_longitude_deg=TORNADO_START_LONGITUDE_DEG)\n\n self.assertTrue(this_id_string == TORNADO_ID_STRING)","def test_spin_type(fixture_code, generate_structure):\n code = fixture_code('quantumespresso.pw')\n structure = generate_structure()\n\n with pytest.raises(NotImplementedError):\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\n PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=spin_type)\n\n builder = PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=SpinType.COLLINEAR)\n\n for namespace in [builder.relax['base'], builder.scf, builder.bands]:\n parameters = namespace['pw']['parameters'].get_dict()\n assert parameters['SYSTEM']['nspin'] == 2\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}","def test_main(data, tmp_path):\n\n main(data, tmp_path)\n\n FILES = (\n \"gd32f888x(0-1)xx-pinctrl.h\",\n \"gd32f888x(2-3)xx-pinctrl.h\",\n \"gd32f888y(0-1)xx-pinctrl.h\",\n \"gd32f999x(0-1)xx-pinctrl.h\",\n \"gd32f999x(2-3)xx-pinctrl.h\",\n \"gd32f999y(0-1)xx-pinctrl.h\",\n )\n\n for file in FILES:\n ref_file = data / file\n gen_file = tmp_path / file\n\n assert gen_file.exists()\n\n with open(ref_file) as ref, open(gen_file) as gen:\n assert ref.read() == gen.read()","def test_rand_func2(self):\n for i in range(0, 100000):\n num = random.randint(0, 32535143990)\n func2_comp(num)","def test_generateuuids(self):\n ret1 = {\"message\": \"No Random.org api key or api version found.\", \"res\": False}\n self.assertDictEqual(random_org.generateUUIDs(), ret1)\n\n ret2 = {\"message\": \"Required argument, number is missing.\", \"res\": False}\n self.assertDictEqual(\n random_org.generateUUIDs(api_key=\"peW\", api_version=\"1\"), ret2\n )\n\n ret3 = {\"message\": \"Number of UUIDs must be between 1 and 1000\", \"res\": False}\n self.assertDictEqual(\n random_org.generateUUIDs(api_key=\"peW\", api_version=\"1\", number=\"5\"), ret3\n )\n\n ret3 = {\"message\": \"Parameter 'apiKey' is malformed\", \"res\": False}\n self.assertDictEqual(\n random_org.generateUUIDs(api_key=\"peW\", api_version=\"1\", number=5), ret3\n )","def test_run_sim_1():\n rnd = rand.Arrivals(36, 41)\n sim.run_sim(3, 2, 5, 6, 22, rnd)","def gen_data(min_coord, max_coord, size):\r\n data = np.random.randint(min_coord, max_coord, size)\r\n return data","def test_id_get(mocker):\n mocker.patch('serial.Serial.open')\n mocker.patch('serial.Serial.flushInput')\n css = mocker.patch('pysds011.driver.SDS011.cmd_set_sleep')\n css.return_value = True\n cfv = mocker.patch('pysds011.driver.SDS011.cmd_firmware_ver')\n cfv.return_value = {'id': b'\\x12\\x34', 'paperino': 'maciomicio'}\n runner = CliRunner()\n result = runner.invoke(main, ['id'])\n\n calls = [call(0, id=b'\\xff\\xff'), call(1, id=b'\\xff\\xff')]\n css.assert_has_calls(calls, any_order=False)\n\n assert '12' in result.output and '34' in result.output\n assert result.exit_code == 0","def get_test_split(self, fraction=0.1):\n rng = np.random.default_rng(42)\n test_size = int(round(len(self.all_asset_ids) * fraction))\n test_ids = rng.choice(self.all_asset_ids, size=test_size, replace=False)\n train_ids = [i for i in self.all_asset_ids if i not in test_ids]\n return train_ids, test_ids","def test_brains_id_get(self):\n pass","def test_get_tid():\n tids = []\n def _foo():\n mytid = yield GetTid()\n tids.append(mytid)\n for i in range(5):\n yield i\n\n scheduler = Scheduler()\n scheduler.new(_foo())\n scheduler.new(_foo())\n scheduler.mainloop()\n\n # can we do better than hard code?\n assert tids == [4, 5]","def test_get_data_array():\n test_file = os.path.join(DATA_PATH, \"paper_test_file.uvh5\")\n test_uv = UVData()\n test_uv.read(test_file)\n\n baseline_array = np.array(list(set(test_uv.baseline_array)))\n data_array = utils.get_data_array(test_uv, reds=baseline_array)\n\n compare_data = np.zeros(\n (test_uv.Npols, test_uv.Nbls, test_uv.Ntimes, test_uv.Nfreqs),\n dtype=np.complex64,\n )\n\n pol_array = uvutils.polnum2str(test_uv.polarization_array)\n for pol_cnt, pol in enumerate(pol_array):\n for cnt, baseline in enumerate(list(set(test_uv.baseline_array))):\n ant_1, ant_2 = test_uv.baseline_to_antnums(baseline)\n compare_data[pol_cnt, cnt] = test_uv.get_data(ant_1, ant_2, pol)\n\n compare_data = compare_data.squeeze(axis=0)\n assert np.allclose(compare_data, data_array)","def test_periodic_boundary_two_ring_rod():\n\n n_elems = 5\n ring_rod_1 = MockRingRod(n_elems)\n ring_rod_2 = MockRingRod(n_elems)\n block_structure = MemoryBlockCosseratRod([ring_rod_1, ring_rod_2], [0, 1])\n\n correct_periodic_boundary_node_idx = np.array(\n [[0, 6, 7, 9, 15, 16], [5, 1, 2, 14, 10, 11]], dtype=np.int64\n )\n correct_periodic_boundary_elem_idx = np.array(\n [[0, 6, 9, 15], [5, 1, 14, 10]], dtype=np.int64\n )\n correct_periodic_boundary_voronoi_idx = np.array([[0, 9], [5, 14]], dtype=np.int64)\n\n assert_allclose(\n correct_periodic_boundary_node_idx,\n block_structure.periodic_boundary_nodes_idx,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_periodic_boundary_elem_idx,\n block_structure.periodic_boundary_elems_idx,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_periodic_boundary_voronoi_idx,\n block_structure.periodic_boundary_voronoi_idx,\n atol=Tolerance.atol(),\n )\n\n correct_start_node_idx = np.array([1, 10], dtype=np.int64)\n correct_end_node_idx = np.array([6, 15], dtype=np.int64)\n\n correct_start_elem_idx = np.array([1, 10], dtype=np.int64)\n correct_end_elem_idx = np.array([6, 15], dtype=np.int64)\n\n correct_start_voronoi_idx = np.array([1, 10], dtype=np.int64)\n correct_end_voronoi_idx = np.array([6, 15], dtype=np.int64)\n\n assert_allclose(\n correct_start_node_idx,\n block_structure.start_idx_in_rod_nodes,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_node_idx,\n block_structure.end_idx_in_rod_nodes,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_start_elem_idx,\n block_structure.start_idx_in_rod_elems,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_elem_idx,\n block_structure.end_idx_in_rod_elems,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_start_voronoi_idx,\n block_structure.start_idx_in_rod_voronoi,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_voronoi_idx,\n block_structure.end_idx_in_rod_voronoi,\n atol=Tolerance.atol(),\n )","def generate_new_ids(ids: np.array, n_required: int) -> np.array:\n\n current_max_id = ids.max()\n new_ids = np.arange(n_required) + current_max_id + 1\n\n return new_ids","def test_return_spin_pipe_fail(self):\n\n # Try to get a spin from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')","def test_SampleIds(self):\r\n exp = [\"PC.354\", \"PC.355\", \"PC.356\", \"PC.481\", \"PC.593\", \"PC.607\",\r\n \"PC.634\", \"PC.635\", \"PC.636\"]\r\n obs = self.overview_map.SampleIds\r\n self.assertEqual(obs, exp)\r\n\r\n obs = self.no_metadata.SampleIds\r\n self.assertEqual(obs, exp)\r\n\r\n obs = self.empty_map.SampleIds\r\n self.assertEqual(obs, [])","def test_pol_id_range(self):\n pol = '0~1'\n ref_idx = []\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_assign_resources_to_tmc_subarray_in_low():","def _spin_sequence(self):\n self.return_position = self.motor.position\n \n for spin_num in range(self.num_spins):\n self.taxi()\n\n det_pre_acquire(self.detector)\n self.fly()\n det_post_acquire(self.detector)\n\n while self.detector.hdf1.write_file.value:\n time.sleep(0.01) # wait for file to be written\n\n event = OrderedDict()\n event[\"time\"] = time.time()\n event[\"seq_num\"] = spin_num + 1\n event[\"data\"] = {}\n event[\"timestamps\"] = {}\n for d_item in (self.detector.hdf1.full_file_name,):\n d = d_item.read()\n for k, v in d.items():\n event['data'][k] = v['value']\n event['timestamps'][k] = v['timestamp']\n\n self._data.append(event)\n\n self.set(\"Return\")\n self._completion_status._finished(success=True)","def test_uuid():\n for _ in range(1000):\n uuid = uuid_generator()\n assert len(uuid) == 36\n assert uuid.count('-') == 4","def test_SampleIds(self):\n exp = [\"PC.354\", \"PC.355\", \"PC.356\", \"PC.481\", \"PC.593\", \"PC.607\",\n \"PC.634\", \"PC.635\", \"PC.636\"]\n obs = self.overview_map.SampleIds\n self.assertEqual(obs, exp)\n\n obs = self.no_metadata.SampleIds\n self.assertEqual(obs, exp)\n\n obs = self.empty_map.SampleIds\n self.assertEqual(obs, [])","def test_run_sim():\n rnd = rand.Arrivals(31, 40)\n sim.run_sim(2, 1, 3, 4, 24, rnd)","def myID() -> np.int:\r\n return 304976335","def myID() -> np.int:\r\n return 304976335","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_ids(self):\n # AdapterID inherited from IOAdapter\n self.assertEqual('553713696', self.sriovs[0].id)\n self.assertEqual(1, self.sriovs[0].sriov_adap_id)\n\n self.assertEqual('553713680', self.sriovs[2].id)\n self.assertIsNone(self.sriovs[2].sriov_adap_id)","def generate_raiz():\n\treturn os.urandom(12)","def test_assign_resources_to_tmc_subarray_in_mid():","def test_periodic_boundary_one_ring_rod():\n\n n_elems = 5\n ring_rod = MockRingRod(n_elems)\n block_structure = MemoryBlockCosseratRod([ring_rod], [0])\n\n correct_periodic_boundary_node_idx = np.array(\n [[0, 6, 7], [5, 1, 2]], dtype=np.int64\n )\n correct_periodic_boundary_elem_idx = np.array([[0, 6], [5, 1]], dtype=np.int64)\n correct_periodic_boundary_voronoi_idx = np.array([[0], [5]], dtype=np.int64)\n\n assert_allclose(\n correct_periodic_boundary_node_idx,\n block_structure.periodic_boundary_nodes_idx,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_periodic_boundary_elem_idx,\n block_structure.periodic_boundary_elems_idx,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_periodic_boundary_voronoi_idx,\n block_structure.periodic_boundary_voronoi_idx,\n atol=Tolerance.atol(),\n )\n\n correct_start_node_idx = np.array([1], dtype=np.int64)\n correct_end_node_idx = np.array([6], dtype=np.int64)\n\n correct_start_elem_idx = np.array([1], dtype=np.int64)\n correct_end_elem_idx = np.array([6], dtype=np.int64)\n\n correct_start_voronoi_idx = np.array([1], dtype=np.int64)\n correct_end_voronoi_idx = np.array([6], dtype=np.int64)\n\n assert_allclose(\n correct_start_node_idx,\n block_structure.start_idx_in_rod_nodes,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_node_idx,\n block_structure.end_idx_in_rod_nodes,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_start_elem_idx,\n block_structure.start_idx_in_rod_elems,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_elem_idx,\n block_structure.end_idx_in_rod_elems,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_start_voronoi_idx,\n block_structure.start_idx_in_rod_voronoi,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_voronoi_idx,\n block_structure.end_idx_in_rod_voronoi,\n atol=Tolerance.atol(),\n )","def test_correct_binid(self):\n\n maps = Maps(plateifu='8485-1901', release='DR17', bintype='HYB10')\n spaxel = maps[22, 14]\n\n assert isinstance(spaxel, Spaxel)\n assert spaxel.x == 14, spaxel.y == 22\n\n bin_spaxels = spaxel.stellar_vel.bin.get_bin_spaxels()\n\n for sp in bin_spaxels:\n\n sp.load()\n assert sp.stellar_vel.bin.binid == spaxel.stellar_vel.bin.binid\n\n sp_bin = maps[sp.y, sp.x]\n assert sp_bin.stellar_vel.bin.binid == spaxel.stellar_vel.bin.binid","def test_id_set(mocker):\n mocker.patch('serial.Serial.open')\n mocker.patch('serial.Serial.flushInput')\n css = mocker.patch('pysds011.driver.SDS011.cmd_set_sleep')\n css.return_value = True\n csi = mocker.patch('pysds011.driver.SDS011.cmd_set_id')\n runner = CliRunner()\n result = runner.invoke(main, ['--id', 'cccc', 'id', 'abcd'])\n\n # Two calls to cmd_set_sleep:\n # the first use original address\n # at the second one, the sensor has a new address: so sleep\n # has the use the new one\n calls = [call(0, id=b'\\xcc\\xcc'), call(1, id=b'\\xab\\xcd')]\n css.assert_has_calls(calls, any_order=False)\n csi.assert_called_once_with(id=b'\\xcc\\xcc', new_id=b'\\xab\\xcd')\n assert result.exit_code == 0","def generaterandomindices(dataSize, percentTest):\n\n TrainIndices = np.array([])\n while TrainIndices.__len__() < int(percentTest * dataSize):\n # Randomly select an index value and store it. If it has already been chosen, pick again.\n index = int(random.random() * dataSize)\n if not TrainIndices.__contains__(index):\n TrainIndices = np.append(TrainIndices, [index])\n\n # For aesthetic purposes:\n TrainIndices = np.sort(TrainIndices)\n\n return TrainIndices","def generate_fake_data(t0, num_array, period=5820, data_range=[0.0, 24.0],\n cyclic=True):\n\n if cyclic:\n uts_root = np.mod(t0, period)\n data = (np.mod(uts_root + num_array, period)\n * (np.diff(data_range)[0] / np.float64(period))) + data_range[0]\n else:\n data = ((t0 + num_array) / period).astype(int)\n\n return data","def _generate_id() -> str:\n return \"\".join(sample(\"abcdefghjkmopqrstuvqxyz\", 16))","def data_gen(size, p):\n #print(np.random.get_state()[1][0])\n random_table = np.random.binomial(size = size, p = p, n = 1)\n test_array = np.zeros((size, 2), dtype = int)\n for i in range(size):\n test_array[i,0] = i\n test_array[i,1] = random_table[i]\n return test_array","def generate_subsegment_id():\n return uuid.uuid4().hex[:16]","def test_run_a_scan_on_sdp_subarray_in_mid():","def test_returned_num_in_random_nums(self):\n self._setup_random_gen([1.], [42])\n self.assertEqual(self._random_gen.next_num(), 42)","def test_CreateROI1(self):\r\n\r\n self.delayDisplay(\"Starting the test\")\r\n #\r\n # first, get some data\r\n #\r\n import urllib\r\n downloads = (\r\n ('http://slicer.kitware.com/midas3/download?items=5767', 'FA.nrrd', slicer.util.loadVolume),\r\n )\r\n\r\n for url,name,loader in downloads:\r\n filePath = slicer.app.temporaryPath + '/' + name\r\n if not os.path.exists(filePath) or os.stat(filePath).st_size == 0:\r\n logging.info('Requesting download %s from %s...\\n' % (name, url))\r\n urllib.urlretrieve(url, filePath)\r\n if loader:\r\n logging.info('Loading %s...' % (name,))\r\n loader(filePath)\r\n self.delayDisplay('Finished with download and loading')\r\n\r\n volumeNode = slicer.util.getNode(pattern=\"FA\")\r\n logic = CreateROILogic()\r\n self.assertIsNotNone( logic.hasImageData(volumeNode) )\r\n self.delayDisplay('Test passed!')","def test_residue_loop(self):\n\n # Loop over the residues.\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\n # Test the selection.\n self.assertEqual(res.num, 2)\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)","def test_scan_id_exprlist(self):\n scan = '15,>16'\n ref_idx = [0,3]\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def generate_synth_data(n):","def generateRegistrationId():\n regId = KeyHelper.getRandomSequence()\n return regId","def test_generate(self):\n cant_interations = int(random()*100)\n for i in range(cant_interations):\n number = self.sudoku.generate() # Generate number\n self.assertGreaterEqual(number, 0) # number >= 0\n self.assertLessEqual(number, 8) # number <= 8","def test_test_ids_request(get_interface_params):\n from sail_on_client.protocol.localinterface import LocalInterface\n\n config_directory, config_name = get_interface_params\n data_dir = f\"{os.path.dirname(__file__)}/data\"\n local_interface = LocalInterface(config_name, config_directory)\n\n assumptions_path = os.path.join(os.path.dirname(__file__), \"assumptions.json\")\n filename = local_interface.test_ids_request(\n \"OND\", \"image_classification\", \"5678\", assumptions_path\n )\n expected = os.path.join(data_dir, \"OND\", \"image_classification\", \"test_ids.csv\")\n assert os.stat(expected).st_size > 5\n assert expected == filename","def get_sampled_ids(self):\n seed = 123\n #initiate two lists, to save randomly picked positive and negative cases respectively\n positiveIds = []\n negativeIds = []\n i = 0\n print \"==> resampling ... \",\n while len(positiveIds)+len(negativeIds)<self.ntotal:\n # start a loop from 0 to total size of the new sampe\n # if it catches a number divisable by the sought ratio, update the list of positive cases ids\n # otherwise keep update the list of negative cases ids\n try:\n if i%int(100 / self.posRate) == 0: \n positiveIds.append(self.posId.next())\n else:\n negativeIds.append(self.negId.next())\n except:\n print \"Enter posRate higher than the initial rate\"\n break\n i+=1\n print \"Done sampling\"\n print \"positive:\", len(positiveIds)\n print \"negative:\", len(negativeIds)\n print \"final size:\", len(positiveIds)+len(negativeIds)\n #return sorted list of the two list of ids combined\n return sorted(positiveIds+negativeIds)","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def test_return_residue(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_residue(':1')\n res2 = mol_res_spin.return_residue(selection=':2')\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\n\n # Test the data of residue 1.\n self.assertEqual(res1.num, 1)\n self.assertEqual(res1.name, None)\n\n # Test the data of residue 2.\n self.assertEqual(res2.num, 2)\n self.assertEqual(res2.name, 'Glu')\n\n # Test the data of residue 4.\n self.assertEqual(res4.num, 4)\n self.assertEqual(res4.name, 'Pro')\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5.num, -5)\n self.assertEqual(res5.name, None)\n self.assertEqual(res5.spin[1].name, 'N5')","def test_if_array_is_good(self):\n testing_param = random.randint(1, 100)\n self.assertEqual(self.exercice.main(testing_param),\n list(range(2, testing_param+1, 2)))","def test_run_a_scan_on_sdp_subarray_in_low():","def test_ipam_rirs_create(self):\n pass","def make_row(invalid_data=[]):\n\n ### Database Identifiers ###\n \n # phac_sample_id, valid/invalid error-grid information.\n phac_sample_id, phac_sample_id_error = lib.random_phac_id(invalid_data)\n # umbrella_bioproject_accession, valid/invalid error-grid information.\n ub_accession, ub_accession_error = lib.umbrella_bioproject_accession(invalid_data)\n # bioproject_accession, valid/invalid error-grid information.\n bp_accession, bp_accession_error = lib.random_bioproject_accession(invalid_data)\n # biosample_accession, valid/invalid error-grid information.\n bs_accession, bs_accession_error = lib.random_biosample_accession(invalid_data)\n # sra_accession, valid/invalid error-grid information.\n sra_accession, sra_accession_error = lib.random_sra_accession(invalid_data)\n # genbank_accession, valid/invalid error-grid information.\n gb_accession, gb_accession_error = lib.random_genbank_accession(invalid_data)\n # gisaid_accession, valid/invalid error-grid information.\n gisaid_accession, gisaid_accession_error = lib.random_gisaid_accession(invalid_data)\n \n ### Sample Collection and Processing ###\n \n # sample_collected_by, valid/invalid error-grid information.\n samp_col_by, samp_col_by_error = lib.random_agency(invalid_data)\n # sample_collector_contact_email, valid/invalid error-grid information.\n samp_col_email, samp_col_email_error = lib.random_email(invalid_data)\n # sample_collector_contact_address, valid/invalid error-grid information.\n samp_col_address, samp_col_address_error = lib.random_address(invalid_data)\n # sequence_submitter_contact_email, valid/invalid error-grid information.\n seq_sub_email, seq_sub_email_error = lib.random_email(invalid_data)\n # sequence_submitter_contact_address, valid/invalid error-grid information.\n seq_sub_address, seq_sub_address_error = lib.random_address(invalid_data)\n # sample_collection_date, valid/invalid error-grid information.\n samp_col_date, samp_col_date_error = lib.random_date(invalid_data)\n # sample_received_date, valid/invalid error-grid information.\n samp_rec_date, samp_rec_date_error = lib.random_date(invalid_data)\n # geo_loc_name_country, valid/invalid error-grid information.\n geo_loc_country, geo_loc_country_error = lib.random_country(invalid_data)\n # geo_loc_name_province_territory, valid/invalid error-grid information.\n geo_loc_prov_ter, geo_loc_prov_ter_error = lib.random_province_territory(invalid_data)\n # geo_loc_name_city, valid/invalid error-grid information.\n geo_loc_city, geo_loc_city_error = lib.random_city(invalid_data)\n # organism, valid/invalid error-grid information.\n organism, organism_error = lib.random_organism(invalid_data)\n # purpose_of_sampling, valid/invalid error-grid information.\n p_o_sampling, p_o_sampling_error = lib.random_purpose_of_sampling(invalid_data)\n # anatomical_material, valid/invalid error-grid information.\n anat_material, anat_material_error = lib.random_anatomical_material(invalid_data)\n # anatomical_part, valid/invalid error-grid information.\n anat_part, anat_part_error = lib.random_anatomical_part(invalid_data)\n # body_product, valid/invalid error-grid information.\n body_product, body_product_error = lib.random_body_product(invalid_data)\n # environmental_material, valid/invalid error-grid information.\n envi_material, envi_material_error = lib.random_environmental_material(invalid_data)\n # environmental_site, valid/invalid error-grid information.\n envi_site, envi_site_error = lib.random_environmental_site(invalid_data)\n # collection_device, valid/invalid error-grid information.\n col_device, col_device_error = lib.random_collection_device(invalid_data)\n # collection_method, valid/invalid error-grid information.\n col_method, col_method_error = lib.random_collection_method(invalid_data)\n # collection_protocol, valid/invalid error-grid information.\n col_protocol, col_protocol_error = lib.fake_protocol(invalid_data)\n # specimen_processing, valid/invalid error-grid information.\n spec_process, spec_process_error = lib.random_specimen_processing(invalid_data)\n # lab_host, valid/invalid error-grid information.\n lab_host, lab_host_error = lib.random_lab_host(invalid_data)\n # passage_number , valid/invalid error-grid information.\n passage_num, passage_num_error = lib.random_passage_number(invalid_data)\n # passage_method, valid/invalid error-grid information.\n passage_method, passage_method_error = lib.passage_method_text(invalid_data)\n # biomaterial_extracted, valid/invalid error-grid information.\n biom_extract, biom_extract_error = lib.random_biomaterial_extracted(invalid_data)\n \n ### Host Information ###\n \n # host_common_name, valid/invalid error-grid information.\n host_com_name, host_com_name_error = lib.random_host_common_name(invalid_data)\n # host_scientific_name, valid/invalid error-grid information.\n host_sci_name, host_sci_name_error = lib.random_host_scientific_name(invalid_data)\n # host_health_state, valid/invalid error-grid information.\n host_health_state, host_health_state_error = lib.random_host_health_state(invalid_data)\n # host_health_status_details, valid/invalid error-grid information.\n host_health_status, host_health_status_error = lib.random_host_health_status_details(invalid_data)\n # host_disease, valid/invalid error-grid information.\n host_disease, host_disease_error = lib.random_host_disease(invalid_data)\n # host_age, valid/invalid error-grid information.\n host_age, host_age_error = lib.random_host_age(invalid_data)\n # host_gender, valid/invalid error-grid information.\n host_gender, host_gender_error = lib.random_host_gender(invalid_data)\n # host_origin_geo_loc_name_country, valid/invalid error-grid information.\n host_loc_country, host_loc_country_error = lib.random_country(invalid_data)\n # host_subject_id, valid/invalid error-grid information.\n host_sub_id, host_sub_id_error = lib.random_host_subject_id(invalid_data)\n # symptom_onset_date, valid/invalid error-grid information.\n symp_onset_date, symp_onset_date_error = lib.random_date(invalid_data)\n # signs_and_symptoms, valid/invalid error-grid information.\n signs_symptoms, signs_symptoms_error = lib.random_signs_symptoms(invalid_data)\n \n ### Host Exposure Information ###\n \n # location_of_exposure_geo_loc_name_country, valid/invalid error-grid information.\n loc_exp_country, loc_exp_country_error = lib.random_country(invalid_data)\n # travel_history, valid/invalid error-grid information. \n trav_history, trav_history_error = lib.random_travel_history(invalid_data)\n # exposure_event, valid/invalid error-grid information.\n exp_event, exp_event_error = lib.random_exposure_event(invalid_data)\n \n ### Sequencing ###\n \n # minion_barcode, valid/invalid error-grid information.\n minion_barcode, minion_barcode_error = lib.random_minIon_barcode(invalid_data)\n # sequencing_instrument, valid/invalid error-grid information.\n seq_instrument, seq_instrument_error = lib.random_seq_instrument(invalid_data)\n # sequencing_protocol_name, valid/invalid error-grid information.\n seq_prot_name, seq_prot_name_error = lib.fake_protocol(invalid_data)\n # sequencing_protocol_source, valid/invalid error-grid information.\n seq_prot_source, seq_prot_source_error = lib.random_seq_protocol_source(invalid_data)\n # sequencing_kit_number, valid/invalid error-grid information.\n seq_kit_num, seq_kit_num_error = lib.random_seq_kit_num(invalid_data)\n # amplicon_pcr_primers_filename, valid/invalid error-grid information.\n amp_pcr_filename, amp_pcr_filename_error = lib.random_txt_filename(invalid_data)\n \n ### Bioinformatics and QC metrics ###\n \n # raw_sequence_data_processing, valid/invalid error-grid information.\n raw_seq_process, raw_seq_process_error = lib.random_seq_process(invalid_data)\n # sequencing_depth_average, valid/invalid error-grid information.\n seq_depth_avg, seq_depth_avg_error = lib.random_seq_depth(invalid_data)\n # assembly_method, valid/invalid error-grid information.\n assemb_method, assemb_method_error = lib.random_assembly_software(invalid_data)\n # assembly_coverage_breadth, valid/invalid error-grid information.\n assemb_cov_breadth, assemb_cov_breadth_error = lib.random_assembly_coverage_breadth(invalid_data)\n # assembly_coverage_depth, valid/invalid error-grid information.\n assemb_cov_depth, assemb_cov_depth_error = lib.random_seq_depth(invalid_data)\n # r1_fastq_filename, valid/invalid error-grid information.\n r1_filename, r1_filename_error = lib.random_fastq_filename(invalid_data)\n # r2_fastq_filename, valid/invalid error-grid information.\n r2_filename, r2_filename_error = lib.random_fastq_filename(invalid_data)\n # r1_fastq_filepath, valid/invalid error-grid information.\n r1_filepath, r1_filepath_error = lib.random_filepath(r1_filename, invalid_data)\n # r2_fastq_filepath, valid/invalid error-grid information.\n r2_filepath, r2_filepath_error = lib.random_filepath(r2_filename, invalid_data)\n # fast5_filename, valid/invalid error-grid information.\n fast5_filename, fast5_filename_error = lib.random_fast5_filename(invalid_data)\n # fast5_filepath, valid/invalid error-grid information.\n fast5_filepath, fast5_filepath_error = lib.random_filepath(fast5_filename, invalid_data)\n # fasta_filename, valid/invalid error-grid information.\n fasta_filename, fasta_filename_error = lib.random_fasta_filename(invalid_data)\n # fasta_filepath, valid/invalid error-grid information.\n fasta_filepath, fasta_filepath_error = lib.random_filepath(fasta_filename, invalid_data)\n # number_base_pairs, valid/invalid error-grid information.\n num_bp, num_bp_error = lib.random_bp_num(invalid_data)\n # consensus_genome_length, valid/invalid error-grid information.\n cons_genome_len, cons_genome_len_error = lib.random_genome_length(invalid_data)\n # mean_contig_length, valid/invalid error-grid information.\n mean_contig_len, mean_contig_len_error = lib.random_contig_length(invalid_data)\n # n50, valid/invalid error-grid information.\n n50, n50_error = lib.random_n50(invalid_data)\n # ns_per_100_kbp, valid/invalid error-grid information.\n ns_100kbp, ns_100kbp_error = lib.random_ns_100kbp(invalid_data)\n # reference_genome_accession, valid/invalid error-grid information.\n ref_genome_accession, ref_genome_accession_error = lib.random_ref_genome(invalid_data)\n # consensus_sequence_id, valid/invalid error-grid information.\n cons_seq_id, cons_seq_id_error = lib.random_consensus_seq_id(invalid_data)\n # consensus_sequence_method, valid/invalid error-grid information.\n cons_seq_method, cons_seq_method_error = lib.random_consensus_seq_method(invalid_data)\n # consensus_sequence_filename, valid/invalid error-grid information.\n cons_seq_filename, cons_seq_filename_error = lib.random_fasta_filename(invalid_data)\n # consensus_sequence_filepath, valid/invalid error-grid information.\n cons_seq_filepath, cons_seq_filepath_error = lib.random_filepath(cons_seq_filename, invalid_data)\n # annotation_feature_table_filename, valid/invalid error-grid information.\n annot_table_filename, annot_table_filename_error = lib.random_feature_table_filename(invalid_data)\n # bioinformatics_protocol, valid/invalid error-grid information.\n biof_protocol, biof_protocol_error = lib.bioinformatics_protocol(invalid_data)\n \n ### Pathogen Diagnostic Testing ###\n \n # gene_name_1, valid/invalid error-grid information.\n gene_1, gene_1_error = lib.random_gene(invalid_data)\n # diagnostic_pcr_protocol_1, valid/invalid error-grid information.\n pcr_protocol_1, pcr_protocol_1_error = lib.fake_protocol(invalid_data)\n # diagnostic_pcr_ct_value_1, valid/invalid error-grid information.\n pcr_ct_1, pcr_ct_1_error = lib.random_pcr_ct_val(invalid_data)\n # gene_name_2, valid/invalid error-grid information.\n gene_2, gene_2_error = lib.random_gene(invalid_data)\n # diagnostic_pcr_protocol_2, valid/invalid error-grid information.\n pcr_protocol_2, pcr_protocol_2_error = lib.fake_protocol(invalid_data)\n # diagnostic_pcr_ct_value_2, valid/invalid error-grid information.\n pcr_ct_2, pcr_ct_2_error = lib.random_pcr_ct_val(invalid_data)\n \n ### Contributor Acknowledgement ###\n \n # authors, valid/invalid error-grid information.\n authors, authors_error = lib.authors(invalid_data)\n \n ### Dependent IDs ###\n \n # specimen_collector_sample_id.\n spec_col_sample_id, spec_col_sample_id_error = lib.random_specimen_collector_sample_id(\n geo_loc_country, \n geo_loc_prov_ter,\n geo_loc_city,\n invalid_data)\n # irida_sample_name.\n irida_sample_id = spec_col_sample_id\n # sequence_submitted_by.\n seq_sub_by = samp_col_by\n # library_id, valid/invalid error-grid information.\n library_id, library_id_error = lib.random_library_id(spec_col_sample_id, invalid_data)\n # isolate.\n isolate = spec_col_sample_id\n # assembly_name, valid/invalid error-grid information.\n assemb_name, assemb_name_error = lib.random_assembly_name(spec_col_sample_id, invalid_data)\n\n # Row of generated data organised by column.\n cols = [spec_col_sample_id,\n phac_sample_id,\n irida_sample_id,\n ub_accession,\n bp_accession,\n bs_accession,\n sra_accession,\n gb_accession,\n gisaid_accession,\n samp_col_by,\n samp_col_email,\n samp_col_address,\n seq_sub_by,\n seq_sub_email,\n seq_sub_address,\n samp_col_date,\n samp_rec_date,\n geo_loc_country,\n geo_loc_prov_ter,\n geo_loc_city,\n organism,\n isolate,\n p_o_sampling,\n anat_material,\n anat_part,\n body_product,\n envi_material,\n envi_site,\n col_device,\n col_method,\n col_protocol,\n spec_process,\n lab_host,\n passage_num,\n passage_method,\n biom_extract,\n host_com_name,\n host_sci_name,\n host_health_state,\n host_health_status,\n host_disease,\n host_age,\n host_gender,\n host_loc_country,\n host_sub_id,\n symp_onset_date,\n signs_symptoms,\n loc_exp_country,\n trav_history,\n exp_event,\n library_id,\n minion_barcode,\n seq_instrument,\n seq_prot_name,\n seq_prot_source,\n seq_kit_num,\n amp_pcr_filename,\n raw_seq_process,\n seq_depth_avg,\n assemb_name,\n assemb_method,\n assemb_cov_breadth,\n assemb_cov_depth,\n r1_filename,\n r2_filename,\n r1_filepath,\n r2_filepath,\n fast5_filename,\n fast5_filepath,\n fasta_filename,\n fasta_filepath,\n num_bp,\n cons_genome_len,\n mean_contig_len,\n n50,\n ns_100kbp,\n ref_genome_accession,\n cons_seq_id,\n cons_seq_method,\n cons_seq_filename,\n cons_seq_filepath,\n annot_table_filename,\n biof_protocol,\n gene_1,\n pcr_protocol_1,\n pcr_ct_1,\n gene_2,\n pcr_protocol_2,\n pcr_ct_2,\n authors]\n\n # Error grid valid/invalid (error specific) information.\n grid = ['-', # spec_col_sample_id_error placeholder\n phac_sample_id_error,\n '-', # irida_sample_id_error placeholder\n ub_accession_error,\n bp_accession_error,\n bs_accession_error,\n sra_accession_error,\n gb_accession_error,\n gisaid_accession_error,\n samp_col_by_error,\n samp_col_email_error,\n samp_col_address_error,\n '-', # seq_sub_by_error placeholder\n seq_sub_email_error,\n seq_sub_address_error,\n samp_col_date_error,\n samp_rec_date_error,\n geo_loc_country_error,\n geo_loc_prov_ter_error,\n geo_loc_city_error,\n organism_error,\n '-', # isolate_error placeholder\n p_o_sampling_error,\n anat_material_error,\n anat_part_error,\n body_product_error,\n envi_material_error,\n envi_site_error,\n col_device_error,\n col_method_error,\n col_protocol_error,\n spec_process_error,\n lab_host_error,\n passage_num_error,\n passage_method_error,\n biom_extract_error,\n host_com_name_error,\n host_sci_name_error,\n host_health_state_error,\n host_health_status_error,\n host_disease_error,\n host_age_error,\n host_gender_error,\n host_loc_country_error,\n host_sub_id_error,\n symp_onset_date_error,\n signs_symptoms_error,\n loc_exp_country_error,\n trav_history_error,\n exp_event_error,\n library_id_error,\n minion_barcode_error,\n seq_instrument_error,\n seq_prot_name_error,\n seq_prot_source_error,\n seq_kit_num_error,\n amp_pcr_filename_error,\n raw_seq_process_error,\n seq_depth_avg_error,\n assemb_name_error,\n assemb_method_error,\n assemb_cov_breadth_error,\n assemb_cov_depth_error,\n r1_filename_error,\n r2_filename_error,\n r1_filepath_error,\n r2_filepath_error,\n fast5_filename_error,\n fast5_filepath_error,\n fasta_filename_error,\n fasta_filepath_error,\n num_bp_error,\n cons_genome_len_error,\n mean_contig_len_error,\n n50_error,\n ns_100kbp_error,\n ref_genome_accession_error,\n cons_seq_id_error,\n cons_seq_method_error,\n cons_seq_filename_error,\n cons_seq_filepath_error,\n annot_table_filename_error,\n biof_protocol_error,\n gene_1_error,\n pcr_protocol_1_error,\n pcr_ct_1_error,\n gene_2_error,\n pcr_protocol_2_error,\n pcr_ct_2_error,\n authors_error]\n\n # return row of data for data file and row of data validity for error grid.\n return cols, grid","def test_slepp_get_at_id(mocker):\n mocker.patch('serial.Serial.open')\n mocker.patch('serial.Serial.flushInput')\n cgs = mocker.patch('pysds011.driver.SDS011.cmd_get_sleep')\n runner = CliRunner()\n result = runner.invoke(main, ['--id', 'ABCD', 'sleep'])\n cgs.assert_called_once_with(id=b'\\xab\\xcd')\n\n assert result.exit_code == 0","def test_simple(self):\n # blocks [0 3583] [3840 4058]\n test_file1 = os.path.join(INPUT_HYPM_PATH, 'unit_364-2013-206-2-0.mdd')\n # blocks [0 1279] [1536 1791] [2048 2303] [2560 2815] [3072 4059]\n test_file2 = os.path.join(INPUT_HYPM_PATH, 'unit_364-2013-206-3-0.mdd')\n\n # parse the two test files into the node and instrument group files\n mdd.procall([test_file1, test_file2])\n\n data_orig = self.read_full_file('node58p1.dat')\n\n # read the data from all generated files into one data string\n data_out = self.read_full_file('node58p1_0.status_1236801.dat')\n # confirm this file only has the allowed instrument IDs\n self.check_sio_type(data_out, ['PS', 'CS'])\n\n data_out_wa = self.read_full_file('node58p1_0.wa_wfp_1236820.dat')\n # confirm this file only has the allowed instrument IDs\n self.check_sio_type(data_out_wa, ['WA'])\n data_out += data_out_wa\n\n data_out_wc = self.read_full_file('node58p1_0.wc_wfp_1236820.dat')\n # confirm this file only has the allowed instrument IDs\n self.check_sio_type(data_out_wc, ['WC'])\n data_out += data_out_wc\n\n data_out_we = self.read_full_file('node58p1_0.we_wfp_1236820.dat')\n # confirm this file only has the allowed instrument IDs\n self.check_sio_type(data_out_wc, ['WE'])\n data_out += data_out_we\n\n # confirm that all data blocks from the node data file made it\n # into the instrument group files\n if not TestSioUnpack.compare_sio_matches(data_orig, data_out):\n self.fail(\"Failed sio block compare\")","def test_spin_loop_wildcard(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N*'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_seqgen(fprime_test_api):\n sequence = Path(__file__).parent / \"test_seq.seq\"\n assert (\n subprocess.run(\n [\n \"fprime-seqgen\",\n \"-d\",\n str(fprime_test_api.pipeline.dictionary_path),\n str(sequence),\n \"/tmp/ref_test_int.bin\",\n ]\n ).returncode\n == 0\n ), \"Failed to run fprime-seqgen\"\n fprime_test_api.send_and_assert_command(\n \"cmdSeq.CS_RUN\", args=[\"/tmp/ref_test_int.bin\", \"BLOCK\"], max_delay=5\n )","def test_get_sample_ids(self):\n obs = self.tester._get_sample_ids(self.conn_handler)\n self.assertEqual(obs, self.exp_sample_ids)","def test_get_sample_ids(self):\n obs = self.tester._get_sample_ids(self.conn_handler)\n self.assertEqual(obs, self.exp_sample_ids)","def test_start_ids_10(self):\n\n\t\texpected_num_layers = 11\n\t\texpected_ids = np.arange(10,21)\n\t\t# test describe\n\t\tdetails = self.watcher.describe(start_ids=10)\n\t\tprint(\"start id = 10\", details)\n\t\tactual_ids = details.layer_id.to_numpy().tolist()\n\t\tself.assertTrue(np.array_equal(actual_ids, expected_ids))\n\t\tself.assertEqual(len(expected_ids), expected_num_layers)\n\t\t\t\t\n\t\treturn","def test_0():\n sync.gen_multi_fake_data()#default is only one randomly selected data set\n sync.main(testing=True)","def iv_gen():\r\n rndiv = os.urandom(16)\r\n return rndiv","def test_get_sample_ids(self):\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\n parse_metadata_state_descriptions('Study:Twin')), [])\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\n parse_metadata_state_descriptions('Study:Dog')), ['a','b'])\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\n parse_metadata_state_descriptions('Study:*,!Dog')), ['c','d','e'])\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\n parse_metadata_state_descriptions('Study:*,!Dog;BodySite:Stool')), ['e'])\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\n parse_metadata_state_descriptions('BodySite:Stool')), ['a','b','e'])","def test_periodic_boundary_two_ring_rod_different_nelems():\n\n ring_rod_1 = MockRingRod(5)\n ring_rod_2 = MockRingRod(3)\n block_structure = MemoryBlockCosseratRod([ring_rod_1, ring_rod_2], [0, 1])\n\n correct_periodic_boundary_node_idx = np.array(\n [[0, 6, 7, 9, 13, 14], [5, 1, 2, 12, 10, 11]], dtype=np.int64\n )\n correct_periodic_boundary_elem_idx = np.array(\n [[0, 6, 9, 13], [5, 1, 12, 10]], dtype=np.int64\n )\n correct_periodic_boundary_voronoi_idx = np.array([[0, 9], [5, 12]], dtype=np.int64)\n\n assert_allclose(\n correct_periodic_boundary_node_idx,\n block_structure.periodic_boundary_nodes_idx,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_periodic_boundary_elem_idx,\n block_structure.periodic_boundary_elems_idx,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_periodic_boundary_voronoi_idx,\n block_structure.periodic_boundary_voronoi_idx,\n atol=Tolerance.atol(),\n )\n\n correct_start_node_idx = np.array([1, 10], dtype=np.int64)\n correct_end_node_idx = np.array([6, 13], dtype=np.int64)\n\n correct_start_elem_idx = np.array([1, 10], dtype=np.int64)\n correct_end_elem_idx = np.array([6, 13], dtype=np.int64)\n\n correct_start_voronoi_idx = np.array([1, 10], dtype=np.int64)\n correct_end_voronoi_idx = np.array([6, 13], dtype=np.int64)\n\n assert_allclose(\n correct_start_node_idx,\n block_structure.start_idx_in_rod_nodes,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_node_idx,\n block_structure.end_idx_in_rod_nodes,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_start_elem_idx,\n block_structure.start_idx_in_rod_elems,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_elem_idx,\n block_structure.end_idx_in_rod_elems,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_start_voronoi_idx,\n block_structure.start_idx_in_rod_voronoi,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_voronoi_idx,\n block_structure.end_idx_in_rod_voronoi,\n atol=Tolerance.atol(),\n )","def __data_generation(self, list_IDs_temp):\n\n # Initialization\n X = np.empty((self.batch_size, self.grid_dim, self.grid_dim, self.grid_dim, self.n_channels))\n y = np.empty(self.batch_size, dtype=int)\n\n # Generate data\n for i, ID in enumerate(list_IDs_temp):\n # Store sample\n X[i], y[i] = pro_lig_reader_sample(ID[0], ID[1], self.grid_size, self.n_channels, self.grid_resolution)\n return X, keras.utils.to_categorical(y, num_classes=self.n_classes)"],"string":"[\n \"def test_generate_spin_id_data_array1(self):\\n\\n # The data.\\n data = ['1', 'GLY']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\\n\\n # Test the string.\\n self.assertEqual(id, ':1')\",\n \"def test_generate_spin_id_data_array6(self):\\n\\n # The data.\\n data = ['1', 'GLY', None, None]\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\\n\\n # Test the string.\\n self.assertEqual(id, ':1')\",\n \"def test_generate_spin_id_data_array5(self):\\n\\n # The data.\\n data = ['Ap4Aase', '1', 'GLY', '234', 'NH']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5)\\n\\n # Test the string.\\n self.assertEqual(id, '#Ap4Aase:1@234')\",\n \"def test_generate_spin_id_data_array3(self):\\n\\n # The data.\\n data = ['Ap4Aase', '234', 'NH']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=None, res_name_col=None, spin_num_col=2, spin_name_col=3)\\n\\n # Test the string.\\n self.assertEqual(id, '#Ap4Aase@234')\",\n \"def test_generate_spin_id_data_array4(self):\\n\\n # The data.\\n data = ['Ap4Aase', '1', 'GLY']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3)\\n\\n # Test the string.\\n self.assertEqual(id, '#Ap4Aase:1')\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_id_array(self):\\n arr = vtk.vtkIdTypeArray()\\n arr.SetNumberOfTuples(10)\\n for i in range(10):\\n arr.SetValue(i, i)\\n\\n np = array_handler.vtk2array(arr)\\n self.assertEqual(numpy.all(np == range(10)), True)\",\n \"def test_random_id(self):\\r\\n ids = \\\\\\r\\n \\\"R27DLI_4812 R27DLI_600 R27DLI_727 U1PLI_403 U1PLI_8969\\\".split(\\r\\n )\\r\\n assert random_id(ids, {}) in ids\\r\\n # just test we got something from the list, don't add stochastic test\\r\",\n \"def createArrayFunc(self):\\r\\n minVal = int(self.spinBoxMin_2.value())\\r\\n maxVal = int(self.spinBoxMax_2.value())\\r\\n arrayLength = int(self.spinBoxLength_2.value())\\r\\n different = maxVal - minVal\\r\\n if self.checkBoxNoRepeate_2.isChecked():\\r\\n if different > arrayLength:\\r\\n def unique_rand(initial, limit, total):\\r\\n data = []\\r\\n i = 0\\r\\n while i < total:\\r\\n number = numpy.random.randint(initial, limit)\\r\\n if number not in data:\\r\\n data.append(number)\\r\\n i += 1\\r\\n return data\\r\\n\\r\\n self.UnsortedArray_2 = unique_rand(minVal, maxVal, arrayLength)\\r\\n else:\\r\\n err = \\\"Array length must be greater than difference between limits\\\"\\r\\n self.labelUnsortedArray_2.setText(str(err))\\r\\n\\r\\n else:\\r\\n self.UnsortedArray_2 = numpy.random.randint(minVal, maxVal, arrayLength)\\r\\n self.labelUnsortedArray_2.setText(str(self.UnsortedArray_2))\\r\\n self.SortedArray_2 = Insertion.sorting(self.UnsortedArray_2)\\r\\n self.labelSortedArray_2.setText(str(self.SortedArray_2))\\r\\n binaryMax = int(self.spinBoxMax_2.value())\\r\\n binaryMin = int(self.spinBoxMin_2.value())\\r\\n self.spinBoxBinary.setMaximum(binaryMax)\\r\\n self.spinBoxBinary.setMinimum(binaryMin)\\r\\n self.spinBoxIthSmallest.setMaximum(arrayLength + 1)\",\n \"def test_create_template(self):\\n m_size = 10\\n data = ecn.IDData(m_size)\\n self.assertEqual(np.shape(data.ID_MATRIX), (m_size, m_size))\\n self.assertEqual(sum(sum(data.ID_MATRIX)), m_size)\\n self.assertTrue((sum(data.ID_MATRIX) == np.ones(m_size)).all())\\n print('Finished testing template\\\\n')\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_spin_loop(self):\\n\\n # Spin data.\\n select = [1, 0]\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, 'N5')\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 2)\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_scan_id_list(self):\\n scan = '15,17'\\n ref_idx = [0,3]\\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_arr2vtkIdList(self):\\n a = [1, 2, 3, 4, 5]\\n p = array_handler.array2vtkIdList(a)\\n for i, j in enumerate(a): \\n self.assertEqual(p.GetId(i), j)\\n p = vtk.vtkIdList()\\n ident = id(p)\\n p = array_handler.array2vtkIdList(numpy.array(a), p)\\n for i, j in enumerate(a): \\n self.assertEqual(p.GetId(i), j)\\n self.assertEqual(id(p), ident)\\n \\n self.assertRaises(AssertionError, array_handler.array2vtkIdList,\\n [[1,2,3]])\",\n \"def test_split_id_otp(self):\\n public_id, otp, = pyhsm.yubikey.split_id_otp(\\\"ft\\\" * 16)\\n self.assertEqual(public_id, '')\\n self.assertEqual(otp, \\\"ft\\\" * 16)\\n\\n public_id, otp, = pyhsm.yubikey.split_id_otp(\\\"cc\\\" + \\\"ft\\\" * 16)\\n self.assertEqual(public_id, 'cc')\\n self.assertEqual(otp, \\\"ft\\\" * 16)\",\n \"def test_spin_type(get_pdos_generator_inputs):\\n with pytest.raises(NotImplementedError):\\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=spin_type)\\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=SpinType.COLLINEAR)\\n for namespace in [builder.scf, builder.nscf]:\\n parameters = namespace['pw']['parameters'].get_dict()\\n assert parameters['SYSTEM']['nspin'] == 2\\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}\",\n \"def _get_rand_array(self):\\n pass\",\n \"def test_spin_loop_no_selection(self):\\n\\n # Spin data.\\n select = [0, 1, 0, 0, 1, 1, 0, 1]\\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 8)\",\n \"def test_get_ids(civic, main_data, updated_data):\\n assert len(civic._get_ids(main_data['assertions'])) == 0\\n assert len(civic._get_ids(main_data['variants'])) == 1\\n assert len(civic._get_ids(main_data['genes'])) == 2\\n assert len(civic._get_ids(main_data['evidence'])) == 1\\n\\n assert len(civic._get_ids(updated_data['assertions'])) == 1\\n assert len(civic._get_ids(updated_data['variants'])) == 1\\n assert len(civic._get_ids(updated_data['genes'])) == 1\\n assert len(civic._get_ids(updated_data['evidence'])) == 1\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def generate_T(number_obeservations):\\n T = np.random.randint(0, 2, (number_obeservations,1))\\n return T\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_weyl_specialize_id(self):\\n a, b, c = 0.0, 0.0, 0.0\\n for da, db, dc in DELTAS:\\n for k1l, k1r, k2l, k2r in K1K2SB:\\n k1 = np.kron(k1l.data, k1r.data)\\n k2 = np.kron(k2l.data, k2r.data)\\n self.check_two_qubit_weyl_specialization(\\n k1 @ Ud(a + da, b + db, c + dc) @ k2,\\n 0.999,\\n TwoQubitWeylIdEquiv,\\n {\\\"rz\\\": 4, \\\"ry\\\": 2},\\n )\",\n \"def _apply_array_spin123(self,\\n h1e: 'Nparray',\\n h2e: 'Nparray',\\n h3e: 'Nparray',\\n dvec: Optional[Tuple['Nparray', 'Nparray']] = None,\\n evec: Optional[Tuple['Nparray', 'Nparray', 'Nparray', 'Nparray']] \\\\\\n = None) -> 'Nparray':\\n norb = self.norb()\\n assert h3e.shape == (norb * 2,) * 6\\n assert not (dvec is None) ^ (evec is None)\\n\\n from1234 = (dvec is not None) and (evec is not None)\\n\\n nh1e = numpy.copy(h1e)\\n nh2e = numpy.copy(h2e)\\n\\n for i in range(norb * 2):\\n for j in range(norb * 2):\\n for k in range(norb * 2):\\n nh2e[j, k, :, :] += (-h3e[k, j, i, i, :, :] -\\n h3e[j, i, k, i, :, :] -\\n h3e[j, k, i, :, i, :])\\n\\n nh1e[:, :] += h3e[:, i, j, i, j, :]\\n\\n out = self._apply_array_spin12_halffilling(nh1e, nh2e)\\n\\n n = norb # This is just shorter\\n if not from1234:\\n symfac = 2.0\\n axes = ((1, 3), (0, 1))\\n (odveca, odvecb) = self.calculate_dvec_spin()\\n dveca = numpy.zeros_like(odveca)\\n dvecb = numpy.zeros_like(odvecb)\\n\\n for i in range(norb):\\n for j in range(norb):\\n evecaa, _ = self._calculate_dvec_spin_with_coeff(\\n odveca[i, j, :, :])\\n evecab, evecbb = self._calculate_dvec_spin_with_coeff(\\n odvecb[i, j, :, :])\\n\\n dveca += numpy.tensordot(h3e[:n, :n, i, :n, :n, j],\\n evecaa,\\n axes=axes)\\n dveca += numpy.tensordot(h3e[:n, :n, n + i, :n, :n, n + j],\\n evecab,\\n axes=axes) * symfac\\n dveca += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\\n evecbb,\\n axes=axes)\\n\\n dvecb += numpy.tensordot(h3e[n:, :n, i, n:, :n, j],\\n evecaa,\\n axes=axes)\\n dvecb += numpy.tensordot(h3e[n:, :n, n + i, n:, :n, n + j],\\n evecab,\\n axes=axes) * symfac\\n dvecb += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\\n evecbb,\\n axes=axes)\\n else:\\n symfac = 1.0\\n axes = ((1, 4, 2, 5), (0, 1, 2, 3)) # type: ignore\\n dveca, dvecb = dvec # type: ignore\\n evecaa, evecab, evecba, evecbb = evec # type: ignore\\n\\n dveca = numpy.tensordot(h3e[:n, :n, :n, :n, :n, :n],\\n evecaa, axes=axes) \\\\\\n + numpy.tensordot(h3e[:n, :n, n:, :n, :n, n:],\\n evecab, axes=axes) * symfac \\\\\\n + numpy.tensordot(h3e[:n, n:, n:, :n, n:, n:],\\n evecbb, axes=axes) + \\\\\\n + numpy.tensordot(h3e[:n, n:, :n, :n, n:, :n],\\n evecba, axes=axes)\\n\\n dvecb = numpy.tensordot(h3e[n:, :n, :n, n:, :n, :n],\\n evecaa, axes=axes) \\\\\\n + numpy.tensordot(h3e[n:, :n, n:, n:, :n, n:],\\n evecab, axes=axes) * symfac \\\\\\n + numpy.tensordot(h3e[n:, n:, n:, n:, n:, n:],\\n evecbb, axes=axes) + \\\\\\n + numpy.tensordot(h3e[n:, n:, :n, n:, n:, :n],\\n evecba, axes=axes)\\n\\n out -= self._calculate_coeff_spin_with_dvec((dveca, dvecb))\\n return out\",\n \"def test_pol_id_list(self):\\n pol = '0,1'\\n ref_idx = []\\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_scan_id_range(self):\\n scan = '16~17'\\n ref_idx = [1,2,3]\\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_sampleId_pairs(self):\\r\\n # expected values\\r\\n dose_vps = \\\\\\r\\n [('1xDose', '2xDose'), ('1xDose', 'Control'),\\r\\n ('2xDose', 'Control')]\\r\\n ttd_vps = \\\\\\r\\n [('31', '21'), ('31', '55'), ('31', '67'), ('21', '55'),\\r\\n ('21', '67'), ('55', '67')]\\r\\n dose_sids = \\\\\\r\\n [(['Sam1', 'Sam2', 'Sam6'], ['Sam3', 'Sam4']),\\r\\n (['Sam1', 'Sam2', 'Sam6'], ['Sam5']),\\r\\n (['Sam3', 'Sam4'], ['Sam5'])]\\r\\n ttd_sids = \\\\\\r\\n [(['Sam1'], ['Sam3']),\\r\\n (['Sam1'], ['Sam4', 'Sam6']),\\r\\n (['Sam1'], ['Sam2', 'Sam5']),\\r\\n (['Sam3'], ['Sam4', 'Sam6']),\\r\\n (['Sam3'], ['Sam2', 'Sam5']),\\r\\n (['Sam4', 'Sam6'], ['Sam2', 'Sam5'])]\\r\\n\\r\\n # observed values\\r\\n obs_dose_sids, obs_dose_vps = sampleId_pairs(self.mapping_data,\\r\\n self.rarefaction_data, 'Dose')\\r\\n obs_ttd_sids, obs_ttd_vps = sampleId_pairs(self.mapping_data,\\r\\n self.rarefaction_data, 'TTD')\\r\\n\\r\\n # sort -- order is unimportant and depends on way presented in mf\\r\\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\\r\\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())\\r\\n self.assertEqual(ttd_vps.sort(), obs_ttd_vps.sort())\\r\\n self.assertEqual(ttd_sids.sort(), obs_ttd_sids.sort())\\r\\n\\r\\n # check errors when no samples had this category\\r\\n self.assertRaises(ValueError, sampleId_pairs, self.mapping_data,\\r\\n self.rarefaction_data, 'DNE')\\r\\n\\r\\n # check no error if map file has more sampleids than rarefaction data\\r\\n superset_mf = \\\\\\r\\n ['#SampleID\\\\tDose\\\\tLinkerPrimerSequence\\\\tWeight\\\\tTTD\\\\tDescription',\\r\\n '#Comment Line',\\r\\n 'Sam1\\\\t1xDose\\\\tATCG\\\\tHigh\\\\t31\\\\ts1_desc',\\r\\n 'Sam2\\\\t1xDose\\\\tACCG\\\\tLow\\\\t67\\\\ts2_desc',\\r\\n 'Sam3\\\\t2xDose\\\\tACGT\\\\tMed\\\\t21\\\\ts3_desc',\\r\\n 'Sam4\\\\t2xDose\\\\tAACG\\\\tLow\\\\t55\\\\ts4_desc',\\r\\n 'Sam5\\\\tControl\\\\tCGTC\\\\tLow\\\\t67\\\\ts5_desc',\\r\\n 'Sam6\\\\t1xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts6_desc',\\r\\n 'Sam7\\\\t4xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts7_desc',\\r\\n 'Sam8\\\\t3xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts8_desc',\\r\\n 'Sam9\\\\t1xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts9_desc']\\r\\n # (mf, comments)\\r\\n superset_mf = parse_mapping_file_to_dict(superset_mf)[0]\\r\\n obs_dose_sids, obs_dose_vps = sampleId_pairs(superset_mf,\\r\\n self.rarefaction_data, 'Dose')\\r\\n\\r\\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\\r\\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())\",\n \"def test_random_integers(self):\\r\\n # Check over two calls to see if the random state is correctly updated.\\r\\n random = RandomStreams(utt.fetch_seed())\\r\\n fn = function([], random.random_integers((20, 20), -5, 5))\\r\\n fn_val0 = fn()\\r\\n fn_val1 = fn()\\r\\n\\r\\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\\r\\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\\r\\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\\r\\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\\r\\n\\r\\n assert numpy.all(fn_val0 == numpy_val0)\\r\\n assert numpy.all(fn_val1 == numpy_val1)\",\n \"def test_id_rot():\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_axis_angle(pr.a_id))\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_quaternion(pr.q_id))\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_xyz(pr.e_xyz_id))\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_zyx(pr.e_zyx_id))\",\n \"def test_random_integers(self):\\r\\n # Check over two calls to see if the random state is correctly updated.\\r\\n m = Module()\\r\\n m.random = RandomStreams(utt.fetch_seed())\\r\\n m.fn = Method([], m.random.random_integers((20,20), -5, 5))\\r\\n\\r\\n made = m.make()\\r\\n made.random.initialize()\\r\\n fn_val0 = made.fn()\\r\\n fn_val1 = made.fn()\\r\\n\\r\\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\\r\\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\\r\\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\\r\\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\\r\\n\\r\\n assert numpy.all(fn_val0 == numpy_val0)\\r\\n assert numpy.all(fn_val1 == numpy_val1)\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_create_tornado_id(self):\\n\\n this_id_string = tornado_io.create_tornado_id(\\n start_time_unix_sec=TORNADO_START_TIME_UNIX_SEC,\\n start_latitude_deg=TORNADO_START_LATITUDE_DEG,\\n start_longitude_deg=TORNADO_START_LONGITUDE_DEG)\\n\\n self.assertTrue(this_id_string == TORNADO_ID_STRING)\",\n \"def test_spin_type(fixture_code, generate_structure):\\n code = fixture_code('quantumespresso.pw')\\n structure = generate_structure()\\n\\n with pytest.raises(NotImplementedError):\\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\\n PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=spin_type)\\n\\n builder = PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=SpinType.COLLINEAR)\\n\\n for namespace in [builder.relax['base'], builder.scf, builder.bands]:\\n parameters = namespace['pw']['parameters'].get_dict()\\n assert parameters['SYSTEM']['nspin'] == 2\\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}\",\n \"def test_main(data, tmp_path):\\n\\n main(data, tmp_path)\\n\\n FILES = (\\n \\\"gd32f888x(0-1)xx-pinctrl.h\\\",\\n \\\"gd32f888x(2-3)xx-pinctrl.h\\\",\\n \\\"gd32f888y(0-1)xx-pinctrl.h\\\",\\n \\\"gd32f999x(0-1)xx-pinctrl.h\\\",\\n \\\"gd32f999x(2-3)xx-pinctrl.h\\\",\\n \\\"gd32f999y(0-1)xx-pinctrl.h\\\",\\n )\\n\\n for file in FILES:\\n ref_file = data / file\\n gen_file = tmp_path / file\\n\\n assert gen_file.exists()\\n\\n with open(ref_file) as ref, open(gen_file) as gen:\\n assert ref.read() == gen.read()\",\n \"def test_rand_func2(self):\\n for i in range(0, 100000):\\n num = random.randint(0, 32535143990)\\n func2_comp(num)\",\n \"def test_generateuuids(self):\\n ret1 = {\\\"message\\\": \\\"No Random.org api key or api version found.\\\", \\\"res\\\": False}\\n self.assertDictEqual(random_org.generateUUIDs(), ret1)\\n\\n ret2 = {\\\"message\\\": \\\"Required argument, number is missing.\\\", \\\"res\\\": False}\\n self.assertDictEqual(\\n random_org.generateUUIDs(api_key=\\\"peW\\\", api_version=\\\"1\\\"), ret2\\n )\\n\\n ret3 = {\\\"message\\\": \\\"Number of UUIDs must be between 1 and 1000\\\", \\\"res\\\": False}\\n self.assertDictEqual(\\n random_org.generateUUIDs(api_key=\\\"peW\\\", api_version=\\\"1\\\", number=\\\"5\\\"), ret3\\n )\\n\\n ret3 = {\\\"message\\\": \\\"Parameter 'apiKey' is malformed\\\", \\\"res\\\": False}\\n self.assertDictEqual(\\n random_org.generateUUIDs(api_key=\\\"peW\\\", api_version=\\\"1\\\", number=5), ret3\\n )\",\n \"def test_run_sim_1():\\n rnd = rand.Arrivals(36, 41)\\n sim.run_sim(3, 2, 5, 6, 22, rnd)\",\n \"def gen_data(min_coord, max_coord, size):\\r\\n data = np.random.randint(min_coord, max_coord, size)\\r\\n return data\",\n \"def test_id_get(mocker):\\n mocker.patch('serial.Serial.open')\\n mocker.patch('serial.Serial.flushInput')\\n css = mocker.patch('pysds011.driver.SDS011.cmd_set_sleep')\\n css.return_value = True\\n cfv = mocker.patch('pysds011.driver.SDS011.cmd_firmware_ver')\\n cfv.return_value = {'id': b'\\\\x12\\\\x34', 'paperino': 'maciomicio'}\\n runner = CliRunner()\\n result = runner.invoke(main, ['id'])\\n\\n calls = [call(0, id=b'\\\\xff\\\\xff'), call(1, id=b'\\\\xff\\\\xff')]\\n css.assert_has_calls(calls, any_order=False)\\n\\n assert '12' in result.output and '34' in result.output\\n assert result.exit_code == 0\",\n \"def get_test_split(self, fraction=0.1):\\n rng = np.random.default_rng(42)\\n test_size = int(round(len(self.all_asset_ids) * fraction))\\n test_ids = rng.choice(self.all_asset_ids, size=test_size, replace=False)\\n train_ids = [i for i in self.all_asset_ids if i not in test_ids]\\n return train_ids, test_ids\",\n \"def test_brains_id_get(self):\\n pass\",\n \"def test_get_tid():\\n tids = []\\n def _foo():\\n mytid = yield GetTid()\\n tids.append(mytid)\\n for i in range(5):\\n yield i\\n\\n scheduler = Scheduler()\\n scheduler.new(_foo())\\n scheduler.new(_foo())\\n scheduler.mainloop()\\n\\n # can we do better than hard code?\\n assert tids == [4, 5]\",\n \"def test_get_data_array():\\n test_file = os.path.join(DATA_PATH, \\\"paper_test_file.uvh5\\\")\\n test_uv = UVData()\\n test_uv.read(test_file)\\n\\n baseline_array = np.array(list(set(test_uv.baseline_array)))\\n data_array = utils.get_data_array(test_uv, reds=baseline_array)\\n\\n compare_data = np.zeros(\\n (test_uv.Npols, test_uv.Nbls, test_uv.Ntimes, test_uv.Nfreqs),\\n dtype=np.complex64,\\n )\\n\\n pol_array = uvutils.polnum2str(test_uv.polarization_array)\\n for pol_cnt, pol in enumerate(pol_array):\\n for cnt, baseline in enumerate(list(set(test_uv.baseline_array))):\\n ant_1, ant_2 = test_uv.baseline_to_antnums(baseline)\\n compare_data[pol_cnt, cnt] = test_uv.get_data(ant_1, ant_2, pol)\\n\\n compare_data = compare_data.squeeze(axis=0)\\n assert np.allclose(compare_data, data_array)\",\n \"def test_periodic_boundary_two_ring_rod():\\n\\n n_elems = 5\\n ring_rod_1 = MockRingRod(n_elems)\\n ring_rod_2 = MockRingRod(n_elems)\\n block_structure = MemoryBlockCosseratRod([ring_rod_1, ring_rod_2], [0, 1])\\n\\n correct_periodic_boundary_node_idx = np.array(\\n [[0, 6, 7, 9, 15, 16], [5, 1, 2, 14, 10, 11]], dtype=np.int64\\n )\\n correct_periodic_boundary_elem_idx = np.array(\\n [[0, 6, 9, 15], [5, 1, 14, 10]], dtype=np.int64\\n )\\n correct_periodic_boundary_voronoi_idx = np.array([[0, 9], [5, 14]], dtype=np.int64)\\n\\n assert_allclose(\\n correct_periodic_boundary_node_idx,\\n block_structure.periodic_boundary_nodes_idx,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_periodic_boundary_elem_idx,\\n block_structure.periodic_boundary_elems_idx,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_periodic_boundary_voronoi_idx,\\n block_structure.periodic_boundary_voronoi_idx,\\n atol=Tolerance.atol(),\\n )\\n\\n correct_start_node_idx = np.array([1, 10], dtype=np.int64)\\n correct_end_node_idx = np.array([6, 15], dtype=np.int64)\\n\\n correct_start_elem_idx = np.array([1, 10], dtype=np.int64)\\n correct_end_elem_idx = np.array([6, 15], dtype=np.int64)\\n\\n correct_start_voronoi_idx = np.array([1, 10], dtype=np.int64)\\n correct_end_voronoi_idx = np.array([6, 15], dtype=np.int64)\\n\\n assert_allclose(\\n correct_start_node_idx,\\n block_structure.start_idx_in_rod_nodes,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_node_idx,\\n block_structure.end_idx_in_rod_nodes,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_start_elem_idx,\\n block_structure.start_idx_in_rod_elems,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_elem_idx,\\n block_structure.end_idx_in_rod_elems,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_start_voronoi_idx,\\n block_structure.start_idx_in_rod_voronoi,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_voronoi_idx,\\n block_structure.end_idx_in_rod_voronoi,\\n atol=Tolerance.atol(),\\n )\",\n \"def generate_new_ids(ids: np.array, n_required: int) -> np.array:\\n\\n current_max_id = ids.max()\\n new_ids = np.arange(n_required) + current_max_id + 1\\n\\n return new_ids\",\n \"def test_return_spin_pipe_fail(self):\\n\\n # Try to get a spin from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')\",\n \"def test_SampleIds(self):\\r\\n exp = [\\\"PC.354\\\", \\\"PC.355\\\", \\\"PC.356\\\", \\\"PC.481\\\", \\\"PC.593\\\", \\\"PC.607\\\",\\r\\n \\\"PC.634\\\", \\\"PC.635\\\", \\\"PC.636\\\"]\\r\\n obs = self.overview_map.SampleIds\\r\\n self.assertEqual(obs, exp)\\r\\n\\r\\n obs = self.no_metadata.SampleIds\\r\\n self.assertEqual(obs, exp)\\r\\n\\r\\n obs = self.empty_map.SampleIds\\r\\n self.assertEqual(obs, [])\",\n \"def test_pol_id_range(self):\\n pol = '0~1'\\n ref_idx = []\\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_assign_resources_to_tmc_subarray_in_low():\",\n \"def _spin_sequence(self):\\n self.return_position = self.motor.position\\n \\n for spin_num in range(self.num_spins):\\n self.taxi()\\n\\n det_pre_acquire(self.detector)\\n self.fly()\\n det_post_acquire(self.detector)\\n\\n while self.detector.hdf1.write_file.value:\\n time.sleep(0.01) # wait for file to be written\\n\\n event = OrderedDict()\\n event[\\\"time\\\"] = time.time()\\n event[\\\"seq_num\\\"] = spin_num + 1\\n event[\\\"data\\\"] = {}\\n event[\\\"timestamps\\\"] = {}\\n for d_item in (self.detector.hdf1.full_file_name,):\\n d = d_item.read()\\n for k, v in d.items():\\n event['data'][k] = v['value']\\n event['timestamps'][k] = v['timestamp']\\n\\n self._data.append(event)\\n\\n self.set(\\\"Return\\\")\\n self._completion_status._finished(success=True)\",\n \"def test_uuid():\\n for _ in range(1000):\\n uuid = uuid_generator()\\n assert len(uuid) == 36\\n assert uuid.count('-') == 4\",\n \"def test_SampleIds(self):\\n exp = [\\\"PC.354\\\", \\\"PC.355\\\", \\\"PC.356\\\", \\\"PC.481\\\", \\\"PC.593\\\", \\\"PC.607\\\",\\n \\\"PC.634\\\", \\\"PC.635\\\", \\\"PC.636\\\"]\\n obs = self.overview_map.SampleIds\\n self.assertEqual(obs, exp)\\n\\n obs = self.no_metadata.SampleIds\\n self.assertEqual(obs, exp)\\n\\n obs = self.empty_map.SampleIds\\n self.assertEqual(obs, [])\",\n \"def test_run_sim():\\n rnd = rand.Arrivals(31, 40)\\n sim.run_sim(2, 1, 3, 4, 24, rnd)\",\n \"def myID() -> np.int:\\r\\n return 304976335\",\n \"def myID() -> np.int:\\r\\n return 304976335\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_ids(self):\\n # AdapterID inherited from IOAdapter\\n self.assertEqual('553713696', self.sriovs[0].id)\\n self.assertEqual(1, self.sriovs[0].sriov_adap_id)\\n\\n self.assertEqual('553713680', self.sriovs[2].id)\\n self.assertIsNone(self.sriovs[2].sriov_adap_id)\",\n \"def generate_raiz():\\n\\treturn os.urandom(12)\",\n \"def test_assign_resources_to_tmc_subarray_in_mid():\",\n \"def test_periodic_boundary_one_ring_rod():\\n\\n n_elems = 5\\n ring_rod = MockRingRod(n_elems)\\n block_structure = MemoryBlockCosseratRod([ring_rod], [0])\\n\\n correct_periodic_boundary_node_idx = np.array(\\n [[0, 6, 7], [5, 1, 2]], dtype=np.int64\\n )\\n correct_periodic_boundary_elem_idx = np.array([[0, 6], [5, 1]], dtype=np.int64)\\n correct_periodic_boundary_voronoi_idx = np.array([[0], [5]], dtype=np.int64)\\n\\n assert_allclose(\\n correct_periodic_boundary_node_idx,\\n block_structure.periodic_boundary_nodes_idx,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_periodic_boundary_elem_idx,\\n block_structure.periodic_boundary_elems_idx,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_periodic_boundary_voronoi_idx,\\n block_structure.periodic_boundary_voronoi_idx,\\n atol=Tolerance.atol(),\\n )\\n\\n correct_start_node_idx = np.array([1], dtype=np.int64)\\n correct_end_node_idx = np.array([6], dtype=np.int64)\\n\\n correct_start_elem_idx = np.array([1], dtype=np.int64)\\n correct_end_elem_idx = np.array([6], dtype=np.int64)\\n\\n correct_start_voronoi_idx = np.array([1], dtype=np.int64)\\n correct_end_voronoi_idx = np.array([6], dtype=np.int64)\\n\\n assert_allclose(\\n correct_start_node_idx,\\n block_structure.start_idx_in_rod_nodes,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_node_idx,\\n block_structure.end_idx_in_rod_nodes,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_start_elem_idx,\\n block_structure.start_idx_in_rod_elems,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_elem_idx,\\n block_structure.end_idx_in_rod_elems,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_start_voronoi_idx,\\n block_structure.start_idx_in_rod_voronoi,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_voronoi_idx,\\n block_structure.end_idx_in_rod_voronoi,\\n atol=Tolerance.atol(),\\n )\",\n \"def test_correct_binid(self):\\n\\n maps = Maps(plateifu='8485-1901', release='DR17', bintype='HYB10')\\n spaxel = maps[22, 14]\\n\\n assert isinstance(spaxel, Spaxel)\\n assert spaxel.x == 14, spaxel.y == 22\\n\\n bin_spaxels = spaxel.stellar_vel.bin.get_bin_spaxels()\\n\\n for sp in bin_spaxels:\\n\\n sp.load()\\n assert sp.stellar_vel.bin.binid == spaxel.stellar_vel.bin.binid\\n\\n sp_bin = maps[sp.y, sp.x]\\n assert sp_bin.stellar_vel.bin.binid == spaxel.stellar_vel.bin.binid\",\n \"def test_id_set(mocker):\\n mocker.patch('serial.Serial.open')\\n mocker.patch('serial.Serial.flushInput')\\n css = mocker.patch('pysds011.driver.SDS011.cmd_set_sleep')\\n css.return_value = True\\n csi = mocker.patch('pysds011.driver.SDS011.cmd_set_id')\\n runner = CliRunner()\\n result = runner.invoke(main, ['--id', 'cccc', 'id', 'abcd'])\\n\\n # Two calls to cmd_set_sleep:\\n # the first use original address\\n # at the second one, the sensor has a new address: so sleep\\n # has the use the new one\\n calls = [call(0, id=b'\\\\xcc\\\\xcc'), call(1, id=b'\\\\xab\\\\xcd')]\\n css.assert_has_calls(calls, any_order=False)\\n csi.assert_called_once_with(id=b'\\\\xcc\\\\xcc', new_id=b'\\\\xab\\\\xcd')\\n assert result.exit_code == 0\",\n \"def generaterandomindices(dataSize, percentTest):\\n\\n TrainIndices = np.array([])\\n while TrainIndices.__len__() < int(percentTest * dataSize):\\n # Randomly select an index value and store it. If it has already been chosen, pick again.\\n index = int(random.random() * dataSize)\\n if not TrainIndices.__contains__(index):\\n TrainIndices = np.append(TrainIndices, [index])\\n\\n # For aesthetic purposes:\\n TrainIndices = np.sort(TrainIndices)\\n\\n return TrainIndices\",\n \"def generate_fake_data(t0, num_array, period=5820, data_range=[0.0, 24.0],\\n cyclic=True):\\n\\n if cyclic:\\n uts_root = np.mod(t0, period)\\n data = (np.mod(uts_root + num_array, period)\\n * (np.diff(data_range)[0] / np.float64(period))) + data_range[0]\\n else:\\n data = ((t0 + num_array) / period).astype(int)\\n\\n return data\",\n \"def _generate_id() -> str:\\n return \\\"\\\".join(sample(\\\"abcdefghjkmopqrstuvqxyz\\\", 16))\",\n \"def data_gen(size, p):\\n #print(np.random.get_state()[1][0])\\n random_table = np.random.binomial(size = size, p = p, n = 1)\\n test_array = np.zeros((size, 2), dtype = int)\\n for i in range(size):\\n test_array[i,0] = i\\n test_array[i,1] = random_table[i]\\n return test_array\",\n \"def generate_subsegment_id():\\n return uuid.uuid4().hex[:16]\",\n \"def test_run_a_scan_on_sdp_subarray_in_mid():\",\n \"def test_returned_num_in_random_nums(self):\\n self._setup_random_gen([1.], [42])\\n self.assertEqual(self._random_gen.next_num(), 42)\",\n \"def test_CreateROI1(self):\\r\\n\\r\\n self.delayDisplay(\\\"Starting the test\\\")\\r\\n #\\r\\n # first, get some data\\r\\n #\\r\\n import urllib\\r\\n downloads = (\\r\\n ('http://slicer.kitware.com/midas3/download?items=5767', 'FA.nrrd', slicer.util.loadVolume),\\r\\n )\\r\\n\\r\\n for url,name,loader in downloads:\\r\\n filePath = slicer.app.temporaryPath + '/' + name\\r\\n if not os.path.exists(filePath) or os.stat(filePath).st_size == 0:\\r\\n logging.info('Requesting download %s from %s...\\\\n' % (name, url))\\r\\n urllib.urlretrieve(url, filePath)\\r\\n if loader:\\r\\n logging.info('Loading %s...' % (name,))\\r\\n loader(filePath)\\r\\n self.delayDisplay('Finished with download and loading')\\r\\n\\r\\n volumeNode = slicer.util.getNode(pattern=\\\"FA\\\")\\r\\n logic = CreateROILogic()\\r\\n self.assertIsNotNone( logic.hasImageData(volumeNode) )\\r\\n self.delayDisplay('Test passed!')\",\n \"def test_residue_loop(self):\\n\\n # Loop over the residues.\\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\\n # Test the selection.\\n self.assertEqual(res.num, 2)\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)\",\n \"def test_scan_id_exprlist(self):\\n scan = '15,>16'\\n ref_idx = [0,3]\\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def generate_synth_data(n):\",\n \"def generateRegistrationId():\\n regId = KeyHelper.getRandomSequence()\\n return regId\",\n \"def test_generate(self):\\n cant_interations = int(random()*100)\\n for i in range(cant_interations):\\n number = self.sudoku.generate() # Generate number\\n self.assertGreaterEqual(number, 0) # number >= 0\\n self.assertLessEqual(number, 8) # number <= 8\",\n \"def test_test_ids_request(get_interface_params):\\n from sail_on_client.protocol.localinterface import LocalInterface\\n\\n config_directory, config_name = get_interface_params\\n data_dir = f\\\"{os.path.dirname(__file__)}/data\\\"\\n local_interface = LocalInterface(config_name, config_directory)\\n\\n assumptions_path = os.path.join(os.path.dirname(__file__), \\\"assumptions.json\\\")\\n filename = local_interface.test_ids_request(\\n \\\"OND\\\", \\\"image_classification\\\", \\\"5678\\\", assumptions_path\\n )\\n expected = os.path.join(data_dir, \\\"OND\\\", \\\"image_classification\\\", \\\"test_ids.csv\\\")\\n assert os.stat(expected).st_size > 5\\n assert expected == filename\",\n \"def get_sampled_ids(self):\\n seed = 123\\n #initiate two lists, to save randomly picked positive and negative cases respectively\\n positiveIds = []\\n negativeIds = []\\n i = 0\\n print \\\"==> resampling ... \\\",\\n while len(positiveIds)+len(negativeIds)<self.ntotal:\\n # start a loop from 0 to total size of the new sampe\\n # if it catches a number divisable by the sought ratio, update the list of positive cases ids\\n # otherwise keep update the list of negative cases ids\\n try:\\n if i%int(100 / self.posRate) == 0: \\n positiveIds.append(self.posId.next())\\n else:\\n negativeIds.append(self.negId.next())\\n except:\\n print \\\"Enter posRate higher than the initial rate\\\"\\n break\\n i+=1\\n print \\\"Done sampling\\\"\\n print \\\"positive:\\\", len(positiveIds)\\n print \\\"negative:\\\", len(negativeIds)\\n print \\\"final size:\\\", len(positiveIds)+len(negativeIds)\\n #return sorted list of the two list of ids combined\\n return sorted(positiveIds+negativeIds)\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def test_return_residue(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_residue(':1')\\n res2 = mol_res_spin.return_residue(selection=':2')\\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1.num, 1)\\n self.assertEqual(res1.name, None)\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2.num, 2)\\n self.assertEqual(res2.name, 'Glu')\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4.num, 4)\\n self.assertEqual(res4.name, 'Pro')\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5.num, -5)\\n self.assertEqual(res5.name, None)\\n self.assertEqual(res5.spin[1].name, 'N5')\",\n \"def test_if_array_is_good(self):\\n testing_param = random.randint(1, 100)\\n self.assertEqual(self.exercice.main(testing_param),\\n list(range(2, testing_param+1, 2)))\",\n \"def test_run_a_scan_on_sdp_subarray_in_low():\",\n \"def test_ipam_rirs_create(self):\\n pass\",\n \"def make_row(invalid_data=[]):\\n\\n ### Database Identifiers ###\\n \\n # phac_sample_id, valid/invalid error-grid information.\\n phac_sample_id, phac_sample_id_error = lib.random_phac_id(invalid_data)\\n # umbrella_bioproject_accession, valid/invalid error-grid information.\\n ub_accession, ub_accession_error = lib.umbrella_bioproject_accession(invalid_data)\\n # bioproject_accession, valid/invalid error-grid information.\\n bp_accession, bp_accession_error = lib.random_bioproject_accession(invalid_data)\\n # biosample_accession, valid/invalid error-grid information.\\n bs_accession, bs_accession_error = lib.random_biosample_accession(invalid_data)\\n # sra_accession, valid/invalid error-grid information.\\n sra_accession, sra_accession_error = lib.random_sra_accession(invalid_data)\\n # genbank_accession, valid/invalid error-grid information.\\n gb_accession, gb_accession_error = lib.random_genbank_accession(invalid_data)\\n # gisaid_accession, valid/invalid error-grid information.\\n gisaid_accession, gisaid_accession_error = lib.random_gisaid_accession(invalid_data)\\n \\n ### Sample Collection and Processing ###\\n \\n # sample_collected_by, valid/invalid error-grid information.\\n samp_col_by, samp_col_by_error = lib.random_agency(invalid_data)\\n # sample_collector_contact_email, valid/invalid error-grid information.\\n samp_col_email, samp_col_email_error = lib.random_email(invalid_data)\\n # sample_collector_contact_address, valid/invalid error-grid information.\\n samp_col_address, samp_col_address_error = lib.random_address(invalid_data)\\n # sequence_submitter_contact_email, valid/invalid error-grid information.\\n seq_sub_email, seq_sub_email_error = lib.random_email(invalid_data)\\n # sequence_submitter_contact_address, valid/invalid error-grid information.\\n seq_sub_address, seq_sub_address_error = lib.random_address(invalid_data)\\n # sample_collection_date, valid/invalid error-grid information.\\n samp_col_date, samp_col_date_error = lib.random_date(invalid_data)\\n # sample_received_date, valid/invalid error-grid information.\\n samp_rec_date, samp_rec_date_error = lib.random_date(invalid_data)\\n # geo_loc_name_country, valid/invalid error-grid information.\\n geo_loc_country, geo_loc_country_error = lib.random_country(invalid_data)\\n # geo_loc_name_province_territory, valid/invalid error-grid information.\\n geo_loc_prov_ter, geo_loc_prov_ter_error = lib.random_province_territory(invalid_data)\\n # geo_loc_name_city, valid/invalid error-grid information.\\n geo_loc_city, geo_loc_city_error = lib.random_city(invalid_data)\\n # organism, valid/invalid error-grid information.\\n organism, organism_error = lib.random_organism(invalid_data)\\n # purpose_of_sampling, valid/invalid error-grid information.\\n p_o_sampling, p_o_sampling_error = lib.random_purpose_of_sampling(invalid_data)\\n # anatomical_material, valid/invalid error-grid information.\\n anat_material, anat_material_error = lib.random_anatomical_material(invalid_data)\\n # anatomical_part, valid/invalid error-grid information.\\n anat_part, anat_part_error = lib.random_anatomical_part(invalid_data)\\n # body_product, valid/invalid error-grid information.\\n body_product, body_product_error = lib.random_body_product(invalid_data)\\n # environmental_material, valid/invalid error-grid information.\\n envi_material, envi_material_error = lib.random_environmental_material(invalid_data)\\n # environmental_site, valid/invalid error-grid information.\\n envi_site, envi_site_error = lib.random_environmental_site(invalid_data)\\n # collection_device, valid/invalid error-grid information.\\n col_device, col_device_error = lib.random_collection_device(invalid_data)\\n # collection_method, valid/invalid error-grid information.\\n col_method, col_method_error = lib.random_collection_method(invalid_data)\\n # collection_protocol, valid/invalid error-grid information.\\n col_protocol, col_protocol_error = lib.fake_protocol(invalid_data)\\n # specimen_processing, valid/invalid error-grid information.\\n spec_process, spec_process_error = lib.random_specimen_processing(invalid_data)\\n # lab_host, valid/invalid error-grid information.\\n lab_host, lab_host_error = lib.random_lab_host(invalid_data)\\n # passage_number , valid/invalid error-grid information.\\n passage_num, passage_num_error = lib.random_passage_number(invalid_data)\\n # passage_method, valid/invalid error-grid information.\\n passage_method, passage_method_error = lib.passage_method_text(invalid_data)\\n # biomaterial_extracted, valid/invalid error-grid information.\\n biom_extract, biom_extract_error = lib.random_biomaterial_extracted(invalid_data)\\n \\n ### Host Information ###\\n \\n # host_common_name, valid/invalid error-grid information.\\n host_com_name, host_com_name_error = lib.random_host_common_name(invalid_data)\\n # host_scientific_name, valid/invalid error-grid information.\\n host_sci_name, host_sci_name_error = lib.random_host_scientific_name(invalid_data)\\n # host_health_state, valid/invalid error-grid information.\\n host_health_state, host_health_state_error = lib.random_host_health_state(invalid_data)\\n # host_health_status_details, valid/invalid error-grid information.\\n host_health_status, host_health_status_error = lib.random_host_health_status_details(invalid_data)\\n # host_disease, valid/invalid error-grid information.\\n host_disease, host_disease_error = lib.random_host_disease(invalid_data)\\n # host_age, valid/invalid error-grid information.\\n host_age, host_age_error = lib.random_host_age(invalid_data)\\n # host_gender, valid/invalid error-grid information.\\n host_gender, host_gender_error = lib.random_host_gender(invalid_data)\\n # host_origin_geo_loc_name_country, valid/invalid error-grid information.\\n host_loc_country, host_loc_country_error = lib.random_country(invalid_data)\\n # host_subject_id, valid/invalid error-grid information.\\n host_sub_id, host_sub_id_error = lib.random_host_subject_id(invalid_data)\\n # symptom_onset_date, valid/invalid error-grid information.\\n symp_onset_date, symp_onset_date_error = lib.random_date(invalid_data)\\n # signs_and_symptoms, valid/invalid error-grid information.\\n signs_symptoms, signs_symptoms_error = lib.random_signs_symptoms(invalid_data)\\n \\n ### Host Exposure Information ###\\n \\n # location_of_exposure_geo_loc_name_country, valid/invalid error-grid information.\\n loc_exp_country, loc_exp_country_error = lib.random_country(invalid_data)\\n # travel_history, valid/invalid error-grid information. \\n trav_history, trav_history_error = lib.random_travel_history(invalid_data)\\n # exposure_event, valid/invalid error-grid information.\\n exp_event, exp_event_error = lib.random_exposure_event(invalid_data)\\n \\n ### Sequencing ###\\n \\n # minion_barcode, valid/invalid error-grid information.\\n minion_barcode, minion_barcode_error = lib.random_minIon_barcode(invalid_data)\\n # sequencing_instrument, valid/invalid error-grid information.\\n seq_instrument, seq_instrument_error = lib.random_seq_instrument(invalid_data)\\n # sequencing_protocol_name, valid/invalid error-grid information.\\n seq_prot_name, seq_prot_name_error = lib.fake_protocol(invalid_data)\\n # sequencing_protocol_source, valid/invalid error-grid information.\\n seq_prot_source, seq_prot_source_error = lib.random_seq_protocol_source(invalid_data)\\n # sequencing_kit_number, valid/invalid error-grid information.\\n seq_kit_num, seq_kit_num_error = lib.random_seq_kit_num(invalid_data)\\n # amplicon_pcr_primers_filename, valid/invalid error-grid information.\\n amp_pcr_filename, amp_pcr_filename_error = lib.random_txt_filename(invalid_data)\\n \\n ### Bioinformatics and QC metrics ###\\n \\n # raw_sequence_data_processing, valid/invalid error-grid information.\\n raw_seq_process, raw_seq_process_error = lib.random_seq_process(invalid_data)\\n # sequencing_depth_average, valid/invalid error-grid information.\\n seq_depth_avg, seq_depth_avg_error = lib.random_seq_depth(invalid_data)\\n # assembly_method, valid/invalid error-grid information.\\n assemb_method, assemb_method_error = lib.random_assembly_software(invalid_data)\\n # assembly_coverage_breadth, valid/invalid error-grid information.\\n assemb_cov_breadth, assemb_cov_breadth_error = lib.random_assembly_coverage_breadth(invalid_data)\\n # assembly_coverage_depth, valid/invalid error-grid information.\\n assemb_cov_depth, assemb_cov_depth_error = lib.random_seq_depth(invalid_data)\\n # r1_fastq_filename, valid/invalid error-grid information.\\n r1_filename, r1_filename_error = lib.random_fastq_filename(invalid_data)\\n # r2_fastq_filename, valid/invalid error-grid information.\\n r2_filename, r2_filename_error = lib.random_fastq_filename(invalid_data)\\n # r1_fastq_filepath, valid/invalid error-grid information.\\n r1_filepath, r1_filepath_error = lib.random_filepath(r1_filename, invalid_data)\\n # r2_fastq_filepath, valid/invalid error-grid information.\\n r2_filepath, r2_filepath_error = lib.random_filepath(r2_filename, invalid_data)\\n # fast5_filename, valid/invalid error-grid information.\\n fast5_filename, fast5_filename_error = lib.random_fast5_filename(invalid_data)\\n # fast5_filepath, valid/invalid error-grid information.\\n fast5_filepath, fast5_filepath_error = lib.random_filepath(fast5_filename, invalid_data)\\n # fasta_filename, valid/invalid error-grid information.\\n fasta_filename, fasta_filename_error = lib.random_fasta_filename(invalid_data)\\n # fasta_filepath, valid/invalid error-grid information.\\n fasta_filepath, fasta_filepath_error = lib.random_filepath(fasta_filename, invalid_data)\\n # number_base_pairs, valid/invalid error-grid information.\\n num_bp, num_bp_error = lib.random_bp_num(invalid_data)\\n # consensus_genome_length, valid/invalid error-grid information.\\n cons_genome_len, cons_genome_len_error = lib.random_genome_length(invalid_data)\\n # mean_contig_length, valid/invalid error-grid information.\\n mean_contig_len, mean_contig_len_error = lib.random_contig_length(invalid_data)\\n # n50, valid/invalid error-grid information.\\n n50, n50_error = lib.random_n50(invalid_data)\\n # ns_per_100_kbp, valid/invalid error-grid information.\\n ns_100kbp, ns_100kbp_error = lib.random_ns_100kbp(invalid_data)\\n # reference_genome_accession, valid/invalid error-grid information.\\n ref_genome_accession, ref_genome_accession_error = lib.random_ref_genome(invalid_data)\\n # consensus_sequence_id, valid/invalid error-grid information.\\n cons_seq_id, cons_seq_id_error = lib.random_consensus_seq_id(invalid_data)\\n # consensus_sequence_method, valid/invalid error-grid information.\\n cons_seq_method, cons_seq_method_error = lib.random_consensus_seq_method(invalid_data)\\n # consensus_sequence_filename, valid/invalid error-grid information.\\n cons_seq_filename, cons_seq_filename_error = lib.random_fasta_filename(invalid_data)\\n # consensus_sequence_filepath, valid/invalid error-grid information.\\n cons_seq_filepath, cons_seq_filepath_error = lib.random_filepath(cons_seq_filename, invalid_data)\\n # annotation_feature_table_filename, valid/invalid error-grid information.\\n annot_table_filename, annot_table_filename_error = lib.random_feature_table_filename(invalid_data)\\n # bioinformatics_protocol, valid/invalid error-grid information.\\n biof_protocol, biof_protocol_error = lib.bioinformatics_protocol(invalid_data)\\n \\n ### Pathogen Diagnostic Testing ###\\n \\n # gene_name_1, valid/invalid error-grid information.\\n gene_1, gene_1_error = lib.random_gene(invalid_data)\\n # diagnostic_pcr_protocol_1, valid/invalid error-grid information.\\n pcr_protocol_1, pcr_protocol_1_error = lib.fake_protocol(invalid_data)\\n # diagnostic_pcr_ct_value_1, valid/invalid error-grid information.\\n pcr_ct_1, pcr_ct_1_error = lib.random_pcr_ct_val(invalid_data)\\n # gene_name_2, valid/invalid error-grid information.\\n gene_2, gene_2_error = lib.random_gene(invalid_data)\\n # diagnostic_pcr_protocol_2, valid/invalid error-grid information.\\n pcr_protocol_2, pcr_protocol_2_error = lib.fake_protocol(invalid_data)\\n # diagnostic_pcr_ct_value_2, valid/invalid error-grid information.\\n pcr_ct_2, pcr_ct_2_error = lib.random_pcr_ct_val(invalid_data)\\n \\n ### Contributor Acknowledgement ###\\n \\n # authors, valid/invalid error-grid information.\\n authors, authors_error = lib.authors(invalid_data)\\n \\n ### Dependent IDs ###\\n \\n # specimen_collector_sample_id.\\n spec_col_sample_id, spec_col_sample_id_error = lib.random_specimen_collector_sample_id(\\n geo_loc_country, \\n geo_loc_prov_ter,\\n geo_loc_city,\\n invalid_data)\\n # irida_sample_name.\\n irida_sample_id = spec_col_sample_id\\n # sequence_submitted_by.\\n seq_sub_by = samp_col_by\\n # library_id, valid/invalid error-grid information.\\n library_id, library_id_error = lib.random_library_id(spec_col_sample_id, invalid_data)\\n # isolate.\\n isolate = spec_col_sample_id\\n # assembly_name, valid/invalid error-grid information.\\n assemb_name, assemb_name_error = lib.random_assembly_name(spec_col_sample_id, invalid_data)\\n\\n # Row of generated data organised by column.\\n cols = [spec_col_sample_id,\\n phac_sample_id,\\n irida_sample_id,\\n ub_accession,\\n bp_accession,\\n bs_accession,\\n sra_accession,\\n gb_accession,\\n gisaid_accession,\\n samp_col_by,\\n samp_col_email,\\n samp_col_address,\\n seq_sub_by,\\n seq_sub_email,\\n seq_sub_address,\\n samp_col_date,\\n samp_rec_date,\\n geo_loc_country,\\n geo_loc_prov_ter,\\n geo_loc_city,\\n organism,\\n isolate,\\n p_o_sampling,\\n anat_material,\\n anat_part,\\n body_product,\\n envi_material,\\n envi_site,\\n col_device,\\n col_method,\\n col_protocol,\\n spec_process,\\n lab_host,\\n passage_num,\\n passage_method,\\n biom_extract,\\n host_com_name,\\n host_sci_name,\\n host_health_state,\\n host_health_status,\\n host_disease,\\n host_age,\\n host_gender,\\n host_loc_country,\\n host_sub_id,\\n symp_onset_date,\\n signs_symptoms,\\n loc_exp_country,\\n trav_history,\\n exp_event,\\n library_id,\\n minion_barcode,\\n seq_instrument,\\n seq_prot_name,\\n seq_prot_source,\\n seq_kit_num,\\n amp_pcr_filename,\\n raw_seq_process,\\n seq_depth_avg,\\n assemb_name,\\n assemb_method,\\n assemb_cov_breadth,\\n assemb_cov_depth,\\n r1_filename,\\n r2_filename,\\n r1_filepath,\\n r2_filepath,\\n fast5_filename,\\n fast5_filepath,\\n fasta_filename,\\n fasta_filepath,\\n num_bp,\\n cons_genome_len,\\n mean_contig_len,\\n n50,\\n ns_100kbp,\\n ref_genome_accession,\\n cons_seq_id,\\n cons_seq_method,\\n cons_seq_filename,\\n cons_seq_filepath,\\n annot_table_filename,\\n biof_protocol,\\n gene_1,\\n pcr_protocol_1,\\n pcr_ct_1,\\n gene_2,\\n pcr_protocol_2,\\n pcr_ct_2,\\n authors]\\n\\n # Error grid valid/invalid (error specific) information.\\n grid = ['-', # spec_col_sample_id_error placeholder\\n phac_sample_id_error,\\n '-', # irida_sample_id_error placeholder\\n ub_accession_error,\\n bp_accession_error,\\n bs_accession_error,\\n sra_accession_error,\\n gb_accession_error,\\n gisaid_accession_error,\\n samp_col_by_error,\\n samp_col_email_error,\\n samp_col_address_error,\\n '-', # seq_sub_by_error placeholder\\n seq_sub_email_error,\\n seq_sub_address_error,\\n samp_col_date_error,\\n samp_rec_date_error,\\n geo_loc_country_error,\\n geo_loc_prov_ter_error,\\n geo_loc_city_error,\\n organism_error,\\n '-', # isolate_error placeholder\\n p_o_sampling_error,\\n anat_material_error,\\n anat_part_error,\\n body_product_error,\\n envi_material_error,\\n envi_site_error,\\n col_device_error,\\n col_method_error,\\n col_protocol_error,\\n spec_process_error,\\n lab_host_error,\\n passage_num_error,\\n passage_method_error,\\n biom_extract_error,\\n host_com_name_error,\\n host_sci_name_error,\\n host_health_state_error,\\n host_health_status_error,\\n host_disease_error,\\n host_age_error,\\n host_gender_error,\\n host_loc_country_error,\\n host_sub_id_error,\\n symp_onset_date_error,\\n signs_symptoms_error,\\n loc_exp_country_error,\\n trav_history_error,\\n exp_event_error,\\n library_id_error,\\n minion_barcode_error,\\n seq_instrument_error,\\n seq_prot_name_error,\\n seq_prot_source_error,\\n seq_kit_num_error,\\n amp_pcr_filename_error,\\n raw_seq_process_error,\\n seq_depth_avg_error,\\n assemb_name_error,\\n assemb_method_error,\\n assemb_cov_breadth_error,\\n assemb_cov_depth_error,\\n r1_filename_error,\\n r2_filename_error,\\n r1_filepath_error,\\n r2_filepath_error,\\n fast5_filename_error,\\n fast5_filepath_error,\\n fasta_filename_error,\\n fasta_filepath_error,\\n num_bp_error,\\n cons_genome_len_error,\\n mean_contig_len_error,\\n n50_error,\\n ns_100kbp_error,\\n ref_genome_accession_error,\\n cons_seq_id_error,\\n cons_seq_method_error,\\n cons_seq_filename_error,\\n cons_seq_filepath_error,\\n annot_table_filename_error,\\n biof_protocol_error,\\n gene_1_error,\\n pcr_protocol_1_error,\\n pcr_ct_1_error,\\n gene_2_error,\\n pcr_protocol_2_error,\\n pcr_ct_2_error,\\n authors_error]\\n\\n # return row of data for data file and row of data validity for error grid.\\n return cols, grid\",\n \"def test_slepp_get_at_id(mocker):\\n mocker.patch('serial.Serial.open')\\n mocker.patch('serial.Serial.flushInput')\\n cgs = mocker.patch('pysds011.driver.SDS011.cmd_get_sleep')\\n runner = CliRunner()\\n result = runner.invoke(main, ['--id', 'ABCD', 'sleep'])\\n cgs.assert_called_once_with(id=b'\\\\xab\\\\xcd')\\n\\n assert result.exit_code == 0\",\n \"def test_simple(self):\\n # blocks [0 3583] [3840 4058]\\n test_file1 = os.path.join(INPUT_HYPM_PATH, 'unit_364-2013-206-2-0.mdd')\\n # blocks [0 1279] [1536 1791] [2048 2303] [2560 2815] [3072 4059]\\n test_file2 = os.path.join(INPUT_HYPM_PATH, 'unit_364-2013-206-3-0.mdd')\\n\\n # parse the two test files into the node and instrument group files\\n mdd.procall([test_file1, test_file2])\\n\\n data_orig = self.read_full_file('node58p1.dat')\\n\\n # read the data from all generated files into one data string\\n data_out = self.read_full_file('node58p1_0.status_1236801.dat')\\n # confirm this file only has the allowed instrument IDs\\n self.check_sio_type(data_out, ['PS', 'CS'])\\n\\n data_out_wa = self.read_full_file('node58p1_0.wa_wfp_1236820.dat')\\n # confirm this file only has the allowed instrument IDs\\n self.check_sio_type(data_out_wa, ['WA'])\\n data_out += data_out_wa\\n\\n data_out_wc = self.read_full_file('node58p1_0.wc_wfp_1236820.dat')\\n # confirm this file only has the allowed instrument IDs\\n self.check_sio_type(data_out_wc, ['WC'])\\n data_out += data_out_wc\\n\\n data_out_we = self.read_full_file('node58p1_0.we_wfp_1236820.dat')\\n # confirm this file only has the allowed instrument IDs\\n self.check_sio_type(data_out_wc, ['WE'])\\n data_out += data_out_we\\n\\n # confirm that all data blocks from the node data file made it\\n # into the instrument group files\\n if not TestSioUnpack.compare_sio_matches(data_orig, data_out):\\n self.fail(\\\"Failed sio block compare\\\")\",\n \"def test_spin_loop_wildcard(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N*'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_seqgen(fprime_test_api):\\n sequence = Path(__file__).parent / \\\"test_seq.seq\\\"\\n assert (\\n subprocess.run(\\n [\\n \\\"fprime-seqgen\\\",\\n \\\"-d\\\",\\n str(fprime_test_api.pipeline.dictionary_path),\\n str(sequence),\\n \\\"/tmp/ref_test_int.bin\\\",\\n ]\\n ).returncode\\n == 0\\n ), \\\"Failed to run fprime-seqgen\\\"\\n fprime_test_api.send_and_assert_command(\\n \\\"cmdSeq.CS_RUN\\\", args=[\\\"/tmp/ref_test_int.bin\\\", \\\"BLOCK\\\"], max_delay=5\\n )\",\n \"def test_get_sample_ids(self):\\n obs = self.tester._get_sample_ids(self.conn_handler)\\n self.assertEqual(obs, self.exp_sample_ids)\",\n \"def test_get_sample_ids(self):\\n obs = self.tester._get_sample_ids(self.conn_handler)\\n self.assertEqual(obs, self.exp_sample_ids)\",\n \"def test_start_ids_10(self):\\n\\n\\t\\texpected_num_layers = 11\\n\\t\\texpected_ids = np.arange(10,21)\\n\\t\\t# test describe\\n\\t\\tdetails = self.watcher.describe(start_ids=10)\\n\\t\\tprint(\\\"start id = 10\\\", details)\\n\\t\\tactual_ids = details.layer_id.to_numpy().tolist()\\n\\t\\tself.assertTrue(np.array_equal(actual_ids, expected_ids))\\n\\t\\tself.assertEqual(len(expected_ids), expected_num_layers)\\n\\t\\t\\t\\t\\n\\t\\treturn\",\n \"def test_0():\\n sync.gen_multi_fake_data()#default is only one randomly selected data set\\n sync.main(testing=True)\",\n \"def iv_gen():\\r\\n rndiv = os.urandom(16)\\r\\n return rndiv\",\n \"def test_get_sample_ids(self):\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\\\\n parse_metadata_state_descriptions('Study:Twin')), [])\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\\\\n parse_metadata_state_descriptions('Study:Dog')), ['a','b'])\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\\\\n parse_metadata_state_descriptions('Study:*,!Dog')), ['c','d','e'])\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\\\\n parse_metadata_state_descriptions('Study:*,!Dog;BodySite:Stool')), ['e'])\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\\\\n parse_metadata_state_descriptions('BodySite:Stool')), ['a','b','e'])\",\n \"def test_periodic_boundary_two_ring_rod_different_nelems():\\n\\n ring_rod_1 = MockRingRod(5)\\n ring_rod_2 = MockRingRod(3)\\n block_structure = MemoryBlockCosseratRod([ring_rod_1, ring_rod_2], [0, 1])\\n\\n correct_periodic_boundary_node_idx = np.array(\\n [[0, 6, 7, 9, 13, 14], [5, 1, 2, 12, 10, 11]], dtype=np.int64\\n )\\n correct_periodic_boundary_elem_idx = np.array(\\n [[0, 6, 9, 13], [5, 1, 12, 10]], dtype=np.int64\\n )\\n correct_periodic_boundary_voronoi_idx = np.array([[0, 9], [5, 12]], dtype=np.int64)\\n\\n assert_allclose(\\n correct_periodic_boundary_node_idx,\\n block_structure.periodic_boundary_nodes_idx,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_periodic_boundary_elem_idx,\\n block_structure.periodic_boundary_elems_idx,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_periodic_boundary_voronoi_idx,\\n block_structure.periodic_boundary_voronoi_idx,\\n atol=Tolerance.atol(),\\n )\\n\\n correct_start_node_idx = np.array([1, 10], dtype=np.int64)\\n correct_end_node_idx = np.array([6, 13], dtype=np.int64)\\n\\n correct_start_elem_idx = np.array([1, 10], dtype=np.int64)\\n correct_end_elem_idx = np.array([6, 13], dtype=np.int64)\\n\\n correct_start_voronoi_idx = np.array([1, 10], dtype=np.int64)\\n correct_end_voronoi_idx = np.array([6, 13], dtype=np.int64)\\n\\n assert_allclose(\\n correct_start_node_idx,\\n block_structure.start_idx_in_rod_nodes,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_node_idx,\\n block_structure.end_idx_in_rod_nodes,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_start_elem_idx,\\n block_structure.start_idx_in_rod_elems,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_elem_idx,\\n block_structure.end_idx_in_rod_elems,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_start_voronoi_idx,\\n block_structure.start_idx_in_rod_voronoi,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_voronoi_idx,\\n block_structure.end_idx_in_rod_voronoi,\\n atol=Tolerance.atol(),\\n )\",\n \"def __data_generation(self, list_IDs_temp):\\n\\n # Initialization\\n X = np.empty((self.batch_size, self.grid_dim, self.grid_dim, self.grid_dim, self.n_channels))\\n y = np.empty(self.batch_size, dtype=int)\\n\\n # Generate data\\n for i, ID in enumerate(list_IDs_temp):\\n # Store sample\\n X[i], y[i] = pro_lig_reader_sample(ID[0], ID[1], self.grid_size, self.n_channels, self.grid_resolution)\\n return X, keras.utils.to_categorical(y, num_classes=self.n_classes)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.8086905","0.7927075","0.7615566","0.7598885","0.75597614","0.6486901","0.6055875","0.58638847","0.57211256","0.5610557","0.55860114","0.558456","0.5549974","0.54673797","0.53942615","0.53439724","0.5339024","0.5296352","0.52316296","0.5216718","0.52012265","0.5191702","0.51896805","0.5180857","0.51776445","0.51724064","0.5158274","0.5155504","0.5151724","0.5144521","0.5142519","0.5139197","0.5135191","0.5089514","0.5088537","0.5085317","0.5049573","0.501817","0.5008705","0.4981375","0.4978904","0.496752","0.49655202","0.49549595","0.49543998","0.49468213","0.4932665","0.49321795","0.49260426","0.49248397","0.4922831","0.49207997","0.49206263","0.49203557","0.49199516","0.491508","0.49135733","0.49128","0.49125558","0.49125558","0.49090543","0.48962286","0.48796764","0.4876504","0.48759884","0.48688465","0.4866883","0.48617187","0.48602632","0.48570347","0.4856979","0.485522","0.48525628","0.48399818","0.48391503","0.48319033","0.482951","0.48110572","0.48059264","0.48036668","0.47996667","0.47991893","0.47990233","0.47966465","0.4791041","0.47910377","0.47848883","0.47830105","0.47811976","0.47784182","0.4777812","0.47776103","0.47764564","0.47764564","0.47669533","0.4765932","0.47642514","0.47624806","0.47600615","0.47576573"],"string":"[\n \"0.8086905\",\n \"0.7927075\",\n \"0.7615566\",\n \"0.7598885\",\n \"0.75597614\",\n \"0.6486901\",\n \"0.6055875\",\n \"0.58638847\",\n \"0.57211256\",\n \"0.5610557\",\n \"0.55860114\",\n \"0.558456\",\n \"0.5549974\",\n \"0.54673797\",\n \"0.53942615\",\n \"0.53439724\",\n \"0.5339024\",\n \"0.5296352\",\n \"0.52316296\",\n \"0.5216718\",\n \"0.52012265\",\n \"0.5191702\",\n \"0.51896805\",\n \"0.5180857\",\n \"0.51776445\",\n \"0.51724064\",\n \"0.5158274\",\n \"0.5155504\",\n \"0.5151724\",\n \"0.5144521\",\n \"0.5142519\",\n \"0.5139197\",\n \"0.5135191\",\n \"0.5089514\",\n \"0.5088537\",\n \"0.5085317\",\n \"0.5049573\",\n \"0.501817\",\n \"0.5008705\",\n \"0.4981375\",\n \"0.4978904\",\n \"0.496752\",\n \"0.49655202\",\n \"0.49549595\",\n \"0.49543998\",\n \"0.49468213\",\n \"0.4932665\",\n \"0.49321795\",\n \"0.49260426\",\n \"0.49248397\",\n \"0.4922831\",\n \"0.49207997\",\n \"0.49206263\",\n \"0.49203557\",\n \"0.49199516\",\n \"0.491508\",\n \"0.49135733\",\n \"0.49128\",\n \"0.49125558\",\n \"0.49125558\",\n \"0.49090543\",\n \"0.48962286\",\n \"0.48796764\",\n \"0.4876504\",\n \"0.48759884\",\n \"0.48688465\",\n \"0.4866883\",\n \"0.48617187\",\n \"0.48602632\",\n \"0.48570347\",\n \"0.4856979\",\n \"0.485522\",\n \"0.48525628\",\n \"0.48399818\",\n \"0.48391503\",\n \"0.48319033\",\n \"0.482951\",\n \"0.48110572\",\n \"0.48059264\",\n \"0.48036668\",\n \"0.47996667\",\n \"0.47991893\",\n \"0.47990233\",\n \"0.47966465\",\n \"0.4791041\",\n \"0.47910377\",\n \"0.47848883\",\n \"0.47830105\",\n \"0.47811976\",\n \"0.47784182\",\n \"0.4777812\",\n \"0.47776103\",\n \"0.47764564\",\n \"0.47764564\",\n \"0.47669533\",\n \"0.4765932\",\n \"0.47642514\",\n \"0.47624806\",\n \"0.47600615\",\n \"0.47576573\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8013001"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":81485,"cells":{"query":{"kind":"string","value":"Third test of the spin ID generation function. The function tested is pipe_control.mol_res_spin.generate_spin_id_data_array()."},"document":{"kind":"string","value":"def test_generate_spin_id_data_array3(self):\n\n # The data.\n data = ['Ap4Aase', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=None, res_name_col=None, spin_num_col=2, spin_name_col=3)\n\n # Test the string.\n self.assertEqual(id, '#Ap4Aase@234')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_generate_spin_id_data_array6(self):\n\n # The data.\n data = ['1', 'GLY', None, None]\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')","def test_generate_spin_id_data_array1(self):\n\n # The data.\n data = ['1', 'GLY']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')","def test_generate_spin_id_data_array2(self):\n\n # The data.\n data = ['1', 'GLY', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2, spin_num_col=3, spin_name_col=4)\n\n # Test the string.\n self.assertEqual(id, ':1@234')","def test_generate_spin_id_data_array5(self):\n\n # The data.\n data = ['Ap4Aase', '1', 'GLY', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5)\n\n # Test the string.\n self.assertEqual(id, '#Ap4Aase:1@234')","def test_generate_spin_id_data_array4(self):\n\n # The data.\n data = ['Ap4Aase', '1', 'GLY']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3)\n\n # Test the string.\n self.assertEqual(id, '#Ap4Aase:1')","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_id_array(self):\n arr = vtk.vtkIdTypeArray()\n arr.SetNumberOfTuples(10)\n for i in range(10):\n arr.SetValue(i, i)\n\n np = array_handler.vtk2array(arr)\n self.assertEqual(numpy.all(np == range(10)), True)","def test_create_template(self):\n m_size = 10\n data = ecn.IDData(m_size)\n self.assertEqual(np.shape(data.ID_MATRIX), (m_size, m_size))\n self.assertEqual(sum(sum(data.ID_MATRIX)), m_size)\n self.assertTrue((sum(data.ID_MATRIX) == np.ones(m_size)).all())\n print('Finished testing template\\n')","def test_random_id(self):\r\n ids = \\\r\n \"R27DLI_4812 R27DLI_600 R27DLI_727 U1PLI_403 U1PLI_8969\".split(\r\n )\r\n assert random_id(ids, {}) in ids\r\n # just test we got something from the list, don't add stochastic test\r","def test_spin_loop(self):\n\n # Spin data.\n select = [1, 0]\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, 'N5')\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 2)","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_arr2vtkIdList(self):\n a = [1, 2, 3, 4, 5]\n p = array_handler.array2vtkIdList(a)\n for i, j in enumerate(a): \n self.assertEqual(p.GetId(i), j)\n p = vtk.vtkIdList()\n ident = id(p)\n p = array_handler.array2vtkIdList(numpy.array(a), p)\n for i, j in enumerate(a): \n self.assertEqual(p.GetId(i), j)\n self.assertEqual(id(p), ident)\n \n self.assertRaises(AssertionError, array_handler.array2vtkIdList,\n [[1,2,3]])","def createArrayFunc(self):\r\n minVal = int(self.spinBoxMin_2.value())\r\n maxVal = int(self.spinBoxMax_2.value())\r\n arrayLength = int(self.spinBoxLength_2.value())\r\n different = maxVal - minVal\r\n if self.checkBoxNoRepeate_2.isChecked():\r\n if different > arrayLength:\r\n def unique_rand(initial, limit, total):\r\n data = []\r\n i = 0\r\n while i < total:\r\n number = numpy.random.randint(initial, limit)\r\n if number not in data:\r\n data.append(number)\r\n i += 1\r\n return data\r\n\r\n self.UnsortedArray_2 = unique_rand(minVal, maxVal, arrayLength)\r\n else:\r\n err = \"Array length must be greater than difference between limits\"\r\n self.labelUnsortedArray_2.setText(str(err))\r\n\r\n else:\r\n self.UnsortedArray_2 = numpy.random.randint(minVal, maxVal, arrayLength)\r\n self.labelUnsortedArray_2.setText(str(self.UnsortedArray_2))\r\n self.SortedArray_2 = Insertion.sorting(self.UnsortedArray_2)\r\n self.labelSortedArray_2.setText(str(self.SortedArray_2))\r\n binaryMax = int(self.spinBoxMax_2.value())\r\n binaryMin = int(self.spinBoxMin_2.value())\r\n self.spinBoxBinary.setMaximum(binaryMax)\r\n self.spinBoxBinary.setMinimum(binaryMin)\r\n self.spinBoxIthSmallest.setMaximum(arrayLength + 1)","def test_get_ids(civic, main_data, updated_data):\n assert len(civic._get_ids(main_data['assertions'])) == 0\n assert len(civic._get_ids(main_data['variants'])) == 1\n assert len(civic._get_ids(main_data['genes'])) == 2\n assert len(civic._get_ids(main_data['evidence'])) == 1\n\n assert len(civic._get_ids(updated_data['assertions'])) == 1\n assert len(civic._get_ids(updated_data['variants'])) == 1\n assert len(civic._get_ids(updated_data['genes'])) == 1\n assert len(civic._get_ids(updated_data['evidence'])) == 1","def test_id_rot():\n assert_array_almost_equal(pr.R_id, pr.matrix_from_axis_angle(pr.a_id))\n assert_array_almost_equal(pr.R_id, pr.matrix_from_quaternion(pr.q_id))\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_xyz(pr.e_xyz_id))\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_zyx(pr.e_zyx_id))","def _apply_array_spin123(self,\n h1e: 'Nparray',\n h2e: 'Nparray',\n h3e: 'Nparray',\n dvec: Optional[Tuple['Nparray', 'Nparray']] = None,\n evec: Optional[Tuple['Nparray', 'Nparray', 'Nparray', 'Nparray']] \\\n = None) -> 'Nparray':\n norb = self.norb()\n assert h3e.shape == (norb * 2,) * 6\n assert not (dvec is None) ^ (evec is None)\n\n from1234 = (dvec is not None) and (evec is not None)\n\n nh1e = numpy.copy(h1e)\n nh2e = numpy.copy(h2e)\n\n for i in range(norb * 2):\n for j in range(norb * 2):\n for k in range(norb * 2):\n nh2e[j, k, :, :] += (-h3e[k, j, i, i, :, :] -\n h3e[j, i, k, i, :, :] -\n h3e[j, k, i, :, i, :])\n\n nh1e[:, :] += h3e[:, i, j, i, j, :]\n\n out = self._apply_array_spin12_halffilling(nh1e, nh2e)\n\n n = norb # This is just shorter\n if not from1234:\n symfac = 2.0\n axes = ((1, 3), (0, 1))\n (odveca, odvecb) = self.calculate_dvec_spin()\n dveca = numpy.zeros_like(odveca)\n dvecb = numpy.zeros_like(odvecb)\n\n for i in range(norb):\n for j in range(norb):\n evecaa, _ = self._calculate_dvec_spin_with_coeff(\n odveca[i, j, :, :])\n evecab, evecbb = self._calculate_dvec_spin_with_coeff(\n odvecb[i, j, :, :])\n\n dveca += numpy.tensordot(h3e[:n, :n, i, :n, :n, j],\n evecaa,\n axes=axes)\n dveca += numpy.tensordot(h3e[:n, :n, n + i, :n, :n, n + j],\n evecab,\n axes=axes) * symfac\n dveca += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\n evecbb,\n axes=axes)\n\n dvecb += numpy.tensordot(h3e[n:, :n, i, n:, :n, j],\n evecaa,\n axes=axes)\n dvecb += numpy.tensordot(h3e[n:, :n, n + i, n:, :n, n + j],\n evecab,\n axes=axes) * symfac\n dvecb += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\n evecbb,\n axes=axes)\n else:\n symfac = 1.0\n axes = ((1, 4, 2, 5), (0, 1, 2, 3)) # type: ignore\n dveca, dvecb = dvec # type: ignore\n evecaa, evecab, evecba, evecbb = evec # type: ignore\n\n dveca = numpy.tensordot(h3e[:n, :n, :n, :n, :n, :n],\n evecaa, axes=axes) \\\n + numpy.tensordot(h3e[:n, :n, n:, :n, :n, n:],\n evecab, axes=axes) * symfac \\\n + numpy.tensordot(h3e[:n, n:, n:, :n, n:, n:],\n evecbb, axes=axes) + \\\n + numpy.tensordot(h3e[:n, n:, :n, :n, n:, :n],\n evecba, axes=axes)\n\n dvecb = numpy.tensordot(h3e[n:, :n, :n, n:, :n, :n],\n evecaa, axes=axes) \\\n + numpy.tensordot(h3e[n:, :n, n:, n:, :n, n:],\n evecab, axes=axes) * symfac \\\n + numpy.tensordot(h3e[n:, n:, n:, n:, n:, n:],\n evecbb, axes=axes) + \\\n + numpy.tensordot(h3e[n:, n:, :n, n:, n:, :n],\n evecba, axes=axes)\n\n out -= self._calculate_coeff_spin_with_dvec((dveca, dvecb))\n return out","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_scan_id_list(self):\n scan = '15,17'\n ref_idx = [0,3]\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_spin_loop_no_selection(self):\n\n # Spin data.\n select = [0, 1, 0, 0, 1, 1, 0, 1]\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 8)","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def generate_T(number_obeservations):\n T = np.random.randint(0, 2, (number_obeservations,1))\n return T","def test_weyl_specialize_id(self):\n a, b, c = 0.0, 0.0, 0.0\n for da, db, dc in DELTAS:\n for k1l, k1r, k2l, k2r in K1K2SB:\n k1 = np.kron(k1l.data, k1r.data)\n k2 = np.kron(k2l.data, k2r.data)\n self.check_two_qubit_weyl_specialization(\n k1 @ Ud(a + da, b + db, c + dc) @ k2,\n 0.999,\n TwoQubitWeylIdEquiv,\n {\"rz\": 4, \"ry\": 2},\n )","def test_pol_id_list(self):\n pol = '0,1'\n ref_idx = []\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_spin_type(get_pdos_generator_inputs):\n with pytest.raises(NotImplementedError):\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=spin_type)\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=SpinType.COLLINEAR)\n for namespace in [builder.scf, builder.nscf]:\n parameters = namespace['pw']['parameters'].get_dict()\n assert parameters['SYSTEM']['nspin'] == 2\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}","def generate_new_ids(ids: np.array, n_required: int) -> np.array:\n\n current_max_id = ids.max()\n new_ids = np.arange(n_required) + current_max_id + 1\n\n return new_ids","def test_uuid():\n for _ in range(1000):\n uuid = uuid_generator()\n assert len(uuid) == 36\n assert uuid.count('-') == 4","def test_random_integers(self):\r\n # Check over two calls to see if the random state is correctly updated.\r\n random = RandomStreams(utt.fetch_seed())\r\n fn = function([], random.random_integers((20, 20), -5, 5))\r\n fn_val0 = fn()\r\n fn_val1 = fn()\r\n\r\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\r\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\r\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\r\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\r\n\r\n assert numpy.all(fn_val0 == numpy_val0)\r\n assert numpy.all(fn_val1 == numpy_val1)","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def test_split_id_otp(self):\n public_id, otp, = pyhsm.yubikey.split_id_otp(\"ft\" * 16)\n self.assertEqual(public_id, '')\n self.assertEqual(otp, \"ft\" * 16)\n\n public_id, otp, = pyhsm.yubikey.split_id_otp(\"cc\" + \"ft\" * 16)\n self.assertEqual(public_id, 'cc')\n self.assertEqual(otp, \"ft\" * 16)","def test_generateuuids(self):\n ret1 = {\"message\": \"No Random.org api key or api version found.\", \"res\": False}\n self.assertDictEqual(random_org.generateUUIDs(), ret1)\n\n ret2 = {\"message\": \"Required argument, number is missing.\", \"res\": False}\n self.assertDictEqual(\n random_org.generateUUIDs(api_key=\"peW\", api_version=\"1\"), ret2\n )\n\n ret3 = {\"message\": \"Number of UUIDs must be between 1 and 1000\", \"res\": False}\n self.assertDictEqual(\n random_org.generateUUIDs(api_key=\"peW\", api_version=\"1\", number=\"5\"), ret3\n )\n\n ret3 = {\"message\": \"Parameter 'apiKey' is malformed\", \"res\": False}\n self.assertDictEqual(\n random_org.generateUUIDs(api_key=\"peW\", api_version=\"1\", number=5), ret3\n )","def myID() -> np.int:\r\n return 304976335","def myID() -> np.int:\r\n return 304976335","def generate_mixture_indicator(number_obeservations):\n mixture_indicator = np.random.randint(0, 2, (number_obeservations,1))\n return mixture_indicator","def test_random_integers(self):\r\n # Check over two calls to see if the random state is correctly updated.\r\n m = Module()\r\n m.random = RandomStreams(utt.fetch_seed())\r\n m.fn = Method([], m.random.random_integers((20,20), -5, 5))\r\n\r\n made = m.make()\r\n made.random.initialize()\r\n fn_val0 = made.fn()\r\n fn_val1 = made.fn()\r\n\r\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\r\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\r\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\r\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\r\n\r\n assert numpy.all(fn_val0 == numpy_val0)\r\n assert numpy.all(fn_val1 == numpy_val1)","def test_create_tornado_id(self):\n\n this_id_string = tornado_io.create_tornado_id(\n start_time_unix_sec=TORNADO_START_TIME_UNIX_SEC,\n start_latitude_deg=TORNADO_START_LATITUDE_DEG,\n start_longitude_deg=TORNADO_START_LONGITUDE_DEG)\n\n self.assertTrue(this_id_string == TORNADO_ID_STRING)","def generate_fake_data(t0, num_array, period=5820, data_range=[0.0, 24.0],\n cyclic=True):\n\n if cyclic:\n uts_root = np.mod(t0, period)\n data = (np.mod(uts_root + num_array, period)\n * (np.diff(data_range)[0] / np.float64(period))) + data_range[0]\n else:\n data = ((t0 + num_array) / period).astype(int)\n\n return data","def test_generate(self):\n cant_interations = int(random()*100)\n for i in range(cant_interations):\n number = self.sudoku.generate() # Generate number\n self.assertGreaterEqual(number, 0) # number >= 0\n self.assertLessEqual(number, 8) # number <= 8","def _get_rand_array(self):\n pass","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def get_test_split(self, fraction=0.1):\n rng = np.random.default_rng(42)\n test_size = int(round(len(self.all_asset_ids) * fraction))\n test_ids = rng.choice(self.all_asset_ids, size=test_size, replace=False)\n train_ids = [i for i in self.all_asset_ids if i not in test_ids]\n return train_ids, test_ids","def test_sampleId_pairs(self):\r\n # expected values\r\n dose_vps = \\\r\n [('1xDose', '2xDose'), ('1xDose', 'Control'),\r\n ('2xDose', 'Control')]\r\n ttd_vps = \\\r\n [('31', '21'), ('31', '55'), ('31', '67'), ('21', '55'),\r\n ('21', '67'), ('55', '67')]\r\n dose_sids = \\\r\n [(['Sam1', 'Sam2', 'Sam6'], ['Sam3', 'Sam4']),\r\n (['Sam1', 'Sam2', 'Sam6'], ['Sam5']),\r\n (['Sam3', 'Sam4'], ['Sam5'])]\r\n ttd_sids = \\\r\n [(['Sam1'], ['Sam3']),\r\n (['Sam1'], ['Sam4', 'Sam6']),\r\n (['Sam1'], ['Sam2', 'Sam5']),\r\n (['Sam3'], ['Sam4', 'Sam6']),\r\n (['Sam3'], ['Sam2', 'Sam5']),\r\n (['Sam4', 'Sam6'], ['Sam2', 'Sam5'])]\r\n\r\n # observed values\r\n obs_dose_sids, obs_dose_vps = sampleId_pairs(self.mapping_data,\r\n self.rarefaction_data, 'Dose')\r\n obs_ttd_sids, obs_ttd_vps = sampleId_pairs(self.mapping_data,\r\n self.rarefaction_data, 'TTD')\r\n\r\n # sort -- order is unimportant and depends on way presented in mf\r\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\r\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())\r\n self.assertEqual(ttd_vps.sort(), obs_ttd_vps.sort())\r\n self.assertEqual(ttd_sids.sort(), obs_ttd_sids.sort())\r\n\r\n # check errors when no samples had this category\r\n self.assertRaises(ValueError, sampleId_pairs, self.mapping_data,\r\n self.rarefaction_data, 'DNE')\r\n\r\n # check no error if map file has more sampleids than rarefaction data\r\n superset_mf = \\\r\n ['#SampleID\\tDose\\tLinkerPrimerSequence\\tWeight\\tTTD\\tDescription',\r\n '#Comment Line',\r\n 'Sam1\\t1xDose\\tATCG\\tHigh\\t31\\ts1_desc',\r\n 'Sam2\\t1xDose\\tACCG\\tLow\\t67\\ts2_desc',\r\n 'Sam3\\t2xDose\\tACGT\\tMed\\t21\\ts3_desc',\r\n 'Sam4\\t2xDose\\tAACG\\tLow\\t55\\ts4_desc',\r\n 'Sam5\\tControl\\tCGTC\\tLow\\t67\\ts5_desc',\r\n 'Sam6\\t1xDose\\tACCT\\tLow\\t55\\ts6_desc',\r\n 'Sam7\\t4xDose\\tACCT\\tLow\\t55\\ts7_desc',\r\n 'Sam8\\t3xDose\\tACCT\\tLow\\t55\\ts8_desc',\r\n 'Sam9\\t1xDose\\tACCT\\tLow\\t55\\ts9_desc']\r\n # (mf, comments)\r\n superset_mf = parse_mapping_file_to_dict(superset_mf)[0]\r\n obs_dose_sids, obs_dose_vps = sampleId_pairs(superset_mf,\r\n self.rarefaction_data, 'Dose')\r\n\r\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\r\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def make_row(invalid_data=[]):\n\n ### Database Identifiers ###\n \n # phac_sample_id, valid/invalid error-grid information.\n phac_sample_id, phac_sample_id_error = lib.random_phac_id(invalid_data)\n # umbrella_bioproject_accession, valid/invalid error-grid information.\n ub_accession, ub_accession_error = lib.umbrella_bioproject_accession(invalid_data)\n # bioproject_accession, valid/invalid error-grid information.\n bp_accession, bp_accession_error = lib.random_bioproject_accession(invalid_data)\n # biosample_accession, valid/invalid error-grid information.\n bs_accession, bs_accession_error = lib.random_biosample_accession(invalid_data)\n # sra_accession, valid/invalid error-grid information.\n sra_accession, sra_accession_error = lib.random_sra_accession(invalid_data)\n # genbank_accession, valid/invalid error-grid information.\n gb_accession, gb_accession_error = lib.random_genbank_accession(invalid_data)\n # gisaid_accession, valid/invalid error-grid information.\n gisaid_accession, gisaid_accession_error = lib.random_gisaid_accession(invalid_data)\n \n ### Sample Collection and Processing ###\n \n # sample_collected_by, valid/invalid error-grid information.\n samp_col_by, samp_col_by_error = lib.random_agency(invalid_data)\n # sample_collector_contact_email, valid/invalid error-grid information.\n samp_col_email, samp_col_email_error = lib.random_email(invalid_data)\n # sample_collector_contact_address, valid/invalid error-grid information.\n samp_col_address, samp_col_address_error = lib.random_address(invalid_data)\n # sequence_submitter_contact_email, valid/invalid error-grid information.\n seq_sub_email, seq_sub_email_error = lib.random_email(invalid_data)\n # sequence_submitter_contact_address, valid/invalid error-grid information.\n seq_sub_address, seq_sub_address_error = lib.random_address(invalid_data)\n # sample_collection_date, valid/invalid error-grid information.\n samp_col_date, samp_col_date_error = lib.random_date(invalid_data)\n # sample_received_date, valid/invalid error-grid information.\n samp_rec_date, samp_rec_date_error = lib.random_date(invalid_data)\n # geo_loc_name_country, valid/invalid error-grid information.\n geo_loc_country, geo_loc_country_error = lib.random_country(invalid_data)\n # geo_loc_name_province_territory, valid/invalid error-grid information.\n geo_loc_prov_ter, geo_loc_prov_ter_error = lib.random_province_territory(invalid_data)\n # geo_loc_name_city, valid/invalid error-grid information.\n geo_loc_city, geo_loc_city_error = lib.random_city(invalid_data)\n # organism, valid/invalid error-grid information.\n organism, organism_error = lib.random_organism(invalid_data)\n # purpose_of_sampling, valid/invalid error-grid information.\n p_o_sampling, p_o_sampling_error = lib.random_purpose_of_sampling(invalid_data)\n # anatomical_material, valid/invalid error-grid information.\n anat_material, anat_material_error = lib.random_anatomical_material(invalid_data)\n # anatomical_part, valid/invalid error-grid information.\n anat_part, anat_part_error = lib.random_anatomical_part(invalid_data)\n # body_product, valid/invalid error-grid information.\n body_product, body_product_error = lib.random_body_product(invalid_data)\n # environmental_material, valid/invalid error-grid information.\n envi_material, envi_material_error = lib.random_environmental_material(invalid_data)\n # environmental_site, valid/invalid error-grid information.\n envi_site, envi_site_error = lib.random_environmental_site(invalid_data)\n # collection_device, valid/invalid error-grid information.\n col_device, col_device_error = lib.random_collection_device(invalid_data)\n # collection_method, valid/invalid error-grid information.\n col_method, col_method_error = lib.random_collection_method(invalid_data)\n # collection_protocol, valid/invalid error-grid information.\n col_protocol, col_protocol_error = lib.fake_protocol(invalid_data)\n # specimen_processing, valid/invalid error-grid information.\n spec_process, spec_process_error = lib.random_specimen_processing(invalid_data)\n # lab_host, valid/invalid error-grid information.\n lab_host, lab_host_error = lib.random_lab_host(invalid_data)\n # passage_number , valid/invalid error-grid information.\n passage_num, passage_num_error = lib.random_passage_number(invalid_data)\n # passage_method, valid/invalid error-grid information.\n passage_method, passage_method_error = lib.passage_method_text(invalid_data)\n # biomaterial_extracted, valid/invalid error-grid information.\n biom_extract, biom_extract_error = lib.random_biomaterial_extracted(invalid_data)\n \n ### Host Information ###\n \n # host_common_name, valid/invalid error-grid information.\n host_com_name, host_com_name_error = lib.random_host_common_name(invalid_data)\n # host_scientific_name, valid/invalid error-grid information.\n host_sci_name, host_sci_name_error = lib.random_host_scientific_name(invalid_data)\n # host_health_state, valid/invalid error-grid information.\n host_health_state, host_health_state_error = lib.random_host_health_state(invalid_data)\n # host_health_status_details, valid/invalid error-grid information.\n host_health_status, host_health_status_error = lib.random_host_health_status_details(invalid_data)\n # host_disease, valid/invalid error-grid information.\n host_disease, host_disease_error = lib.random_host_disease(invalid_data)\n # host_age, valid/invalid error-grid information.\n host_age, host_age_error = lib.random_host_age(invalid_data)\n # host_gender, valid/invalid error-grid information.\n host_gender, host_gender_error = lib.random_host_gender(invalid_data)\n # host_origin_geo_loc_name_country, valid/invalid error-grid information.\n host_loc_country, host_loc_country_error = lib.random_country(invalid_data)\n # host_subject_id, valid/invalid error-grid information.\n host_sub_id, host_sub_id_error = lib.random_host_subject_id(invalid_data)\n # symptom_onset_date, valid/invalid error-grid information.\n symp_onset_date, symp_onset_date_error = lib.random_date(invalid_data)\n # signs_and_symptoms, valid/invalid error-grid information.\n signs_symptoms, signs_symptoms_error = lib.random_signs_symptoms(invalid_data)\n \n ### Host Exposure Information ###\n \n # location_of_exposure_geo_loc_name_country, valid/invalid error-grid information.\n loc_exp_country, loc_exp_country_error = lib.random_country(invalid_data)\n # travel_history, valid/invalid error-grid information. \n trav_history, trav_history_error = lib.random_travel_history(invalid_data)\n # exposure_event, valid/invalid error-grid information.\n exp_event, exp_event_error = lib.random_exposure_event(invalid_data)\n \n ### Sequencing ###\n \n # minion_barcode, valid/invalid error-grid information.\n minion_barcode, minion_barcode_error = lib.random_minIon_barcode(invalid_data)\n # sequencing_instrument, valid/invalid error-grid information.\n seq_instrument, seq_instrument_error = lib.random_seq_instrument(invalid_data)\n # sequencing_protocol_name, valid/invalid error-grid information.\n seq_prot_name, seq_prot_name_error = lib.fake_protocol(invalid_data)\n # sequencing_protocol_source, valid/invalid error-grid information.\n seq_prot_source, seq_prot_source_error = lib.random_seq_protocol_source(invalid_data)\n # sequencing_kit_number, valid/invalid error-grid information.\n seq_kit_num, seq_kit_num_error = lib.random_seq_kit_num(invalid_data)\n # amplicon_pcr_primers_filename, valid/invalid error-grid information.\n amp_pcr_filename, amp_pcr_filename_error = lib.random_txt_filename(invalid_data)\n \n ### Bioinformatics and QC metrics ###\n \n # raw_sequence_data_processing, valid/invalid error-grid information.\n raw_seq_process, raw_seq_process_error = lib.random_seq_process(invalid_data)\n # sequencing_depth_average, valid/invalid error-grid information.\n seq_depth_avg, seq_depth_avg_error = lib.random_seq_depth(invalid_data)\n # assembly_method, valid/invalid error-grid information.\n assemb_method, assemb_method_error = lib.random_assembly_software(invalid_data)\n # assembly_coverage_breadth, valid/invalid error-grid information.\n assemb_cov_breadth, assemb_cov_breadth_error = lib.random_assembly_coverage_breadth(invalid_data)\n # assembly_coverage_depth, valid/invalid error-grid information.\n assemb_cov_depth, assemb_cov_depth_error = lib.random_seq_depth(invalid_data)\n # r1_fastq_filename, valid/invalid error-grid information.\n r1_filename, r1_filename_error = lib.random_fastq_filename(invalid_data)\n # r2_fastq_filename, valid/invalid error-grid information.\n r2_filename, r2_filename_error = lib.random_fastq_filename(invalid_data)\n # r1_fastq_filepath, valid/invalid error-grid information.\n r1_filepath, r1_filepath_error = lib.random_filepath(r1_filename, invalid_data)\n # r2_fastq_filepath, valid/invalid error-grid information.\n r2_filepath, r2_filepath_error = lib.random_filepath(r2_filename, invalid_data)\n # fast5_filename, valid/invalid error-grid information.\n fast5_filename, fast5_filename_error = lib.random_fast5_filename(invalid_data)\n # fast5_filepath, valid/invalid error-grid information.\n fast5_filepath, fast5_filepath_error = lib.random_filepath(fast5_filename, invalid_data)\n # fasta_filename, valid/invalid error-grid information.\n fasta_filename, fasta_filename_error = lib.random_fasta_filename(invalid_data)\n # fasta_filepath, valid/invalid error-grid information.\n fasta_filepath, fasta_filepath_error = lib.random_filepath(fasta_filename, invalid_data)\n # number_base_pairs, valid/invalid error-grid information.\n num_bp, num_bp_error = lib.random_bp_num(invalid_data)\n # consensus_genome_length, valid/invalid error-grid information.\n cons_genome_len, cons_genome_len_error = lib.random_genome_length(invalid_data)\n # mean_contig_length, valid/invalid error-grid information.\n mean_contig_len, mean_contig_len_error = lib.random_contig_length(invalid_data)\n # n50, valid/invalid error-grid information.\n n50, n50_error = lib.random_n50(invalid_data)\n # ns_per_100_kbp, valid/invalid error-grid information.\n ns_100kbp, ns_100kbp_error = lib.random_ns_100kbp(invalid_data)\n # reference_genome_accession, valid/invalid error-grid information.\n ref_genome_accession, ref_genome_accession_error = lib.random_ref_genome(invalid_data)\n # consensus_sequence_id, valid/invalid error-grid information.\n cons_seq_id, cons_seq_id_error = lib.random_consensus_seq_id(invalid_data)\n # consensus_sequence_method, valid/invalid error-grid information.\n cons_seq_method, cons_seq_method_error = lib.random_consensus_seq_method(invalid_data)\n # consensus_sequence_filename, valid/invalid error-grid information.\n cons_seq_filename, cons_seq_filename_error = lib.random_fasta_filename(invalid_data)\n # consensus_sequence_filepath, valid/invalid error-grid information.\n cons_seq_filepath, cons_seq_filepath_error = lib.random_filepath(cons_seq_filename, invalid_data)\n # annotation_feature_table_filename, valid/invalid error-grid information.\n annot_table_filename, annot_table_filename_error = lib.random_feature_table_filename(invalid_data)\n # bioinformatics_protocol, valid/invalid error-grid information.\n biof_protocol, biof_protocol_error = lib.bioinformatics_protocol(invalid_data)\n \n ### Pathogen Diagnostic Testing ###\n \n # gene_name_1, valid/invalid error-grid information.\n gene_1, gene_1_error = lib.random_gene(invalid_data)\n # diagnostic_pcr_protocol_1, valid/invalid error-grid information.\n pcr_protocol_1, pcr_protocol_1_error = lib.fake_protocol(invalid_data)\n # diagnostic_pcr_ct_value_1, valid/invalid error-grid information.\n pcr_ct_1, pcr_ct_1_error = lib.random_pcr_ct_val(invalid_data)\n # gene_name_2, valid/invalid error-grid information.\n gene_2, gene_2_error = lib.random_gene(invalid_data)\n # diagnostic_pcr_protocol_2, valid/invalid error-grid information.\n pcr_protocol_2, pcr_protocol_2_error = lib.fake_protocol(invalid_data)\n # diagnostic_pcr_ct_value_2, valid/invalid error-grid information.\n pcr_ct_2, pcr_ct_2_error = lib.random_pcr_ct_val(invalid_data)\n \n ### Contributor Acknowledgement ###\n \n # authors, valid/invalid error-grid information.\n authors, authors_error = lib.authors(invalid_data)\n \n ### Dependent IDs ###\n \n # specimen_collector_sample_id.\n spec_col_sample_id, spec_col_sample_id_error = lib.random_specimen_collector_sample_id(\n geo_loc_country, \n geo_loc_prov_ter,\n geo_loc_city,\n invalid_data)\n # irida_sample_name.\n irida_sample_id = spec_col_sample_id\n # sequence_submitted_by.\n seq_sub_by = samp_col_by\n # library_id, valid/invalid error-grid information.\n library_id, library_id_error = lib.random_library_id(spec_col_sample_id, invalid_data)\n # isolate.\n isolate = spec_col_sample_id\n # assembly_name, valid/invalid error-grid information.\n assemb_name, assemb_name_error = lib.random_assembly_name(spec_col_sample_id, invalid_data)\n\n # Row of generated data organised by column.\n cols = [spec_col_sample_id,\n phac_sample_id,\n irida_sample_id,\n ub_accession,\n bp_accession,\n bs_accession,\n sra_accession,\n gb_accession,\n gisaid_accession,\n samp_col_by,\n samp_col_email,\n samp_col_address,\n seq_sub_by,\n seq_sub_email,\n seq_sub_address,\n samp_col_date,\n samp_rec_date,\n geo_loc_country,\n geo_loc_prov_ter,\n geo_loc_city,\n organism,\n isolate,\n p_o_sampling,\n anat_material,\n anat_part,\n body_product,\n envi_material,\n envi_site,\n col_device,\n col_method,\n col_protocol,\n spec_process,\n lab_host,\n passage_num,\n passage_method,\n biom_extract,\n host_com_name,\n host_sci_name,\n host_health_state,\n host_health_status,\n host_disease,\n host_age,\n host_gender,\n host_loc_country,\n host_sub_id,\n symp_onset_date,\n signs_symptoms,\n loc_exp_country,\n trav_history,\n exp_event,\n library_id,\n minion_barcode,\n seq_instrument,\n seq_prot_name,\n seq_prot_source,\n seq_kit_num,\n amp_pcr_filename,\n raw_seq_process,\n seq_depth_avg,\n assemb_name,\n assemb_method,\n assemb_cov_breadth,\n assemb_cov_depth,\n r1_filename,\n r2_filename,\n r1_filepath,\n r2_filepath,\n fast5_filename,\n fast5_filepath,\n fasta_filename,\n fasta_filepath,\n num_bp,\n cons_genome_len,\n mean_contig_len,\n n50,\n ns_100kbp,\n ref_genome_accession,\n cons_seq_id,\n cons_seq_method,\n cons_seq_filename,\n cons_seq_filepath,\n annot_table_filename,\n biof_protocol,\n gene_1,\n pcr_protocol_1,\n pcr_ct_1,\n gene_2,\n pcr_protocol_2,\n pcr_ct_2,\n authors]\n\n # Error grid valid/invalid (error specific) information.\n grid = ['-', # spec_col_sample_id_error placeholder\n phac_sample_id_error,\n '-', # irida_sample_id_error placeholder\n ub_accession_error,\n bp_accession_error,\n bs_accession_error,\n sra_accession_error,\n gb_accession_error,\n gisaid_accession_error,\n samp_col_by_error,\n samp_col_email_error,\n samp_col_address_error,\n '-', # seq_sub_by_error placeholder\n seq_sub_email_error,\n seq_sub_address_error,\n samp_col_date_error,\n samp_rec_date_error,\n geo_loc_country_error,\n geo_loc_prov_ter_error,\n geo_loc_city_error,\n organism_error,\n '-', # isolate_error placeholder\n p_o_sampling_error,\n anat_material_error,\n anat_part_error,\n body_product_error,\n envi_material_error,\n envi_site_error,\n col_device_error,\n col_method_error,\n col_protocol_error,\n spec_process_error,\n lab_host_error,\n passage_num_error,\n passage_method_error,\n biom_extract_error,\n host_com_name_error,\n host_sci_name_error,\n host_health_state_error,\n host_health_status_error,\n host_disease_error,\n host_age_error,\n host_gender_error,\n host_loc_country_error,\n host_sub_id_error,\n symp_onset_date_error,\n signs_symptoms_error,\n loc_exp_country_error,\n trav_history_error,\n exp_event_error,\n library_id_error,\n minion_barcode_error,\n seq_instrument_error,\n seq_prot_name_error,\n seq_prot_source_error,\n seq_kit_num_error,\n amp_pcr_filename_error,\n raw_seq_process_error,\n seq_depth_avg_error,\n assemb_name_error,\n assemb_method_error,\n assemb_cov_breadth_error,\n assemb_cov_depth_error,\n r1_filename_error,\n r2_filename_error,\n r1_filepath_error,\n r2_filepath_error,\n fast5_filename_error,\n fast5_filepath_error,\n fasta_filename_error,\n fasta_filepath_error,\n num_bp_error,\n cons_genome_len_error,\n mean_contig_len_error,\n n50_error,\n ns_100kbp_error,\n ref_genome_accession_error,\n cons_seq_id_error,\n cons_seq_method_error,\n cons_seq_filename_error,\n cons_seq_filepath_error,\n annot_table_filename_error,\n biof_protocol_error,\n gene_1_error,\n pcr_protocol_1_error,\n pcr_ct_1_error,\n gene_2_error,\n pcr_protocol_2_error,\n pcr_ct_2_error,\n authors_error]\n\n # return row of data for data file and row of data validity for error grid.\n return cols, grid","def test_returned_num_in_random_nums(self):\n self._setup_random_gen([1.], [42])\n self.assertEqual(self._random_gen.next_num(), 42)","def test_kf_id():\n\n for _ in range(1000):\n prefix = ''.join(random.sample(string.ascii_uppercase, 2))\n kf_id = kf_id_generator(prefix)()\n assert kf_id[:2] == prefix\n assert len(kf_id) == 11\n assert kf_id[2] == '_'\n\n assert 'I' not in kf_id[2:]\n assert 'L' not in kf_id[2:]\n assert 'O' not in kf_id[2:]\n assert 'U' not in kf_id[2:]\n\n assert re.search(r'^'+prefix+r'_[A-HJ-KM-NP-TV-Z0-9]{8}', kf_id)","def test_run_sim_1():\n rnd = rand.Arrivals(36, 41)\n sim.run_sim(3, 2, 5, 6, 22, rnd)","def test_spin_type(fixture_code, generate_structure):\n code = fixture_code('quantumespresso.pw')\n structure = generate_structure()\n\n with pytest.raises(NotImplementedError):\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\n PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=spin_type)\n\n builder = PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=SpinType.COLLINEAR)\n\n for namespace in [builder.relax['base'], builder.scf, builder.bands]:\n parameters = namespace['pw']['parameters'].get_dict()\n assert parameters['SYSTEM']['nspin'] == 2\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}","def generaterandomindices(dataSize, percentTest):\n\n TrainIndices = np.array([])\n while TrainIndices.__len__() < int(percentTest * dataSize):\n # Randomly select an index value and store it. If it has already been chosen, pick again.\n index = int(random.random() * dataSize)\n if not TrainIndices.__contains__(index):\n TrainIndices = np.append(TrainIndices, [index])\n\n # For aesthetic purposes:\n TrainIndices = np.sort(TrainIndices)\n\n return TrainIndices","def test_if_array_is_good(self):\n testing_param = random.randint(1, 100)\n self.assertEqual(self.exercice.main(testing_param),\n list(range(2, testing_param+1, 2)))","def gen_data(min_coord, max_coord, size):\r\n data = np.random.randint(min_coord, max_coord, size)\r\n return data","def test_scan_id_range(self):\n scan = '16~17'\n ref_idx = [1,2,3]\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_SampleIds(self):\r\n exp = [\"PC.354\", \"PC.355\", \"PC.356\", \"PC.481\", \"PC.593\", \"PC.607\",\r\n \"PC.634\", \"PC.635\", \"PC.636\"]\r\n obs = self.overview_map.SampleIds\r\n self.assertEqual(obs, exp)\r\n\r\n obs = self.no_metadata.SampleIds\r\n self.assertEqual(obs, exp)\r\n\r\n obs = self.empty_map.SampleIds\r\n self.assertEqual(obs, [])","def test_SampleIds(self):\n exp = [\"PC.354\", \"PC.355\", \"PC.356\", \"PC.481\", \"PC.593\", \"PC.607\",\n \"PC.634\", \"PC.635\", \"PC.636\"]\n obs = self.overview_map.SampleIds\n self.assertEqual(obs, exp)\n\n obs = self.no_metadata.SampleIds\n self.assertEqual(obs, exp)\n\n obs = self.empty_map.SampleIds\n self.assertEqual(obs, [])","def test_0():\n sync.gen_multi_fake_data()#default is only one randomly selected data set\n sync.main(testing=True)","def test_assign_resources_to_tmc_subarray_in_low():","def test_main(data, tmp_path):\n\n main(data, tmp_path)\n\n FILES = (\n \"gd32f888x(0-1)xx-pinctrl.h\",\n \"gd32f888x(2-3)xx-pinctrl.h\",\n \"gd32f888y(0-1)xx-pinctrl.h\",\n \"gd32f999x(0-1)xx-pinctrl.h\",\n \"gd32f999x(2-3)xx-pinctrl.h\",\n \"gd32f999y(0-1)xx-pinctrl.h\",\n )\n\n for file in FILES:\n ref_file = data / file\n gen_file = tmp_path / file\n\n assert gen_file.exists()\n\n with open(ref_file) as ref, open(gen_file) as gen:\n assert ref.read() == gen.read()","def generate_synth_data(n):","def test_init():\n mesh = CuboidMesh(nx=100, ny=1, nz=1)\n sim = Sim(mesh)\n sim.set_m(init_m)\n\n expected = np.array([0, 0, 1,\n 0, np.sin(0.1), np.cos(0.1)])\n\n assert max(abs(sim.spin[:6] - expected)) < 1e-15","def test_get_data_array():\n test_file = os.path.join(DATA_PATH, \"paper_test_file.uvh5\")\n test_uv = UVData()\n test_uv.read(test_file)\n\n baseline_array = np.array(list(set(test_uv.baseline_array)))\n data_array = utils.get_data_array(test_uv, reds=baseline_array)\n\n compare_data = np.zeros(\n (test_uv.Npols, test_uv.Nbls, test_uv.Ntimes, test_uv.Nfreqs),\n dtype=np.complex64,\n )\n\n pol_array = uvutils.polnum2str(test_uv.polarization_array)\n for pol_cnt, pol in enumerate(pol_array):\n for cnt, baseline in enumerate(list(set(test_uv.baseline_array))):\n ant_1, ant_2 = test_uv.baseline_to_antnums(baseline)\n compare_data[pol_cnt, cnt] = test_uv.get_data(ant_1, ant_2, pol)\n\n compare_data = compare_data.squeeze(axis=0)\n assert np.allclose(compare_data, data_array)","def test1():\n for test in pkl.load(open(TEST_RESOURCES_DIR / \"regression_vault.pkl\", \"rb\"))[:5]:\n init_dict, rslt = test\n np.testing.assert_array_equal(run_regression_test(init_dict), rslt)","def test_run_sim():\n rnd = rand.Arrivals(31, 40)\n sim.run_sim(2, 1, 3, 4, 24, rnd)","def _generate_id() -> str:\n return \"\".join(sample(\"abcdefghjkmopqrstuvqxyz\", 16))","def generate_raiz():\n\treturn os.urandom(12)","def iv_gen():\r\n rndiv = os.urandom(16)\r\n return rndiv","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def random_lottery():\n\treturn 0","def test_arbitrary_rotation(self):\n \n # This test is run a bunch of times on various intervals, ranging from 50% to 1/6\n\t\t# (16.667%).\n for i in range(2, 7):\n \n interval = 1 / i # The amount to increase each qubit's probability by, relative to the previous qubit\n step_string = \"{:.4f}\".format(100 / i) # The decimal representation of the interval, as a percent\n target_probabilities = [0] * (i + 1) # This will store the desired probabilities of each qubit\n for j in range(0, i + 1):\n target_probability = j * interval\n target_probabilities[j] = target_probability\n\n # Run the test\n self.run_test(self.arbitrary_rotation_function, f\"Rotation with steps of 1/{i} ({step_string}%)\", 2000, target_probabilities, 0.05)","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def generate_client_volgen_data(data):\n\n # No of distribute groups in a volume\n dist_grp_count = 0\n # No of storage units in a distribute group\n storage_unit_count = 0\n replica_count = 0\n arbiter_count = 0\n\n get_replica_count = {\n \"Replica1\" : 1,\n \"Replica2\" : 2,\n \"Replica3\" : 3\n }\n\n if data[\"type\"] == \"Disperse\":\n storage_unit_count = data[\"disperse\"][\"data\"] + data[\"disperse\"][\"redundancy\"]\n replica_count = 0\n elif \"Replica\" in data[\"type\"]:\n storage_unit_count = replica_count = get_replica_count.get(data[\"type\"], \"\")\n elif data[\"type\"] == \"Arbiter\":\n storage_unit_count = replica_count = 3\n arbiter_count = 1\n\n client_data = {}\n client_data[\"name\"] = data[\"volname\"]\n client_data[\"id\"] = data[\"volume_id\"]\n\n dist_grp_count = int((len(data[\"bricks\"]) / storage_unit_count))\n client_data[\"distribute_groups\"] = [{} for _ in range(dist_grp_count)]\n\n for dist_grp_idx, dist_grp in enumerate(client_data[\"distribute_groups\"]):\n if \"Replica\" in data[\"type\"]:\n dist_grp[\"type\"] = \"replicate\"\n elif \"Disperse\" in data[\"type\"]:\n dist_grp[\"type\"] = \"disperse\"\n else:\n dist_grp[\"type\"] = \"arbiter\"\n\n if replica_count:\n dist_grp[\"replica_count\"] = replica_count\n if arbiter_count:\n dist_grp[\"arbiter_count\"] = arbiter_count\n if dist_grp[\"type\"] == \"disperse\":\n dist_grp[\"disperse_count\"] = data[\"disperse\"].get(\"data\", 0)\n dist_grp[\"redundancy_count\"] = data[\"disperse\"].get(\"redundancy\", 0)\n\n dist_grp[\"storage_units\"] = [{} for _ in range(storage_unit_count)]\n\n for storage_unit_idx, storage_unit in enumerate(dist_grp[\"storage_units\"]):\n brick_idx = (dist_grp_idx * storage_unit_count + storage_unit_idx)\n storage_unit[\"path\"] = data[\"bricks\"][brick_idx].get(\"brick_path\", \"\")\n storage_unit[\"port\"] = 24007\n storage_unit[\"node\"] = {\n \"name\" : data[\"bricks\"][brick_idx].get(\"node\", \"\"),\n \"id\" : data[\"bricks\"][brick_idx].get(\"node_id\", \"\")\n }\n\n return client_data","def test_return_spin_pipe_fail(self):\n\n # Try to get a spin from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')","def test_assign_resources_to_tmc_subarray_in_mid():","def genNumID(size):\n\tid = \"\"\n\tfor i in range(size):\n\t\tid = id + selectRandomFromList(numTokens)\n\treturn id","def test_brains_id_get(self):\n pass","def test_start_ids_10(self):\n\n\t\texpected_num_layers = 11\n\t\texpected_ids = np.arange(10,21)\n\t\t# test describe\n\t\tdetails = self.watcher.describe(start_ids=10)\n\t\tprint(\"start id = 10\", details)\n\t\tactual_ids = details.layer_id.to_numpy().tolist()\n\t\tself.assertTrue(np.array_equal(actual_ids, expected_ids))\n\t\tself.assertEqual(len(expected_ids), expected_num_layers)\n\t\t\t\t\n\t\treturn","def test_pol_id_range(self):\n pol = '0~1'\n ref_idx = []\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def generate_run_id(self):\n r_id_len = 4\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\n while r_id in self.cache:\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\n return r_id","def create_test_sino_3d_tilted(A=9, Nx=22, Ny=22, max_phase=5.0,\n ampl_range=(1.0, 1.0),\n tilt_plane=0.0):\n # initiate array\n resar = np.zeros((A, Ny, Nx), dtype=np.complex128)\n # 2pi coverage\n angles = np.linspace(0, 2*np.pi, A, endpoint=False)\n # x-values of Gaussain\n x = np.linspace(-Nx/2, Nx/2, Nx, endpoint=True).reshape(1, -1)\n y = np.linspace(-Ny/2, Ny/2, Ny, endpoint=True).reshape(-1, 1)\n # SD of Gaussian\n dev = min(np.sqrt(Nx/2), np.sqrt(Ny/2))\n # Off-centered rotation about second axis:\n off = Nx/7\n for ii in range(A):\n # Gaussian distribution sinogram\n x0 = np.cos(angles[ii])*off\n phase = np.exp(-(x-x0)**2/dev**2) * np.exp(-(y)**2/dev**2)\n phase = normalize(phase, vmax=max_phase)\n if ampl_range[0] == ampl_range[1]:\n # constant amplitude\n ampl = np.ones((Nx, Ny))*ampl_range[0]\n else:\n # ring\n ampldev = dev/5\n amploff = off*.3\n ampl1 = np.exp(-(x-x0-amploff)**2/ampldev**2)\n ampl2 = np.exp(-(x-x0+amploff)**2/ampldev**2)\n ampl = ampl1+ampl2\n ampl = normalize(ampl, vmin=ampl_range[0], vmax=ampl_range[1])\n\n # perform in-plane rotation\n ampl = rotate(ampl, np.rad2deg(tilt_plane), reshape=False, cval=1)\n phase = rotate(phase, np.rad2deg(tilt_plane), reshape=False, cval=0)\n resar[ii] = ampl*np.exp(1j*phase)\n\n return resar, angles","def generate_license_plate(self, num):\n license_plate = []\n for _ in range(num):\n license_plate.append(self.fake.license_plate())\n return license_plate","def test_spin_loop_multiatom(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def test_CreateROI1(self):\r\n\r\n self.delayDisplay(\"Starting the test\")\r\n #\r\n # first, get some data\r\n #\r\n import urllib\r\n downloads = (\r\n ('http://slicer.kitware.com/midas3/download?items=5767', 'FA.nrrd', slicer.util.loadVolume),\r\n )\r\n\r\n for url,name,loader in downloads:\r\n filePath = slicer.app.temporaryPath + '/' + name\r\n if not os.path.exists(filePath) or os.stat(filePath).st_size == 0:\r\n logging.info('Requesting download %s from %s...\\n' % (name, url))\r\n urllib.urlretrieve(url, filePath)\r\n if loader:\r\n logging.info('Loading %s...' % (name,))\r\n loader(filePath)\r\n self.delayDisplay('Finished with download and loading')\r\n\r\n volumeNode = slicer.util.getNode(pattern=\"FA\")\r\n logic = CreateROILogic()\r\n self.assertIsNotNone( logic.hasImageData(volumeNode) )\r\n self.delayDisplay('Test passed!')","def test_id(self):\n b1 = Base()\n self.assertEqual(b1.id, 1)\n b2 = Base()\n self.assertEqual(b2.id, 2)\n b3 = Base(98)\n self.assertEqual(b3.id, 98)\n b4 = Base(256)\n self.assertEqual(b4.id, 256)\n b5 = Base()\n self.assertEqual(b5.id, 3)\n b6 = Base(-98)\n self.assertEqual(b6.id, -98)\n b7 = Base(None)\n self.assertEqual(b7.id, 4)\n b8 = Base(4.4)\n self.assertEqual(b8.id, 4.4)","def test_field_id_list(self):\n field = '5,8'\n ref_idx = [0,3]\n self.res=self.run_task(infile=self.rawfile,field=field,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_residue_loop(self):\n\n # Loop over the residues.\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\n # Test the selection.\n self.assertEqual(res.num, 2)\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)","def test_api_random_id(api_client, single_brew_number):\n response = api_client.get(path='/breweries' + '/' + str(single_brew_number))\n assert response.json()['id'] == single_brew_number","def _spin_sequence(self):\n self.return_position = self.motor.position\n \n for spin_num in range(self.num_spins):\n self.taxi()\n\n det_pre_acquire(self.detector)\n self.fly()\n det_post_acquire(self.detector)\n\n while self.detector.hdf1.write_file.value:\n time.sleep(0.01) # wait for file to be written\n\n event = OrderedDict()\n event[\"time\"] = time.time()\n event[\"seq_num\"] = spin_num + 1\n event[\"data\"] = {}\n event[\"timestamps\"] = {}\n for d_item in (self.detector.hdf1.full_file_name,):\n d = d_item.read()\n for k, v in d.items():\n event['data'][k] = v['value']\n event['timestamps'][k] = v['timestamp']\n\n self._data.append(event)\n\n self.set(\"Return\")\n self._completion_status._finished(success=True)","def test_generate_factoid():\n generator = mockdata.generate_factoid()\n for i in range(100):\n factoid = next(generator)\n assert factoid[\"@id\"] == \"Factoid %03d\" % (i + 1)\n assert \"Person\" in factoid[\"person\"][\"@id\"]\n assert \"Source\" in factoid[\"source\"][\"@id\"]\n assert \"statement\" in factoid\n assert factoid[\"statement\"][\"@id\"] == \"F%dS1\" % (i + 1)","def test_test_ids_request(get_interface_params):\n from sail_on_client.protocol.localinterface import LocalInterface\n\n config_directory, config_name = get_interface_params\n data_dir = f\"{os.path.dirname(__file__)}/data\"\n local_interface = LocalInterface(config_name, config_directory)\n\n assumptions_path = os.path.join(os.path.dirname(__file__), \"assumptions.json\")\n filename = local_interface.test_ids_request(\n \"OND\", \"image_classification\", \"5678\", assumptions_path\n )\n expected = os.path.join(data_dir, \"OND\", \"image_classification\", \"test_ids.csv\")\n assert os.stat(expected).st_size > 5\n assert expected == filename","def test_004_init(self):\n self.assertIsInstance(rawdata.rawdata(\"id\",testRawdata.ioc,testRawdata.sam),rawdata.rawdata)","def test_ipam_rirs_create(self):\n pass","def test_id_get(mocker):\n mocker.patch('serial.Serial.open')\n mocker.patch('serial.Serial.flushInput')\n css = mocker.patch('pysds011.driver.SDS011.cmd_set_sleep')\n css.return_value = True\n cfv = mocker.patch('pysds011.driver.SDS011.cmd_firmware_ver')\n cfv.return_value = {'id': b'\\x12\\x34', 'paperino': 'maciomicio'}\n runner = CliRunner()\n result = runner.invoke(main, ['id'])\n\n calls = [call(0, id=b'\\xff\\xff'), call(1, id=b'\\xff\\xff')]\n css.assert_has_calls(calls, any_order=False)\n\n assert '12' in result.output and '34' in result.output\n assert result.exit_code == 0","def test_post_cve_id_reserve_sequential_over_quota(reg_user_headers):\n res = get_reserve_cve_ids(100001, utils.CURRENT_YEAR, reg_user_headers['CVE-API-ORG'])\n assert res.status_code == 403\n response_contains_json(res, 'error', 'EXCEEDED_ID_QUOTA')","def next():\n iraw = 0\n run = 0\n seqno = 0\n with db_connection() as conn:\n with conn.cursor() as curs:\n try:\n curs.execute(\"\"\"SELECT rawdata.id,rawdata.run,rawdata.seqno,\n slices.block1,slices.block2,\n jobs.cluster,jobs.process\n FROM rawdata\n LEFT JOIN bindings\n ON bindings.iraw = rawdata.id\n INNER JOIN slices\n ON slices.iraw = rawdata.id\n LEFT JOIN jobs\n ON slices.ijob = jobs.id\n AND jobs.exitcode = 0\n WHERE bindings.id IS NULL\n ORDER BY rawdata.id,slices.block1\n LIMIT 2000;\n \"\"\")\n slices_missing = 1\n for row in curs.fetchall():\n i = int(row[0])\n if i != iraw:\n if slices_missing == 0:\n break\n else:\n run = int(row[1])\n seqno = int(row[2])\n slices_missing = 0\n slices = []\n iraw = i\n block1 = int(row[3])\n block2 = int(row[4])\n if row[5] is not None and row[6] is not None:\n cluster = int(row[5])\n process = int(row[6])\n slices.append((block1,block2,cluster,process))\n else:\n print(\"slices missing on\", row[5], row[6])\n slices_missing += 1\n if slices_missing:\n return 0\n else:\n curs.execute(\"SELECT TIMEZONE('GMT', NOW());\")\n now = curs.fetchone()[0]\n curs.execute(\"\"\"INSERT INTO bindings\n (iraw,starttime)\n VALUES (%s,%s)\n RETURNING id;\n \"\"\", (iraw, now))\n row = curs.fetchone()\n if row:\n ibind = int(row[0])\n else:\n return 0\n except:\n iraw = 0\n if iraw == 0:\n time.sleep(random.randint(1,30))\n return -9 # collision\n\n workdir = str(iraw)\n os.mkdir(workdir)\n os.chdir(workdir)\n badslices = []\n for sl in slices:\n sdir = str(sl[0]) + \",\" + str(sl[1])\n os.mkdir(sdir)\n tarfile = \"job_{0}_{1}.tar.gz\".format(sl[2], sl[3])\n tarpath = input_area + \"/\" + tarfile\n try:\n subprocess.check_output([\"gfal-copy\", src_url + tarpath,\n \"file://\" + os.getcwd() + \"/\" + tarfile])\n except:\n sys.stderr.write(\"Error -999 on rawdata id {0}\".format(iraw) +\n \" - job output \" + tarfile + \" is missing!\\n\")\n sys.stderr.flush()\n badslices.append(sdir)\n continue\n try:\n subprocess.check_output([\"tar\", \"zxf\", tarfile, \"-C\", sdir])\n except:\n sys.stderr.write(\"Error -999 on rawdata id {0}\".format(iraw) +\n \" - job output \" + tarfile + \" is not readable!\\n\")\n sys.stderr.flush()\n badslices.append(sdir)\n finally:\n os.remove(tarfile)\n if len(badslices) > 0:\n with db_connection() as conn:\n with conn.cursor() as curs:\n curs.execute(\"SELECT TIMEZONE('GMT', NOW());\")\n now = curs.fetchone()[0]\n curs.execute(\"\"\"UPDATE bindings\n SET endtime=%s, \n exitcode=%s,\n details=%s\n WHERE id = %s;\n \"\"\", (now, -999, \":\".join(badslices), ibind))\n os.chdir(\"..\")\n shutil.rmtree(workdir)\n return 1\n\n badslices += merge_evio_skims(run, seqno, slices)\n badslices += merge_hddm_output(run, seqno, slices)\n badslices += merge_job_info(run, seqno, slices)\n badslices += merge_root_histos(run, seqno, slices)\n exitcode = -len(badslices)\n with db_connection() as comm:\n with conn.cursor() as curs:\n curs.execute(\"SELECT TIMEZONE('GMT', NOW());\")\n now = curs.fetchone()[0]\n curs.execute(\"\"\"UPDATE bindings\n SET endtime=%s,\n exitcode=%s,\n details=%s\n WHERE id = %s;\n \"\"\", (now, exitcode, \":\".join(badslices), ibind))\n os.chdir(\"..\")\n shutil.rmtree(workdir)\n return 1","def get_ids(data, N_max):\n\n id_data = data[['molecule_name', 'id']].copy()\n\n # write molecules into one line\n id_data = id_data.groupby('molecule_name').apply(lambda x:\n x.values.reshape(-1))\n\n # pad with nans\n id_list = []\n for i in range(len(id_data)):\n n = N_max*2 - len(id_data[i])\n id_list.append(np.pad(id_data[i], (0, n), 'constant',\n constant_values=(0, np.nan)))\n\n # build np array and remove molecule names\n id_data = np.vstack(id_list)\n del id_list\n id_data = np.delete(id_data, [2*i for i in range(N_max)], 1)\n\n return id_data","def test_generation_index_one(self):\n generator = math_helpers.triangle_number_generator(1)\n first_ten_triangle_numbers = [next(generator) for _ in range(10)]\n canonical_values = [1, 3, 6, 10, 15, 21, 28, 36, 45, 55]\n self.assertEqual(canonical_values, first_ten_triangle_numbers)","def __test_gen_report_id_check():\n # all fresh\n report = dp.Report(md_block, md_block, md_block)\n assert_report(report) # expected_id_count=5)\n # 2 fresh\n report = dp.Report(md_block, md_block_id, md_block)\n assert_report(report) # expected_id_count=4)\n # 0 fresh\n report = dp.Report(md_block_id, dp.Text(\"test\", name=\"test-2\"))\n assert_report(report) # expected_id_count=2)","def data_gen(size, p):\n #print(np.random.get_state()[1][0])\n random_table = np.random.binomial(size = size, p = p, n = 1)\n test_array = np.zeros((size, 2), dtype = int)\n for i in range(size):\n test_array[i,0] = i\n test_array[i,1] = random_table[i]\n return test_array","def test_rand_func2(self):\n for i in range(0, 100000):\n num = random.randint(0, 32535143990)\n func2_comp(num)"],"string":"[\n \"def test_generate_spin_id_data_array6(self):\\n\\n # The data.\\n data = ['1', 'GLY', None, None]\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\\n\\n # Test the string.\\n self.assertEqual(id, ':1')\",\n \"def test_generate_spin_id_data_array1(self):\\n\\n # The data.\\n data = ['1', 'GLY']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\\n\\n # Test the string.\\n self.assertEqual(id, ':1')\",\n \"def test_generate_spin_id_data_array2(self):\\n\\n # The data.\\n data = ['1', 'GLY', '234', 'NH']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2, spin_num_col=3, spin_name_col=4)\\n\\n # Test the string.\\n self.assertEqual(id, ':1@234')\",\n \"def test_generate_spin_id_data_array5(self):\\n\\n # The data.\\n data = ['Ap4Aase', '1', 'GLY', '234', 'NH']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5)\\n\\n # Test the string.\\n self.assertEqual(id, '#Ap4Aase:1@234')\",\n \"def test_generate_spin_id_data_array4(self):\\n\\n # The data.\\n data = ['Ap4Aase', '1', 'GLY']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3)\\n\\n # Test the string.\\n self.assertEqual(id, '#Ap4Aase:1')\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_id_array(self):\\n arr = vtk.vtkIdTypeArray()\\n arr.SetNumberOfTuples(10)\\n for i in range(10):\\n arr.SetValue(i, i)\\n\\n np = array_handler.vtk2array(arr)\\n self.assertEqual(numpy.all(np == range(10)), True)\",\n \"def test_create_template(self):\\n m_size = 10\\n data = ecn.IDData(m_size)\\n self.assertEqual(np.shape(data.ID_MATRIX), (m_size, m_size))\\n self.assertEqual(sum(sum(data.ID_MATRIX)), m_size)\\n self.assertTrue((sum(data.ID_MATRIX) == np.ones(m_size)).all())\\n print('Finished testing template\\\\n')\",\n \"def test_random_id(self):\\r\\n ids = \\\\\\r\\n \\\"R27DLI_4812 R27DLI_600 R27DLI_727 U1PLI_403 U1PLI_8969\\\".split(\\r\\n )\\r\\n assert random_id(ids, {}) in ids\\r\\n # just test we got something from the list, don't add stochastic test\\r\",\n \"def test_spin_loop(self):\\n\\n # Spin data.\\n select = [1, 0]\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, 'N5')\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 2)\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_arr2vtkIdList(self):\\n a = [1, 2, 3, 4, 5]\\n p = array_handler.array2vtkIdList(a)\\n for i, j in enumerate(a): \\n self.assertEqual(p.GetId(i), j)\\n p = vtk.vtkIdList()\\n ident = id(p)\\n p = array_handler.array2vtkIdList(numpy.array(a), p)\\n for i, j in enumerate(a): \\n self.assertEqual(p.GetId(i), j)\\n self.assertEqual(id(p), ident)\\n \\n self.assertRaises(AssertionError, array_handler.array2vtkIdList,\\n [[1,2,3]])\",\n \"def createArrayFunc(self):\\r\\n minVal = int(self.spinBoxMin_2.value())\\r\\n maxVal = int(self.spinBoxMax_2.value())\\r\\n arrayLength = int(self.spinBoxLength_2.value())\\r\\n different = maxVal - minVal\\r\\n if self.checkBoxNoRepeate_2.isChecked():\\r\\n if different > arrayLength:\\r\\n def unique_rand(initial, limit, total):\\r\\n data = []\\r\\n i = 0\\r\\n while i < total:\\r\\n number = numpy.random.randint(initial, limit)\\r\\n if number not in data:\\r\\n data.append(number)\\r\\n i += 1\\r\\n return data\\r\\n\\r\\n self.UnsortedArray_2 = unique_rand(minVal, maxVal, arrayLength)\\r\\n else:\\r\\n err = \\\"Array length must be greater than difference between limits\\\"\\r\\n self.labelUnsortedArray_2.setText(str(err))\\r\\n\\r\\n else:\\r\\n self.UnsortedArray_2 = numpy.random.randint(minVal, maxVal, arrayLength)\\r\\n self.labelUnsortedArray_2.setText(str(self.UnsortedArray_2))\\r\\n self.SortedArray_2 = Insertion.sorting(self.UnsortedArray_2)\\r\\n self.labelSortedArray_2.setText(str(self.SortedArray_2))\\r\\n binaryMax = int(self.spinBoxMax_2.value())\\r\\n binaryMin = int(self.spinBoxMin_2.value())\\r\\n self.spinBoxBinary.setMaximum(binaryMax)\\r\\n self.spinBoxBinary.setMinimum(binaryMin)\\r\\n self.spinBoxIthSmallest.setMaximum(arrayLength + 1)\",\n \"def test_get_ids(civic, main_data, updated_data):\\n assert len(civic._get_ids(main_data['assertions'])) == 0\\n assert len(civic._get_ids(main_data['variants'])) == 1\\n assert len(civic._get_ids(main_data['genes'])) == 2\\n assert len(civic._get_ids(main_data['evidence'])) == 1\\n\\n assert len(civic._get_ids(updated_data['assertions'])) == 1\\n assert len(civic._get_ids(updated_data['variants'])) == 1\\n assert len(civic._get_ids(updated_data['genes'])) == 1\\n assert len(civic._get_ids(updated_data['evidence'])) == 1\",\n \"def test_id_rot():\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_axis_angle(pr.a_id))\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_quaternion(pr.q_id))\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_xyz(pr.e_xyz_id))\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_zyx(pr.e_zyx_id))\",\n \"def _apply_array_spin123(self,\\n h1e: 'Nparray',\\n h2e: 'Nparray',\\n h3e: 'Nparray',\\n dvec: Optional[Tuple['Nparray', 'Nparray']] = None,\\n evec: Optional[Tuple['Nparray', 'Nparray', 'Nparray', 'Nparray']] \\\\\\n = None) -> 'Nparray':\\n norb = self.norb()\\n assert h3e.shape == (norb * 2,) * 6\\n assert not (dvec is None) ^ (evec is None)\\n\\n from1234 = (dvec is not None) and (evec is not None)\\n\\n nh1e = numpy.copy(h1e)\\n nh2e = numpy.copy(h2e)\\n\\n for i in range(norb * 2):\\n for j in range(norb * 2):\\n for k in range(norb * 2):\\n nh2e[j, k, :, :] += (-h3e[k, j, i, i, :, :] -\\n h3e[j, i, k, i, :, :] -\\n h3e[j, k, i, :, i, :])\\n\\n nh1e[:, :] += h3e[:, i, j, i, j, :]\\n\\n out = self._apply_array_spin12_halffilling(nh1e, nh2e)\\n\\n n = norb # This is just shorter\\n if not from1234:\\n symfac = 2.0\\n axes = ((1, 3), (0, 1))\\n (odveca, odvecb) = self.calculate_dvec_spin()\\n dveca = numpy.zeros_like(odveca)\\n dvecb = numpy.zeros_like(odvecb)\\n\\n for i in range(norb):\\n for j in range(norb):\\n evecaa, _ = self._calculate_dvec_spin_with_coeff(\\n odveca[i, j, :, :])\\n evecab, evecbb = self._calculate_dvec_spin_with_coeff(\\n odvecb[i, j, :, :])\\n\\n dveca += numpy.tensordot(h3e[:n, :n, i, :n, :n, j],\\n evecaa,\\n axes=axes)\\n dveca += numpy.tensordot(h3e[:n, :n, n + i, :n, :n, n + j],\\n evecab,\\n axes=axes) * symfac\\n dveca += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\\n evecbb,\\n axes=axes)\\n\\n dvecb += numpy.tensordot(h3e[n:, :n, i, n:, :n, j],\\n evecaa,\\n axes=axes)\\n dvecb += numpy.tensordot(h3e[n:, :n, n + i, n:, :n, n + j],\\n evecab,\\n axes=axes) * symfac\\n dvecb += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\\n evecbb,\\n axes=axes)\\n else:\\n symfac = 1.0\\n axes = ((1, 4, 2, 5), (0, 1, 2, 3)) # type: ignore\\n dveca, dvecb = dvec # type: ignore\\n evecaa, evecab, evecba, evecbb = evec # type: ignore\\n\\n dveca = numpy.tensordot(h3e[:n, :n, :n, :n, :n, :n],\\n evecaa, axes=axes) \\\\\\n + numpy.tensordot(h3e[:n, :n, n:, :n, :n, n:],\\n evecab, axes=axes) * symfac \\\\\\n + numpy.tensordot(h3e[:n, n:, n:, :n, n:, n:],\\n evecbb, axes=axes) + \\\\\\n + numpy.tensordot(h3e[:n, n:, :n, :n, n:, :n],\\n evecba, axes=axes)\\n\\n dvecb = numpy.tensordot(h3e[n:, :n, :n, n:, :n, :n],\\n evecaa, axes=axes) \\\\\\n + numpy.tensordot(h3e[n:, :n, n:, n:, :n, n:],\\n evecab, axes=axes) * symfac \\\\\\n + numpy.tensordot(h3e[n:, n:, n:, n:, n:, n:],\\n evecbb, axes=axes) + \\\\\\n + numpy.tensordot(h3e[n:, n:, :n, n:, n:, :n],\\n evecba, axes=axes)\\n\\n out -= self._calculate_coeff_spin_with_dvec((dveca, dvecb))\\n return out\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_scan_id_list(self):\\n scan = '15,17'\\n ref_idx = [0,3]\\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_spin_loop_no_selection(self):\\n\\n # Spin data.\\n select = [0, 1, 0, 0, 1, 1, 0, 1]\\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 8)\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def generate_T(number_obeservations):\\n T = np.random.randint(0, 2, (number_obeservations,1))\\n return T\",\n \"def test_weyl_specialize_id(self):\\n a, b, c = 0.0, 0.0, 0.0\\n for da, db, dc in DELTAS:\\n for k1l, k1r, k2l, k2r in K1K2SB:\\n k1 = np.kron(k1l.data, k1r.data)\\n k2 = np.kron(k2l.data, k2r.data)\\n self.check_two_qubit_weyl_specialization(\\n k1 @ Ud(a + da, b + db, c + dc) @ k2,\\n 0.999,\\n TwoQubitWeylIdEquiv,\\n {\\\"rz\\\": 4, \\\"ry\\\": 2},\\n )\",\n \"def test_pol_id_list(self):\\n pol = '0,1'\\n ref_idx = []\\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_spin_type(get_pdos_generator_inputs):\\n with pytest.raises(NotImplementedError):\\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=spin_type)\\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=SpinType.COLLINEAR)\\n for namespace in [builder.scf, builder.nscf]:\\n parameters = namespace['pw']['parameters'].get_dict()\\n assert parameters['SYSTEM']['nspin'] == 2\\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}\",\n \"def generate_new_ids(ids: np.array, n_required: int) -> np.array:\\n\\n current_max_id = ids.max()\\n new_ids = np.arange(n_required) + current_max_id + 1\\n\\n return new_ids\",\n \"def test_uuid():\\n for _ in range(1000):\\n uuid = uuid_generator()\\n assert len(uuid) == 36\\n assert uuid.count('-') == 4\",\n \"def test_random_integers(self):\\r\\n # Check over two calls to see if the random state is correctly updated.\\r\\n random = RandomStreams(utt.fetch_seed())\\r\\n fn = function([], random.random_integers((20, 20), -5, 5))\\r\\n fn_val0 = fn()\\r\\n fn_val1 = fn()\\r\\n\\r\\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\\r\\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\\r\\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\\r\\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\\r\\n\\r\\n assert numpy.all(fn_val0 == numpy_val0)\\r\\n assert numpy.all(fn_val1 == numpy_val1)\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def test_split_id_otp(self):\\n public_id, otp, = pyhsm.yubikey.split_id_otp(\\\"ft\\\" * 16)\\n self.assertEqual(public_id, '')\\n self.assertEqual(otp, \\\"ft\\\" * 16)\\n\\n public_id, otp, = pyhsm.yubikey.split_id_otp(\\\"cc\\\" + \\\"ft\\\" * 16)\\n self.assertEqual(public_id, 'cc')\\n self.assertEqual(otp, \\\"ft\\\" * 16)\",\n \"def test_generateuuids(self):\\n ret1 = {\\\"message\\\": \\\"No Random.org api key or api version found.\\\", \\\"res\\\": False}\\n self.assertDictEqual(random_org.generateUUIDs(), ret1)\\n\\n ret2 = {\\\"message\\\": \\\"Required argument, number is missing.\\\", \\\"res\\\": False}\\n self.assertDictEqual(\\n random_org.generateUUIDs(api_key=\\\"peW\\\", api_version=\\\"1\\\"), ret2\\n )\\n\\n ret3 = {\\\"message\\\": \\\"Number of UUIDs must be between 1 and 1000\\\", \\\"res\\\": False}\\n self.assertDictEqual(\\n random_org.generateUUIDs(api_key=\\\"peW\\\", api_version=\\\"1\\\", number=\\\"5\\\"), ret3\\n )\\n\\n ret3 = {\\\"message\\\": \\\"Parameter 'apiKey' is malformed\\\", \\\"res\\\": False}\\n self.assertDictEqual(\\n random_org.generateUUIDs(api_key=\\\"peW\\\", api_version=\\\"1\\\", number=5), ret3\\n )\",\n \"def myID() -> np.int:\\r\\n return 304976335\",\n \"def myID() -> np.int:\\r\\n return 304976335\",\n \"def generate_mixture_indicator(number_obeservations):\\n mixture_indicator = np.random.randint(0, 2, (number_obeservations,1))\\n return mixture_indicator\",\n \"def test_random_integers(self):\\r\\n # Check over two calls to see if the random state is correctly updated.\\r\\n m = Module()\\r\\n m.random = RandomStreams(utt.fetch_seed())\\r\\n m.fn = Method([], m.random.random_integers((20,20), -5, 5))\\r\\n\\r\\n made = m.make()\\r\\n made.random.initialize()\\r\\n fn_val0 = made.fn()\\r\\n fn_val1 = made.fn()\\r\\n\\r\\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\\r\\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\\r\\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\\r\\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\\r\\n\\r\\n assert numpy.all(fn_val0 == numpy_val0)\\r\\n assert numpy.all(fn_val1 == numpy_val1)\",\n \"def test_create_tornado_id(self):\\n\\n this_id_string = tornado_io.create_tornado_id(\\n start_time_unix_sec=TORNADO_START_TIME_UNIX_SEC,\\n start_latitude_deg=TORNADO_START_LATITUDE_DEG,\\n start_longitude_deg=TORNADO_START_LONGITUDE_DEG)\\n\\n self.assertTrue(this_id_string == TORNADO_ID_STRING)\",\n \"def generate_fake_data(t0, num_array, period=5820, data_range=[0.0, 24.0],\\n cyclic=True):\\n\\n if cyclic:\\n uts_root = np.mod(t0, period)\\n data = (np.mod(uts_root + num_array, period)\\n * (np.diff(data_range)[0] / np.float64(period))) + data_range[0]\\n else:\\n data = ((t0 + num_array) / period).astype(int)\\n\\n return data\",\n \"def test_generate(self):\\n cant_interations = int(random()*100)\\n for i in range(cant_interations):\\n number = self.sudoku.generate() # Generate number\\n self.assertGreaterEqual(number, 0) # number >= 0\\n self.assertLessEqual(number, 8) # number <= 8\",\n \"def _get_rand_array(self):\\n pass\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def get_test_split(self, fraction=0.1):\\n rng = np.random.default_rng(42)\\n test_size = int(round(len(self.all_asset_ids) * fraction))\\n test_ids = rng.choice(self.all_asset_ids, size=test_size, replace=False)\\n train_ids = [i for i in self.all_asset_ids if i not in test_ids]\\n return train_ids, test_ids\",\n \"def test_sampleId_pairs(self):\\r\\n # expected values\\r\\n dose_vps = \\\\\\r\\n [('1xDose', '2xDose'), ('1xDose', 'Control'),\\r\\n ('2xDose', 'Control')]\\r\\n ttd_vps = \\\\\\r\\n [('31', '21'), ('31', '55'), ('31', '67'), ('21', '55'),\\r\\n ('21', '67'), ('55', '67')]\\r\\n dose_sids = \\\\\\r\\n [(['Sam1', 'Sam2', 'Sam6'], ['Sam3', 'Sam4']),\\r\\n (['Sam1', 'Sam2', 'Sam6'], ['Sam5']),\\r\\n (['Sam3', 'Sam4'], ['Sam5'])]\\r\\n ttd_sids = \\\\\\r\\n [(['Sam1'], ['Sam3']),\\r\\n (['Sam1'], ['Sam4', 'Sam6']),\\r\\n (['Sam1'], ['Sam2', 'Sam5']),\\r\\n (['Sam3'], ['Sam4', 'Sam6']),\\r\\n (['Sam3'], ['Sam2', 'Sam5']),\\r\\n (['Sam4', 'Sam6'], ['Sam2', 'Sam5'])]\\r\\n\\r\\n # observed values\\r\\n obs_dose_sids, obs_dose_vps = sampleId_pairs(self.mapping_data,\\r\\n self.rarefaction_data, 'Dose')\\r\\n obs_ttd_sids, obs_ttd_vps = sampleId_pairs(self.mapping_data,\\r\\n self.rarefaction_data, 'TTD')\\r\\n\\r\\n # sort -- order is unimportant and depends on way presented in mf\\r\\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\\r\\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())\\r\\n self.assertEqual(ttd_vps.sort(), obs_ttd_vps.sort())\\r\\n self.assertEqual(ttd_sids.sort(), obs_ttd_sids.sort())\\r\\n\\r\\n # check errors when no samples had this category\\r\\n self.assertRaises(ValueError, sampleId_pairs, self.mapping_data,\\r\\n self.rarefaction_data, 'DNE')\\r\\n\\r\\n # check no error if map file has more sampleids than rarefaction data\\r\\n superset_mf = \\\\\\r\\n ['#SampleID\\\\tDose\\\\tLinkerPrimerSequence\\\\tWeight\\\\tTTD\\\\tDescription',\\r\\n '#Comment Line',\\r\\n 'Sam1\\\\t1xDose\\\\tATCG\\\\tHigh\\\\t31\\\\ts1_desc',\\r\\n 'Sam2\\\\t1xDose\\\\tACCG\\\\tLow\\\\t67\\\\ts2_desc',\\r\\n 'Sam3\\\\t2xDose\\\\tACGT\\\\tMed\\\\t21\\\\ts3_desc',\\r\\n 'Sam4\\\\t2xDose\\\\tAACG\\\\tLow\\\\t55\\\\ts4_desc',\\r\\n 'Sam5\\\\tControl\\\\tCGTC\\\\tLow\\\\t67\\\\ts5_desc',\\r\\n 'Sam6\\\\t1xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts6_desc',\\r\\n 'Sam7\\\\t4xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts7_desc',\\r\\n 'Sam8\\\\t3xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts8_desc',\\r\\n 'Sam9\\\\t1xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts9_desc']\\r\\n # (mf, comments)\\r\\n superset_mf = parse_mapping_file_to_dict(superset_mf)[0]\\r\\n obs_dose_sids, obs_dose_vps = sampleId_pairs(superset_mf,\\r\\n self.rarefaction_data, 'Dose')\\r\\n\\r\\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\\r\\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def make_row(invalid_data=[]):\\n\\n ### Database Identifiers ###\\n \\n # phac_sample_id, valid/invalid error-grid information.\\n phac_sample_id, phac_sample_id_error = lib.random_phac_id(invalid_data)\\n # umbrella_bioproject_accession, valid/invalid error-grid information.\\n ub_accession, ub_accession_error = lib.umbrella_bioproject_accession(invalid_data)\\n # bioproject_accession, valid/invalid error-grid information.\\n bp_accession, bp_accession_error = lib.random_bioproject_accession(invalid_data)\\n # biosample_accession, valid/invalid error-grid information.\\n bs_accession, bs_accession_error = lib.random_biosample_accession(invalid_data)\\n # sra_accession, valid/invalid error-grid information.\\n sra_accession, sra_accession_error = lib.random_sra_accession(invalid_data)\\n # genbank_accession, valid/invalid error-grid information.\\n gb_accession, gb_accession_error = lib.random_genbank_accession(invalid_data)\\n # gisaid_accession, valid/invalid error-grid information.\\n gisaid_accession, gisaid_accession_error = lib.random_gisaid_accession(invalid_data)\\n \\n ### Sample Collection and Processing ###\\n \\n # sample_collected_by, valid/invalid error-grid information.\\n samp_col_by, samp_col_by_error = lib.random_agency(invalid_data)\\n # sample_collector_contact_email, valid/invalid error-grid information.\\n samp_col_email, samp_col_email_error = lib.random_email(invalid_data)\\n # sample_collector_contact_address, valid/invalid error-grid information.\\n samp_col_address, samp_col_address_error = lib.random_address(invalid_data)\\n # sequence_submitter_contact_email, valid/invalid error-grid information.\\n seq_sub_email, seq_sub_email_error = lib.random_email(invalid_data)\\n # sequence_submitter_contact_address, valid/invalid error-grid information.\\n seq_sub_address, seq_sub_address_error = lib.random_address(invalid_data)\\n # sample_collection_date, valid/invalid error-grid information.\\n samp_col_date, samp_col_date_error = lib.random_date(invalid_data)\\n # sample_received_date, valid/invalid error-grid information.\\n samp_rec_date, samp_rec_date_error = lib.random_date(invalid_data)\\n # geo_loc_name_country, valid/invalid error-grid information.\\n geo_loc_country, geo_loc_country_error = lib.random_country(invalid_data)\\n # geo_loc_name_province_territory, valid/invalid error-grid information.\\n geo_loc_prov_ter, geo_loc_prov_ter_error = lib.random_province_territory(invalid_data)\\n # geo_loc_name_city, valid/invalid error-grid information.\\n geo_loc_city, geo_loc_city_error = lib.random_city(invalid_data)\\n # organism, valid/invalid error-grid information.\\n organism, organism_error = lib.random_organism(invalid_data)\\n # purpose_of_sampling, valid/invalid error-grid information.\\n p_o_sampling, p_o_sampling_error = lib.random_purpose_of_sampling(invalid_data)\\n # anatomical_material, valid/invalid error-grid information.\\n anat_material, anat_material_error = lib.random_anatomical_material(invalid_data)\\n # anatomical_part, valid/invalid error-grid information.\\n anat_part, anat_part_error = lib.random_anatomical_part(invalid_data)\\n # body_product, valid/invalid error-grid information.\\n body_product, body_product_error = lib.random_body_product(invalid_data)\\n # environmental_material, valid/invalid error-grid information.\\n envi_material, envi_material_error = lib.random_environmental_material(invalid_data)\\n # environmental_site, valid/invalid error-grid information.\\n envi_site, envi_site_error = lib.random_environmental_site(invalid_data)\\n # collection_device, valid/invalid error-grid information.\\n col_device, col_device_error = lib.random_collection_device(invalid_data)\\n # collection_method, valid/invalid error-grid information.\\n col_method, col_method_error = lib.random_collection_method(invalid_data)\\n # collection_protocol, valid/invalid error-grid information.\\n col_protocol, col_protocol_error = lib.fake_protocol(invalid_data)\\n # specimen_processing, valid/invalid error-grid information.\\n spec_process, spec_process_error = lib.random_specimen_processing(invalid_data)\\n # lab_host, valid/invalid error-grid information.\\n lab_host, lab_host_error = lib.random_lab_host(invalid_data)\\n # passage_number , valid/invalid error-grid information.\\n passage_num, passage_num_error = lib.random_passage_number(invalid_data)\\n # passage_method, valid/invalid error-grid information.\\n passage_method, passage_method_error = lib.passage_method_text(invalid_data)\\n # biomaterial_extracted, valid/invalid error-grid information.\\n biom_extract, biom_extract_error = lib.random_biomaterial_extracted(invalid_data)\\n \\n ### Host Information ###\\n \\n # host_common_name, valid/invalid error-grid information.\\n host_com_name, host_com_name_error = lib.random_host_common_name(invalid_data)\\n # host_scientific_name, valid/invalid error-grid information.\\n host_sci_name, host_sci_name_error = lib.random_host_scientific_name(invalid_data)\\n # host_health_state, valid/invalid error-grid information.\\n host_health_state, host_health_state_error = lib.random_host_health_state(invalid_data)\\n # host_health_status_details, valid/invalid error-grid information.\\n host_health_status, host_health_status_error = lib.random_host_health_status_details(invalid_data)\\n # host_disease, valid/invalid error-grid information.\\n host_disease, host_disease_error = lib.random_host_disease(invalid_data)\\n # host_age, valid/invalid error-grid information.\\n host_age, host_age_error = lib.random_host_age(invalid_data)\\n # host_gender, valid/invalid error-grid information.\\n host_gender, host_gender_error = lib.random_host_gender(invalid_data)\\n # host_origin_geo_loc_name_country, valid/invalid error-grid information.\\n host_loc_country, host_loc_country_error = lib.random_country(invalid_data)\\n # host_subject_id, valid/invalid error-grid information.\\n host_sub_id, host_sub_id_error = lib.random_host_subject_id(invalid_data)\\n # symptom_onset_date, valid/invalid error-grid information.\\n symp_onset_date, symp_onset_date_error = lib.random_date(invalid_data)\\n # signs_and_symptoms, valid/invalid error-grid information.\\n signs_symptoms, signs_symptoms_error = lib.random_signs_symptoms(invalid_data)\\n \\n ### Host Exposure Information ###\\n \\n # location_of_exposure_geo_loc_name_country, valid/invalid error-grid information.\\n loc_exp_country, loc_exp_country_error = lib.random_country(invalid_data)\\n # travel_history, valid/invalid error-grid information. \\n trav_history, trav_history_error = lib.random_travel_history(invalid_data)\\n # exposure_event, valid/invalid error-grid information.\\n exp_event, exp_event_error = lib.random_exposure_event(invalid_data)\\n \\n ### Sequencing ###\\n \\n # minion_barcode, valid/invalid error-grid information.\\n minion_barcode, minion_barcode_error = lib.random_minIon_barcode(invalid_data)\\n # sequencing_instrument, valid/invalid error-grid information.\\n seq_instrument, seq_instrument_error = lib.random_seq_instrument(invalid_data)\\n # sequencing_protocol_name, valid/invalid error-grid information.\\n seq_prot_name, seq_prot_name_error = lib.fake_protocol(invalid_data)\\n # sequencing_protocol_source, valid/invalid error-grid information.\\n seq_prot_source, seq_prot_source_error = lib.random_seq_protocol_source(invalid_data)\\n # sequencing_kit_number, valid/invalid error-grid information.\\n seq_kit_num, seq_kit_num_error = lib.random_seq_kit_num(invalid_data)\\n # amplicon_pcr_primers_filename, valid/invalid error-grid information.\\n amp_pcr_filename, amp_pcr_filename_error = lib.random_txt_filename(invalid_data)\\n \\n ### Bioinformatics and QC metrics ###\\n \\n # raw_sequence_data_processing, valid/invalid error-grid information.\\n raw_seq_process, raw_seq_process_error = lib.random_seq_process(invalid_data)\\n # sequencing_depth_average, valid/invalid error-grid information.\\n seq_depth_avg, seq_depth_avg_error = lib.random_seq_depth(invalid_data)\\n # assembly_method, valid/invalid error-grid information.\\n assemb_method, assemb_method_error = lib.random_assembly_software(invalid_data)\\n # assembly_coverage_breadth, valid/invalid error-grid information.\\n assemb_cov_breadth, assemb_cov_breadth_error = lib.random_assembly_coverage_breadth(invalid_data)\\n # assembly_coverage_depth, valid/invalid error-grid information.\\n assemb_cov_depth, assemb_cov_depth_error = lib.random_seq_depth(invalid_data)\\n # r1_fastq_filename, valid/invalid error-grid information.\\n r1_filename, r1_filename_error = lib.random_fastq_filename(invalid_data)\\n # r2_fastq_filename, valid/invalid error-grid information.\\n r2_filename, r2_filename_error = lib.random_fastq_filename(invalid_data)\\n # r1_fastq_filepath, valid/invalid error-grid information.\\n r1_filepath, r1_filepath_error = lib.random_filepath(r1_filename, invalid_data)\\n # r2_fastq_filepath, valid/invalid error-grid information.\\n r2_filepath, r2_filepath_error = lib.random_filepath(r2_filename, invalid_data)\\n # fast5_filename, valid/invalid error-grid information.\\n fast5_filename, fast5_filename_error = lib.random_fast5_filename(invalid_data)\\n # fast5_filepath, valid/invalid error-grid information.\\n fast5_filepath, fast5_filepath_error = lib.random_filepath(fast5_filename, invalid_data)\\n # fasta_filename, valid/invalid error-grid information.\\n fasta_filename, fasta_filename_error = lib.random_fasta_filename(invalid_data)\\n # fasta_filepath, valid/invalid error-grid information.\\n fasta_filepath, fasta_filepath_error = lib.random_filepath(fasta_filename, invalid_data)\\n # number_base_pairs, valid/invalid error-grid information.\\n num_bp, num_bp_error = lib.random_bp_num(invalid_data)\\n # consensus_genome_length, valid/invalid error-grid information.\\n cons_genome_len, cons_genome_len_error = lib.random_genome_length(invalid_data)\\n # mean_contig_length, valid/invalid error-grid information.\\n mean_contig_len, mean_contig_len_error = lib.random_contig_length(invalid_data)\\n # n50, valid/invalid error-grid information.\\n n50, n50_error = lib.random_n50(invalid_data)\\n # ns_per_100_kbp, valid/invalid error-grid information.\\n ns_100kbp, ns_100kbp_error = lib.random_ns_100kbp(invalid_data)\\n # reference_genome_accession, valid/invalid error-grid information.\\n ref_genome_accession, ref_genome_accession_error = lib.random_ref_genome(invalid_data)\\n # consensus_sequence_id, valid/invalid error-grid information.\\n cons_seq_id, cons_seq_id_error = lib.random_consensus_seq_id(invalid_data)\\n # consensus_sequence_method, valid/invalid error-grid information.\\n cons_seq_method, cons_seq_method_error = lib.random_consensus_seq_method(invalid_data)\\n # consensus_sequence_filename, valid/invalid error-grid information.\\n cons_seq_filename, cons_seq_filename_error = lib.random_fasta_filename(invalid_data)\\n # consensus_sequence_filepath, valid/invalid error-grid information.\\n cons_seq_filepath, cons_seq_filepath_error = lib.random_filepath(cons_seq_filename, invalid_data)\\n # annotation_feature_table_filename, valid/invalid error-grid information.\\n annot_table_filename, annot_table_filename_error = lib.random_feature_table_filename(invalid_data)\\n # bioinformatics_protocol, valid/invalid error-grid information.\\n biof_protocol, biof_protocol_error = lib.bioinformatics_protocol(invalid_data)\\n \\n ### Pathogen Diagnostic Testing ###\\n \\n # gene_name_1, valid/invalid error-grid information.\\n gene_1, gene_1_error = lib.random_gene(invalid_data)\\n # diagnostic_pcr_protocol_1, valid/invalid error-grid information.\\n pcr_protocol_1, pcr_protocol_1_error = lib.fake_protocol(invalid_data)\\n # diagnostic_pcr_ct_value_1, valid/invalid error-grid information.\\n pcr_ct_1, pcr_ct_1_error = lib.random_pcr_ct_val(invalid_data)\\n # gene_name_2, valid/invalid error-grid information.\\n gene_2, gene_2_error = lib.random_gene(invalid_data)\\n # diagnostic_pcr_protocol_2, valid/invalid error-grid information.\\n pcr_protocol_2, pcr_protocol_2_error = lib.fake_protocol(invalid_data)\\n # diagnostic_pcr_ct_value_2, valid/invalid error-grid information.\\n pcr_ct_2, pcr_ct_2_error = lib.random_pcr_ct_val(invalid_data)\\n \\n ### Contributor Acknowledgement ###\\n \\n # authors, valid/invalid error-grid information.\\n authors, authors_error = lib.authors(invalid_data)\\n \\n ### Dependent IDs ###\\n \\n # specimen_collector_sample_id.\\n spec_col_sample_id, spec_col_sample_id_error = lib.random_specimen_collector_sample_id(\\n geo_loc_country, \\n geo_loc_prov_ter,\\n geo_loc_city,\\n invalid_data)\\n # irida_sample_name.\\n irida_sample_id = spec_col_sample_id\\n # sequence_submitted_by.\\n seq_sub_by = samp_col_by\\n # library_id, valid/invalid error-grid information.\\n library_id, library_id_error = lib.random_library_id(spec_col_sample_id, invalid_data)\\n # isolate.\\n isolate = spec_col_sample_id\\n # assembly_name, valid/invalid error-grid information.\\n assemb_name, assemb_name_error = lib.random_assembly_name(spec_col_sample_id, invalid_data)\\n\\n # Row of generated data organised by column.\\n cols = [spec_col_sample_id,\\n phac_sample_id,\\n irida_sample_id,\\n ub_accession,\\n bp_accession,\\n bs_accession,\\n sra_accession,\\n gb_accession,\\n gisaid_accession,\\n samp_col_by,\\n samp_col_email,\\n samp_col_address,\\n seq_sub_by,\\n seq_sub_email,\\n seq_sub_address,\\n samp_col_date,\\n samp_rec_date,\\n geo_loc_country,\\n geo_loc_prov_ter,\\n geo_loc_city,\\n organism,\\n isolate,\\n p_o_sampling,\\n anat_material,\\n anat_part,\\n body_product,\\n envi_material,\\n envi_site,\\n col_device,\\n col_method,\\n col_protocol,\\n spec_process,\\n lab_host,\\n passage_num,\\n passage_method,\\n biom_extract,\\n host_com_name,\\n host_sci_name,\\n host_health_state,\\n host_health_status,\\n host_disease,\\n host_age,\\n host_gender,\\n host_loc_country,\\n host_sub_id,\\n symp_onset_date,\\n signs_symptoms,\\n loc_exp_country,\\n trav_history,\\n exp_event,\\n library_id,\\n minion_barcode,\\n seq_instrument,\\n seq_prot_name,\\n seq_prot_source,\\n seq_kit_num,\\n amp_pcr_filename,\\n raw_seq_process,\\n seq_depth_avg,\\n assemb_name,\\n assemb_method,\\n assemb_cov_breadth,\\n assemb_cov_depth,\\n r1_filename,\\n r2_filename,\\n r1_filepath,\\n r2_filepath,\\n fast5_filename,\\n fast5_filepath,\\n fasta_filename,\\n fasta_filepath,\\n num_bp,\\n cons_genome_len,\\n mean_contig_len,\\n n50,\\n ns_100kbp,\\n ref_genome_accession,\\n cons_seq_id,\\n cons_seq_method,\\n cons_seq_filename,\\n cons_seq_filepath,\\n annot_table_filename,\\n biof_protocol,\\n gene_1,\\n pcr_protocol_1,\\n pcr_ct_1,\\n gene_2,\\n pcr_protocol_2,\\n pcr_ct_2,\\n authors]\\n\\n # Error grid valid/invalid (error specific) information.\\n grid = ['-', # spec_col_sample_id_error placeholder\\n phac_sample_id_error,\\n '-', # irida_sample_id_error placeholder\\n ub_accession_error,\\n bp_accession_error,\\n bs_accession_error,\\n sra_accession_error,\\n gb_accession_error,\\n gisaid_accession_error,\\n samp_col_by_error,\\n samp_col_email_error,\\n samp_col_address_error,\\n '-', # seq_sub_by_error placeholder\\n seq_sub_email_error,\\n seq_sub_address_error,\\n samp_col_date_error,\\n samp_rec_date_error,\\n geo_loc_country_error,\\n geo_loc_prov_ter_error,\\n geo_loc_city_error,\\n organism_error,\\n '-', # isolate_error placeholder\\n p_o_sampling_error,\\n anat_material_error,\\n anat_part_error,\\n body_product_error,\\n envi_material_error,\\n envi_site_error,\\n col_device_error,\\n col_method_error,\\n col_protocol_error,\\n spec_process_error,\\n lab_host_error,\\n passage_num_error,\\n passage_method_error,\\n biom_extract_error,\\n host_com_name_error,\\n host_sci_name_error,\\n host_health_state_error,\\n host_health_status_error,\\n host_disease_error,\\n host_age_error,\\n host_gender_error,\\n host_loc_country_error,\\n host_sub_id_error,\\n symp_onset_date_error,\\n signs_symptoms_error,\\n loc_exp_country_error,\\n trav_history_error,\\n exp_event_error,\\n library_id_error,\\n minion_barcode_error,\\n seq_instrument_error,\\n seq_prot_name_error,\\n seq_prot_source_error,\\n seq_kit_num_error,\\n amp_pcr_filename_error,\\n raw_seq_process_error,\\n seq_depth_avg_error,\\n assemb_name_error,\\n assemb_method_error,\\n assemb_cov_breadth_error,\\n assemb_cov_depth_error,\\n r1_filename_error,\\n r2_filename_error,\\n r1_filepath_error,\\n r2_filepath_error,\\n fast5_filename_error,\\n fast5_filepath_error,\\n fasta_filename_error,\\n fasta_filepath_error,\\n num_bp_error,\\n cons_genome_len_error,\\n mean_contig_len_error,\\n n50_error,\\n ns_100kbp_error,\\n ref_genome_accession_error,\\n cons_seq_id_error,\\n cons_seq_method_error,\\n cons_seq_filename_error,\\n cons_seq_filepath_error,\\n annot_table_filename_error,\\n biof_protocol_error,\\n gene_1_error,\\n pcr_protocol_1_error,\\n pcr_ct_1_error,\\n gene_2_error,\\n pcr_protocol_2_error,\\n pcr_ct_2_error,\\n authors_error]\\n\\n # return row of data for data file and row of data validity for error grid.\\n return cols, grid\",\n \"def test_returned_num_in_random_nums(self):\\n self._setup_random_gen([1.], [42])\\n self.assertEqual(self._random_gen.next_num(), 42)\",\n \"def test_kf_id():\\n\\n for _ in range(1000):\\n prefix = ''.join(random.sample(string.ascii_uppercase, 2))\\n kf_id = kf_id_generator(prefix)()\\n assert kf_id[:2] == prefix\\n assert len(kf_id) == 11\\n assert kf_id[2] == '_'\\n\\n assert 'I' not in kf_id[2:]\\n assert 'L' not in kf_id[2:]\\n assert 'O' not in kf_id[2:]\\n assert 'U' not in kf_id[2:]\\n\\n assert re.search(r'^'+prefix+r'_[A-HJ-KM-NP-TV-Z0-9]{8}', kf_id)\",\n \"def test_run_sim_1():\\n rnd = rand.Arrivals(36, 41)\\n sim.run_sim(3, 2, 5, 6, 22, rnd)\",\n \"def test_spin_type(fixture_code, generate_structure):\\n code = fixture_code('quantumespresso.pw')\\n structure = generate_structure()\\n\\n with pytest.raises(NotImplementedError):\\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\\n PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=spin_type)\\n\\n builder = PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=SpinType.COLLINEAR)\\n\\n for namespace in [builder.relax['base'], builder.scf, builder.bands]:\\n parameters = namespace['pw']['parameters'].get_dict()\\n assert parameters['SYSTEM']['nspin'] == 2\\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}\",\n \"def generaterandomindices(dataSize, percentTest):\\n\\n TrainIndices = np.array([])\\n while TrainIndices.__len__() < int(percentTest * dataSize):\\n # Randomly select an index value and store it. If it has already been chosen, pick again.\\n index = int(random.random() * dataSize)\\n if not TrainIndices.__contains__(index):\\n TrainIndices = np.append(TrainIndices, [index])\\n\\n # For aesthetic purposes:\\n TrainIndices = np.sort(TrainIndices)\\n\\n return TrainIndices\",\n \"def test_if_array_is_good(self):\\n testing_param = random.randint(1, 100)\\n self.assertEqual(self.exercice.main(testing_param),\\n list(range(2, testing_param+1, 2)))\",\n \"def gen_data(min_coord, max_coord, size):\\r\\n data = np.random.randint(min_coord, max_coord, size)\\r\\n return data\",\n \"def test_scan_id_range(self):\\n scan = '16~17'\\n ref_idx = [1,2,3]\\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_SampleIds(self):\\r\\n exp = [\\\"PC.354\\\", \\\"PC.355\\\", \\\"PC.356\\\", \\\"PC.481\\\", \\\"PC.593\\\", \\\"PC.607\\\",\\r\\n \\\"PC.634\\\", \\\"PC.635\\\", \\\"PC.636\\\"]\\r\\n obs = self.overview_map.SampleIds\\r\\n self.assertEqual(obs, exp)\\r\\n\\r\\n obs = self.no_metadata.SampleIds\\r\\n self.assertEqual(obs, exp)\\r\\n\\r\\n obs = self.empty_map.SampleIds\\r\\n self.assertEqual(obs, [])\",\n \"def test_SampleIds(self):\\n exp = [\\\"PC.354\\\", \\\"PC.355\\\", \\\"PC.356\\\", \\\"PC.481\\\", \\\"PC.593\\\", \\\"PC.607\\\",\\n \\\"PC.634\\\", \\\"PC.635\\\", \\\"PC.636\\\"]\\n obs = self.overview_map.SampleIds\\n self.assertEqual(obs, exp)\\n\\n obs = self.no_metadata.SampleIds\\n self.assertEqual(obs, exp)\\n\\n obs = self.empty_map.SampleIds\\n self.assertEqual(obs, [])\",\n \"def test_0():\\n sync.gen_multi_fake_data()#default is only one randomly selected data set\\n sync.main(testing=True)\",\n \"def test_assign_resources_to_tmc_subarray_in_low():\",\n \"def test_main(data, tmp_path):\\n\\n main(data, tmp_path)\\n\\n FILES = (\\n \\\"gd32f888x(0-1)xx-pinctrl.h\\\",\\n \\\"gd32f888x(2-3)xx-pinctrl.h\\\",\\n \\\"gd32f888y(0-1)xx-pinctrl.h\\\",\\n \\\"gd32f999x(0-1)xx-pinctrl.h\\\",\\n \\\"gd32f999x(2-3)xx-pinctrl.h\\\",\\n \\\"gd32f999y(0-1)xx-pinctrl.h\\\",\\n )\\n\\n for file in FILES:\\n ref_file = data / file\\n gen_file = tmp_path / file\\n\\n assert gen_file.exists()\\n\\n with open(ref_file) as ref, open(gen_file) as gen:\\n assert ref.read() == gen.read()\",\n \"def generate_synth_data(n):\",\n \"def test_init():\\n mesh = CuboidMesh(nx=100, ny=1, nz=1)\\n sim = Sim(mesh)\\n sim.set_m(init_m)\\n\\n expected = np.array([0, 0, 1,\\n 0, np.sin(0.1), np.cos(0.1)])\\n\\n assert max(abs(sim.spin[:6] - expected)) < 1e-15\",\n \"def test_get_data_array():\\n test_file = os.path.join(DATA_PATH, \\\"paper_test_file.uvh5\\\")\\n test_uv = UVData()\\n test_uv.read(test_file)\\n\\n baseline_array = np.array(list(set(test_uv.baseline_array)))\\n data_array = utils.get_data_array(test_uv, reds=baseline_array)\\n\\n compare_data = np.zeros(\\n (test_uv.Npols, test_uv.Nbls, test_uv.Ntimes, test_uv.Nfreqs),\\n dtype=np.complex64,\\n )\\n\\n pol_array = uvutils.polnum2str(test_uv.polarization_array)\\n for pol_cnt, pol in enumerate(pol_array):\\n for cnt, baseline in enumerate(list(set(test_uv.baseline_array))):\\n ant_1, ant_2 = test_uv.baseline_to_antnums(baseline)\\n compare_data[pol_cnt, cnt] = test_uv.get_data(ant_1, ant_2, pol)\\n\\n compare_data = compare_data.squeeze(axis=0)\\n assert np.allclose(compare_data, data_array)\",\n \"def test1():\\n for test in pkl.load(open(TEST_RESOURCES_DIR / \\\"regression_vault.pkl\\\", \\\"rb\\\"))[:5]:\\n init_dict, rslt = test\\n np.testing.assert_array_equal(run_regression_test(init_dict), rslt)\",\n \"def test_run_sim():\\n rnd = rand.Arrivals(31, 40)\\n sim.run_sim(2, 1, 3, 4, 24, rnd)\",\n \"def _generate_id() -> str:\\n return \\\"\\\".join(sample(\\\"abcdefghjkmopqrstuvqxyz\\\", 16))\",\n \"def generate_raiz():\\n\\treturn os.urandom(12)\",\n \"def iv_gen():\\r\\n rndiv = os.urandom(16)\\r\\n return rndiv\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def random_lottery():\\n\\treturn 0\",\n \"def test_arbitrary_rotation(self):\\n \\n # This test is run a bunch of times on various intervals, ranging from 50% to 1/6\\n\\t\\t# (16.667%).\\n for i in range(2, 7):\\n \\n interval = 1 / i # The amount to increase each qubit's probability by, relative to the previous qubit\\n step_string = \\\"{:.4f}\\\".format(100 / i) # The decimal representation of the interval, as a percent\\n target_probabilities = [0] * (i + 1) # This will store the desired probabilities of each qubit\\n for j in range(0, i + 1):\\n target_probability = j * interval\\n target_probabilities[j] = target_probability\\n\\n # Run the test\\n self.run_test(self.arbitrary_rotation_function, f\\\"Rotation with steps of 1/{i} ({step_string}%)\\\", 2000, target_probabilities, 0.05)\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def generate_client_volgen_data(data):\\n\\n # No of distribute groups in a volume\\n dist_grp_count = 0\\n # No of storage units in a distribute group\\n storage_unit_count = 0\\n replica_count = 0\\n arbiter_count = 0\\n\\n get_replica_count = {\\n \\\"Replica1\\\" : 1,\\n \\\"Replica2\\\" : 2,\\n \\\"Replica3\\\" : 3\\n }\\n\\n if data[\\\"type\\\"] == \\\"Disperse\\\":\\n storage_unit_count = data[\\\"disperse\\\"][\\\"data\\\"] + data[\\\"disperse\\\"][\\\"redundancy\\\"]\\n replica_count = 0\\n elif \\\"Replica\\\" in data[\\\"type\\\"]:\\n storage_unit_count = replica_count = get_replica_count.get(data[\\\"type\\\"], \\\"\\\")\\n elif data[\\\"type\\\"] == \\\"Arbiter\\\":\\n storage_unit_count = replica_count = 3\\n arbiter_count = 1\\n\\n client_data = {}\\n client_data[\\\"name\\\"] = data[\\\"volname\\\"]\\n client_data[\\\"id\\\"] = data[\\\"volume_id\\\"]\\n\\n dist_grp_count = int((len(data[\\\"bricks\\\"]) / storage_unit_count))\\n client_data[\\\"distribute_groups\\\"] = [{} for _ in range(dist_grp_count)]\\n\\n for dist_grp_idx, dist_grp in enumerate(client_data[\\\"distribute_groups\\\"]):\\n if \\\"Replica\\\" in data[\\\"type\\\"]:\\n dist_grp[\\\"type\\\"] = \\\"replicate\\\"\\n elif \\\"Disperse\\\" in data[\\\"type\\\"]:\\n dist_grp[\\\"type\\\"] = \\\"disperse\\\"\\n else:\\n dist_grp[\\\"type\\\"] = \\\"arbiter\\\"\\n\\n if replica_count:\\n dist_grp[\\\"replica_count\\\"] = replica_count\\n if arbiter_count:\\n dist_grp[\\\"arbiter_count\\\"] = arbiter_count\\n if dist_grp[\\\"type\\\"] == \\\"disperse\\\":\\n dist_grp[\\\"disperse_count\\\"] = data[\\\"disperse\\\"].get(\\\"data\\\", 0)\\n dist_grp[\\\"redundancy_count\\\"] = data[\\\"disperse\\\"].get(\\\"redundancy\\\", 0)\\n\\n dist_grp[\\\"storage_units\\\"] = [{} for _ in range(storage_unit_count)]\\n\\n for storage_unit_idx, storage_unit in enumerate(dist_grp[\\\"storage_units\\\"]):\\n brick_idx = (dist_grp_idx * storage_unit_count + storage_unit_idx)\\n storage_unit[\\\"path\\\"] = data[\\\"bricks\\\"][brick_idx].get(\\\"brick_path\\\", \\\"\\\")\\n storage_unit[\\\"port\\\"] = 24007\\n storage_unit[\\\"node\\\"] = {\\n \\\"name\\\" : data[\\\"bricks\\\"][brick_idx].get(\\\"node\\\", \\\"\\\"),\\n \\\"id\\\" : data[\\\"bricks\\\"][brick_idx].get(\\\"node_id\\\", \\\"\\\")\\n }\\n\\n return client_data\",\n \"def test_return_spin_pipe_fail(self):\\n\\n # Try to get a spin from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')\",\n \"def test_assign_resources_to_tmc_subarray_in_mid():\",\n \"def genNumID(size):\\n\\tid = \\\"\\\"\\n\\tfor i in range(size):\\n\\t\\tid = id + selectRandomFromList(numTokens)\\n\\treturn id\",\n \"def test_brains_id_get(self):\\n pass\",\n \"def test_start_ids_10(self):\\n\\n\\t\\texpected_num_layers = 11\\n\\t\\texpected_ids = np.arange(10,21)\\n\\t\\t# test describe\\n\\t\\tdetails = self.watcher.describe(start_ids=10)\\n\\t\\tprint(\\\"start id = 10\\\", details)\\n\\t\\tactual_ids = details.layer_id.to_numpy().tolist()\\n\\t\\tself.assertTrue(np.array_equal(actual_ids, expected_ids))\\n\\t\\tself.assertEqual(len(expected_ids), expected_num_layers)\\n\\t\\t\\t\\t\\n\\t\\treturn\",\n \"def test_pol_id_range(self):\\n pol = '0~1'\\n ref_idx = []\\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def generate_run_id(self):\\n r_id_len = 4\\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\\n while r_id in self.cache:\\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\\n return r_id\",\n \"def create_test_sino_3d_tilted(A=9, Nx=22, Ny=22, max_phase=5.0,\\n ampl_range=(1.0, 1.0),\\n tilt_plane=0.0):\\n # initiate array\\n resar = np.zeros((A, Ny, Nx), dtype=np.complex128)\\n # 2pi coverage\\n angles = np.linspace(0, 2*np.pi, A, endpoint=False)\\n # x-values of Gaussain\\n x = np.linspace(-Nx/2, Nx/2, Nx, endpoint=True).reshape(1, -1)\\n y = np.linspace(-Ny/2, Ny/2, Ny, endpoint=True).reshape(-1, 1)\\n # SD of Gaussian\\n dev = min(np.sqrt(Nx/2), np.sqrt(Ny/2))\\n # Off-centered rotation about second axis:\\n off = Nx/7\\n for ii in range(A):\\n # Gaussian distribution sinogram\\n x0 = np.cos(angles[ii])*off\\n phase = np.exp(-(x-x0)**2/dev**2) * np.exp(-(y)**2/dev**2)\\n phase = normalize(phase, vmax=max_phase)\\n if ampl_range[0] == ampl_range[1]:\\n # constant amplitude\\n ampl = np.ones((Nx, Ny))*ampl_range[0]\\n else:\\n # ring\\n ampldev = dev/5\\n amploff = off*.3\\n ampl1 = np.exp(-(x-x0-amploff)**2/ampldev**2)\\n ampl2 = np.exp(-(x-x0+amploff)**2/ampldev**2)\\n ampl = ampl1+ampl2\\n ampl = normalize(ampl, vmin=ampl_range[0], vmax=ampl_range[1])\\n\\n # perform in-plane rotation\\n ampl = rotate(ampl, np.rad2deg(tilt_plane), reshape=False, cval=1)\\n phase = rotate(phase, np.rad2deg(tilt_plane), reshape=False, cval=0)\\n resar[ii] = ampl*np.exp(1j*phase)\\n\\n return resar, angles\",\n \"def generate_license_plate(self, num):\\n license_plate = []\\n for _ in range(num):\\n license_plate.append(self.fake.license_plate())\\n return license_plate\",\n \"def test_spin_loop_multiatom(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def test_CreateROI1(self):\\r\\n\\r\\n self.delayDisplay(\\\"Starting the test\\\")\\r\\n #\\r\\n # first, get some data\\r\\n #\\r\\n import urllib\\r\\n downloads = (\\r\\n ('http://slicer.kitware.com/midas3/download?items=5767', 'FA.nrrd', slicer.util.loadVolume),\\r\\n )\\r\\n\\r\\n for url,name,loader in downloads:\\r\\n filePath = slicer.app.temporaryPath + '/' + name\\r\\n if not os.path.exists(filePath) or os.stat(filePath).st_size == 0:\\r\\n logging.info('Requesting download %s from %s...\\\\n' % (name, url))\\r\\n urllib.urlretrieve(url, filePath)\\r\\n if loader:\\r\\n logging.info('Loading %s...' % (name,))\\r\\n loader(filePath)\\r\\n self.delayDisplay('Finished with download and loading')\\r\\n\\r\\n volumeNode = slicer.util.getNode(pattern=\\\"FA\\\")\\r\\n logic = CreateROILogic()\\r\\n self.assertIsNotNone( logic.hasImageData(volumeNode) )\\r\\n self.delayDisplay('Test passed!')\",\n \"def test_id(self):\\n b1 = Base()\\n self.assertEqual(b1.id, 1)\\n b2 = Base()\\n self.assertEqual(b2.id, 2)\\n b3 = Base(98)\\n self.assertEqual(b3.id, 98)\\n b4 = Base(256)\\n self.assertEqual(b4.id, 256)\\n b5 = Base()\\n self.assertEqual(b5.id, 3)\\n b6 = Base(-98)\\n self.assertEqual(b6.id, -98)\\n b7 = Base(None)\\n self.assertEqual(b7.id, 4)\\n b8 = Base(4.4)\\n self.assertEqual(b8.id, 4.4)\",\n \"def test_field_id_list(self):\\n field = '5,8'\\n ref_idx = [0,3]\\n self.res=self.run_task(infile=self.rawfile,field=field,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_residue_loop(self):\\n\\n # Loop over the residues.\\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\\n # Test the selection.\\n self.assertEqual(res.num, 2)\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)\",\n \"def test_api_random_id(api_client, single_brew_number):\\n response = api_client.get(path='/breweries' + '/' + str(single_brew_number))\\n assert response.json()['id'] == single_brew_number\",\n \"def _spin_sequence(self):\\n self.return_position = self.motor.position\\n \\n for spin_num in range(self.num_spins):\\n self.taxi()\\n\\n det_pre_acquire(self.detector)\\n self.fly()\\n det_post_acquire(self.detector)\\n\\n while self.detector.hdf1.write_file.value:\\n time.sleep(0.01) # wait for file to be written\\n\\n event = OrderedDict()\\n event[\\\"time\\\"] = time.time()\\n event[\\\"seq_num\\\"] = spin_num + 1\\n event[\\\"data\\\"] = {}\\n event[\\\"timestamps\\\"] = {}\\n for d_item in (self.detector.hdf1.full_file_name,):\\n d = d_item.read()\\n for k, v in d.items():\\n event['data'][k] = v['value']\\n event['timestamps'][k] = v['timestamp']\\n\\n self._data.append(event)\\n\\n self.set(\\\"Return\\\")\\n self._completion_status._finished(success=True)\",\n \"def test_generate_factoid():\\n generator = mockdata.generate_factoid()\\n for i in range(100):\\n factoid = next(generator)\\n assert factoid[\\\"@id\\\"] == \\\"Factoid %03d\\\" % (i + 1)\\n assert \\\"Person\\\" in factoid[\\\"person\\\"][\\\"@id\\\"]\\n assert \\\"Source\\\" in factoid[\\\"source\\\"][\\\"@id\\\"]\\n assert \\\"statement\\\" in factoid\\n assert factoid[\\\"statement\\\"][\\\"@id\\\"] == \\\"F%dS1\\\" % (i + 1)\",\n \"def test_test_ids_request(get_interface_params):\\n from sail_on_client.protocol.localinterface import LocalInterface\\n\\n config_directory, config_name = get_interface_params\\n data_dir = f\\\"{os.path.dirname(__file__)}/data\\\"\\n local_interface = LocalInterface(config_name, config_directory)\\n\\n assumptions_path = os.path.join(os.path.dirname(__file__), \\\"assumptions.json\\\")\\n filename = local_interface.test_ids_request(\\n \\\"OND\\\", \\\"image_classification\\\", \\\"5678\\\", assumptions_path\\n )\\n expected = os.path.join(data_dir, \\\"OND\\\", \\\"image_classification\\\", \\\"test_ids.csv\\\")\\n assert os.stat(expected).st_size > 5\\n assert expected == filename\",\n \"def test_004_init(self):\\n self.assertIsInstance(rawdata.rawdata(\\\"id\\\",testRawdata.ioc,testRawdata.sam),rawdata.rawdata)\",\n \"def test_ipam_rirs_create(self):\\n pass\",\n \"def test_id_get(mocker):\\n mocker.patch('serial.Serial.open')\\n mocker.patch('serial.Serial.flushInput')\\n css = mocker.patch('pysds011.driver.SDS011.cmd_set_sleep')\\n css.return_value = True\\n cfv = mocker.patch('pysds011.driver.SDS011.cmd_firmware_ver')\\n cfv.return_value = {'id': b'\\\\x12\\\\x34', 'paperino': 'maciomicio'}\\n runner = CliRunner()\\n result = runner.invoke(main, ['id'])\\n\\n calls = [call(0, id=b'\\\\xff\\\\xff'), call(1, id=b'\\\\xff\\\\xff')]\\n css.assert_has_calls(calls, any_order=False)\\n\\n assert '12' in result.output and '34' in result.output\\n assert result.exit_code == 0\",\n \"def test_post_cve_id_reserve_sequential_over_quota(reg_user_headers):\\n res = get_reserve_cve_ids(100001, utils.CURRENT_YEAR, reg_user_headers['CVE-API-ORG'])\\n assert res.status_code == 403\\n response_contains_json(res, 'error', 'EXCEEDED_ID_QUOTA')\",\n \"def next():\\n iraw = 0\\n run = 0\\n seqno = 0\\n with db_connection() as conn:\\n with conn.cursor() as curs:\\n try:\\n curs.execute(\\\"\\\"\\\"SELECT rawdata.id,rawdata.run,rawdata.seqno,\\n slices.block1,slices.block2,\\n jobs.cluster,jobs.process\\n FROM rawdata\\n LEFT JOIN bindings\\n ON bindings.iraw = rawdata.id\\n INNER JOIN slices\\n ON slices.iraw = rawdata.id\\n LEFT JOIN jobs\\n ON slices.ijob = jobs.id\\n AND jobs.exitcode = 0\\n WHERE bindings.id IS NULL\\n ORDER BY rawdata.id,slices.block1\\n LIMIT 2000;\\n \\\"\\\"\\\")\\n slices_missing = 1\\n for row in curs.fetchall():\\n i = int(row[0])\\n if i != iraw:\\n if slices_missing == 0:\\n break\\n else:\\n run = int(row[1])\\n seqno = int(row[2])\\n slices_missing = 0\\n slices = []\\n iraw = i\\n block1 = int(row[3])\\n block2 = int(row[4])\\n if row[5] is not None and row[6] is not None:\\n cluster = int(row[5])\\n process = int(row[6])\\n slices.append((block1,block2,cluster,process))\\n else:\\n print(\\\"slices missing on\\\", row[5], row[6])\\n slices_missing += 1\\n if slices_missing:\\n return 0\\n else:\\n curs.execute(\\\"SELECT TIMEZONE('GMT', NOW());\\\")\\n now = curs.fetchone()[0]\\n curs.execute(\\\"\\\"\\\"INSERT INTO bindings\\n (iraw,starttime)\\n VALUES (%s,%s)\\n RETURNING id;\\n \\\"\\\"\\\", (iraw, now))\\n row = curs.fetchone()\\n if row:\\n ibind = int(row[0])\\n else:\\n return 0\\n except:\\n iraw = 0\\n if iraw == 0:\\n time.sleep(random.randint(1,30))\\n return -9 # collision\\n\\n workdir = str(iraw)\\n os.mkdir(workdir)\\n os.chdir(workdir)\\n badslices = []\\n for sl in slices:\\n sdir = str(sl[0]) + \\\",\\\" + str(sl[1])\\n os.mkdir(sdir)\\n tarfile = \\\"job_{0}_{1}.tar.gz\\\".format(sl[2], sl[3])\\n tarpath = input_area + \\\"/\\\" + tarfile\\n try:\\n subprocess.check_output([\\\"gfal-copy\\\", src_url + tarpath,\\n \\\"file://\\\" + os.getcwd() + \\\"/\\\" + tarfile])\\n except:\\n sys.stderr.write(\\\"Error -999 on rawdata id {0}\\\".format(iraw) +\\n \\\" - job output \\\" + tarfile + \\\" is missing!\\\\n\\\")\\n sys.stderr.flush()\\n badslices.append(sdir)\\n continue\\n try:\\n subprocess.check_output([\\\"tar\\\", \\\"zxf\\\", tarfile, \\\"-C\\\", sdir])\\n except:\\n sys.stderr.write(\\\"Error -999 on rawdata id {0}\\\".format(iraw) +\\n \\\" - job output \\\" + tarfile + \\\" is not readable!\\\\n\\\")\\n sys.stderr.flush()\\n badslices.append(sdir)\\n finally:\\n os.remove(tarfile)\\n if len(badslices) > 0:\\n with db_connection() as conn:\\n with conn.cursor() as curs:\\n curs.execute(\\\"SELECT TIMEZONE('GMT', NOW());\\\")\\n now = curs.fetchone()[0]\\n curs.execute(\\\"\\\"\\\"UPDATE bindings\\n SET endtime=%s, \\n exitcode=%s,\\n details=%s\\n WHERE id = %s;\\n \\\"\\\"\\\", (now, -999, \\\":\\\".join(badslices), ibind))\\n os.chdir(\\\"..\\\")\\n shutil.rmtree(workdir)\\n return 1\\n\\n badslices += merge_evio_skims(run, seqno, slices)\\n badslices += merge_hddm_output(run, seqno, slices)\\n badslices += merge_job_info(run, seqno, slices)\\n badslices += merge_root_histos(run, seqno, slices)\\n exitcode = -len(badslices)\\n with db_connection() as comm:\\n with conn.cursor() as curs:\\n curs.execute(\\\"SELECT TIMEZONE('GMT', NOW());\\\")\\n now = curs.fetchone()[0]\\n curs.execute(\\\"\\\"\\\"UPDATE bindings\\n SET endtime=%s,\\n exitcode=%s,\\n details=%s\\n WHERE id = %s;\\n \\\"\\\"\\\", (now, exitcode, \\\":\\\".join(badslices), ibind))\\n os.chdir(\\\"..\\\")\\n shutil.rmtree(workdir)\\n return 1\",\n \"def get_ids(data, N_max):\\n\\n id_data = data[['molecule_name', 'id']].copy()\\n\\n # write molecules into one line\\n id_data = id_data.groupby('molecule_name').apply(lambda x:\\n x.values.reshape(-1))\\n\\n # pad with nans\\n id_list = []\\n for i in range(len(id_data)):\\n n = N_max*2 - len(id_data[i])\\n id_list.append(np.pad(id_data[i], (0, n), 'constant',\\n constant_values=(0, np.nan)))\\n\\n # build np array and remove molecule names\\n id_data = np.vstack(id_list)\\n del id_list\\n id_data = np.delete(id_data, [2*i for i in range(N_max)], 1)\\n\\n return id_data\",\n \"def test_generation_index_one(self):\\n generator = math_helpers.triangle_number_generator(1)\\n first_ten_triangle_numbers = [next(generator) for _ in range(10)]\\n canonical_values = [1, 3, 6, 10, 15, 21, 28, 36, 45, 55]\\n self.assertEqual(canonical_values, first_ten_triangle_numbers)\",\n \"def __test_gen_report_id_check():\\n # all fresh\\n report = dp.Report(md_block, md_block, md_block)\\n assert_report(report) # expected_id_count=5)\\n # 2 fresh\\n report = dp.Report(md_block, md_block_id, md_block)\\n assert_report(report) # expected_id_count=4)\\n # 0 fresh\\n report = dp.Report(md_block_id, dp.Text(\\\"test\\\", name=\\\"test-2\\\"))\\n assert_report(report) # expected_id_count=2)\",\n \"def data_gen(size, p):\\n #print(np.random.get_state()[1][0])\\n random_table = np.random.binomial(size = size, p = p, n = 1)\\n test_array = np.zeros((size, 2), dtype = int)\\n for i in range(size):\\n test_array[i,0] = i\\n test_array[i,1] = random_table[i]\\n return test_array\",\n \"def test_rand_func2(self):\\n for i in range(0, 100000):\\n num = random.randint(0, 32535143990)\\n func2_comp(num)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7930686","0.79260224","0.77357745","0.7663863","0.7659892","0.64280635","0.5991729","0.591287","0.5785646","0.5763235","0.5534429","0.5532555","0.5476528","0.5412773","0.5298371","0.528956","0.52654487","0.523596","0.52343017","0.5201792","0.5143447","0.5128533","0.51038617","0.509966","0.50971425","0.5095984","0.5095425","0.5093191","0.5071263","0.5064877","0.5061626","0.50599426","0.504783","0.504783","0.5047341","0.5034421","0.50337553","0.5015472","0.50149864","0.5007578","0.49980518","0.499089","0.49825752","0.4979093","0.497736","0.49599335","0.49433774","0.49330968","0.4923372","0.4922648","0.4918362","0.4910171","0.49011678","0.4896982","0.48925105","0.48814937","0.48756957","0.48730934","0.48679534","0.48634243","0.4855932","0.48545212","0.48531163","0.4850674","0.4849508","0.48468068","0.4841792","0.4841569","0.4836594","0.48365188","0.48286107","0.48270643","0.48262107","0.4821625","0.48126516","0.48121482","0.48073104","0.47970682","0.47964355","0.47938684","0.47916356","0.47875452","0.47870803","0.4786932","0.47865254","0.4776483","0.47735938","0.47637945","0.4758071","0.47550628","0.47522822","0.4750591","0.4735793","0.47347927","0.4733854","0.47327483","0.47312143","0.47308627","0.47283936","0.4722349"],"string":"[\n \"0.7930686\",\n \"0.79260224\",\n \"0.77357745\",\n \"0.7663863\",\n \"0.7659892\",\n \"0.64280635\",\n \"0.5991729\",\n \"0.591287\",\n \"0.5785646\",\n \"0.5763235\",\n \"0.5534429\",\n \"0.5532555\",\n \"0.5476528\",\n \"0.5412773\",\n \"0.5298371\",\n \"0.528956\",\n \"0.52654487\",\n \"0.523596\",\n \"0.52343017\",\n \"0.5201792\",\n \"0.5143447\",\n \"0.5128533\",\n \"0.51038617\",\n \"0.509966\",\n \"0.50971425\",\n \"0.5095984\",\n \"0.5095425\",\n \"0.5093191\",\n \"0.5071263\",\n \"0.5064877\",\n \"0.5061626\",\n \"0.50599426\",\n \"0.504783\",\n \"0.504783\",\n \"0.5047341\",\n \"0.5034421\",\n \"0.50337553\",\n \"0.5015472\",\n \"0.50149864\",\n \"0.5007578\",\n \"0.49980518\",\n \"0.499089\",\n \"0.49825752\",\n \"0.4979093\",\n \"0.497736\",\n \"0.49599335\",\n \"0.49433774\",\n \"0.49330968\",\n \"0.4923372\",\n \"0.4922648\",\n \"0.4918362\",\n \"0.4910171\",\n \"0.49011678\",\n \"0.4896982\",\n \"0.48925105\",\n \"0.48814937\",\n \"0.48756957\",\n \"0.48730934\",\n \"0.48679534\",\n \"0.48634243\",\n \"0.4855932\",\n \"0.48545212\",\n \"0.48531163\",\n \"0.4850674\",\n \"0.4849508\",\n \"0.48468068\",\n \"0.4841792\",\n \"0.4841569\",\n \"0.4836594\",\n \"0.48365188\",\n \"0.48286107\",\n \"0.48270643\",\n \"0.48262107\",\n \"0.4821625\",\n \"0.48126516\",\n \"0.48121482\",\n \"0.48073104\",\n \"0.47970682\",\n \"0.47964355\",\n \"0.47938684\",\n \"0.47916356\",\n \"0.47875452\",\n \"0.47870803\",\n \"0.4786932\",\n \"0.47865254\",\n \"0.4776483\",\n \"0.47735938\",\n \"0.47637945\",\n \"0.4758071\",\n \"0.47550628\",\n \"0.47522822\",\n \"0.4750591\",\n \"0.4735793\",\n \"0.47347927\",\n \"0.4733854\",\n \"0.47327483\",\n \"0.47312143\",\n \"0.47308627\",\n \"0.47283936\",\n \"0.4722349\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.79937476"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81486,"cells":{"query":{"kind":"string","value":"Fourth test of the spin ID generation function. The function tested is pipe_control.mol_res_spin.generate_spin_id_data_array()."},"document":{"kind":"string","value":"def test_generate_spin_id_data_array4(self):\n\n # The data.\n data = ['Ap4Aase', '1', 'GLY']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3)\n\n # Test the string.\n self.assertEqual(id, '#Ap4Aase:1')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_generate_spin_id_data_array6(self):\n\n # The data.\n data = ['1', 'GLY', None, None]\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')","def test_generate_spin_id_data_array1(self):\n\n # The data.\n data = ['1', 'GLY']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')","def test_generate_spin_id_data_array5(self):\n\n # The data.\n data = ['Ap4Aase', '1', 'GLY', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5)\n\n # Test the string.\n self.assertEqual(id, '#Ap4Aase:1@234')","def test_generate_spin_id_data_array2(self):\n\n # The data.\n data = ['1', 'GLY', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2, spin_num_col=3, spin_name_col=4)\n\n # Test the string.\n self.assertEqual(id, ':1@234')","def test_generate_spin_id_data_array3(self):\n\n # The data.\n data = ['Ap4Aase', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=None, res_name_col=None, spin_num_col=2, spin_name_col=3)\n\n # Test the string.\n self.assertEqual(id, '#Ap4Aase@234')","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def test_id_array(self):\n arr = vtk.vtkIdTypeArray()\n arr.SetNumberOfTuples(10)\n for i in range(10):\n arr.SetValue(i, i)\n\n np = array_handler.vtk2array(arr)\n self.assertEqual(numpy.all(np == range(10)), True)","def test_random_id(self):\r\n ids = \\\r\n \"R27DLI_4812 R27DLI_600 R27DLI_727 U1PLI_403 U1PLI_8969\".split(\r\n )\r\n assert random_id(ids, {}) in ids\r\n # just test we got something from the list, don't add stochastic test\r","def test_create_template(self):\n m_size = 10\n data = ecn.IDData(m_size)\n self.assertEqual(np.shape(data.ID_MATRIX), (m_size, m_size))\n self.assertEqual(sum(sum(data.ID_MATRIX)), m_size)\n self.assertTrue((sum(data.ID_MATRIX) == np.ones(m_size)).all())\n print('Finished testing template\\n')","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_spin_loop(self):\n\n # Spin data.\n select = [1, 0]\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, 'N5')\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 2)","def createArrayFunc(self):\r\n minVal = int(self.spinBoxMin_2.value())\r\n maxVal = int(self.spinBoxMax_2.value())\r\n arrayLength = int(self.spinBoxLength_2.value())\r\n different = maxVal - minVal\r\n if self.checkBoxNoRepeate_2.isChecked():\r\n if different > arrayLength:\r\n def unique_rand(initial, limit, total):\r\n data = []\r\n i = 0\r\n while i < total:\r\n number = numpy.random.randint(initial, limit)\r\n if number not in data:\r\n data.append(number)\r\n i += 1\r\n return data\r\n\r\n self.UnsortedArray_2 = unique_rand(minVal, maxVal, arrayLength)\r\n else:\r\n err = \"Array length must be greater than difference between limits\"\r\n self.labelUnsortedArray_2.setText(str(err))\r\n\r\n else:\r\n self.UnsortedArray_2 = numpy.random.randint(minVal, maxVal, arrayLength)\r\n self.labelUnsortedArray_2.setText(str(self.UnsortedArray_2))\r\n self.SortedArray_2 = Insertion.sorting(self.UnsortedArray_2)\r\n self.labelSortedArray_2.setText(str(self.SortedArray_2))\r\n binaryMax = int(self.spinBoxMax_2.value())\r\n binaryMin = int(self.spinBoxMin_2.value())\r\n self.spinBoxBinary.setMaximum(binaryMax)\r\n self.spinBoxBinary.setMinimum(binaryMin)\r\n self.spinBoxIthSmallest.setMaximum(arrayLength + 1)","def test_scan_id_list(self):\n scan = '15,17'\n ref_idx = [0,3]\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_arr2vtkIdList(self):\n a = [1, 2, 3, 4, 5]\n p = array_handler.array2vtkIdList(a)\n for i, j in enumerate(a): \n self.assertEqual(p.GetId(i), j)\n p = vtk.vtkIdList()\n ident = id(p)\n p = array_handler.array2vtkIdList(numpy.array(a), p)\n for i, j in enumerate(a): \n self.assertEqual(p.GetId(i), j)\n self.assertEqual(id(p), ident)\n \n self.assertRaises(AssertionError, array_handler.array2vtkIdList,\n [[1,2,3]])","def test_id_rot():\n assert_array_almost_equal(pr.R_id, pr.matrix_from_axis_angle(pr.a_id))\n assert_array_almost_equal(pr.R_id, pr.matrix_from_quaternion(pr.q_id))\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_xyz(pr.e_xyz_id))\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_zyx(pr.e_zyx_id))","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_pol_id_list(self):\n pol = '0,1'\n ref_idx = []\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_uuid():\n for _ in range(1000):\n uuid = uuid_generator()\n assert len(uuid) == 36\n assert uuid.count('-') == 4","def _apply_array_spin123(self,\n h1e: 'Nparray',\n h2e: 'Nparray',\n h3e: 'Nparray',\n dvec: Optional[Tuple['Nparray', 'Nparray']] = None,\n evec: Optional[Tuple['Nparray', 'Nparray', 'Nparray', 'Nparray']] \\\n = None) -> 'Nparray':\n norb = self.norb()\n assert h3e.shape == (norb * 2,) * 6\n assert not (dvec is None) ^ (evec is None)\n\n from1234 = (dvec is not None) and (evec is not None)\n\n nh1e = numpy.copy(h1e)\n nh2e = numpy.copy(h2e)\n\n for i in range(norb * 2):\n for j in range(norb * 2):\n for k in range(norb * 2):\n nh2e[j, k, :, :] += (-h3e[k, j, i, i, :, :] -\n h3e[j, i, k, i, :, :] -\n h3e[j, k, i, :, i, :])\n\n nh1e[:, :] += h3e[:, i, j, i, j, :]\n\n out = self._apply_array_spin12_halffilling(nh1e, nh2e)\n\n n = norb # This is just shorter\n if not from1234:\n symfac = 2.0\n axes = ((1, 3), (0, 1))\n (odveca, odvecb) = self.calculate_dvec_spin()\n dveca = numpy.zeros_like(odveca)\n dvecb = numpy.zeros_like(odvecb)\n\n for i in range(norb):\n for j in range(norb):\n evecaa, _ = self._calculate_dvec_spin_with_coeff(\n odveca[i, j, :, :])\n evecab, evecbb = self._calculate_dvec_spin_with_coeff(\n odvecb[i, j, :, :])\n\n dveca += numpy.tensordot(h3e[:n, :n, i, :n, :n, j],\n evecaa,\n axes=axes)\n dveca += numpy.tensordot(h3e[:n, :n, n + i, :n, :n, n + j],\n evecab,\n axes=axes) * symfac\n dveca += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\n evecbb,\n axes=axes)\n\n dvecb += numpy.tensordot(h3e[n:, :n, i, n:, :n, j],\n evecaa,\n axes=axes)\n dvecb += numpy.tensordot(h3e[n:, :n, n + i, n:, :n, n + j],\n evecab,\n axes=axes) * symfac\n dvecb += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\n evecbb,\n axes=axes)\n else:\n symfac = 1.0\n axes = ((1, 4, 2, 5), (0, 1, 2, 3)) # type: ignore\n dveca, dvecb = dvec # type: ignore\n evecaa, evecab, evecba, evecbb = evec # type: ignore\n\n dveca = numpy.tensordot(h3e[:n, :n, :n, :n, :n, :n],\n evecaa, axes=axes) \\\n + numpy.tensordot(h3e[:n, :n, n:, :n, :n, n:],\n evecab, axes=axes) * symfac \\\n + numpy.tensordot(h3e[:n, n:, n:, :n, n:, n:],\n evecbb, axes=axes) + \\\n + numpy.tensordot(h3e[:n, n:, :n, :n, n:, :n],\n evecba, axes=axes)\n\n dvecb = numpy.tensordot(h3e[n:, :n, :n, n:, :n, :n],\n evecaa, axes=axes) \\\n + numpy.tensordot(h3e[n:, :n, n:, n:, :n, n:],\n evecab, axes=axes) * symfac \\\n + numpy.tensordot(h3e[n:, n:, n:, n:, n:, n:],\n evecbb, axes=axes) + \\\n + numpy.tensordot(h3e[n:, n:, :n, n:, n:, :n],\n evecba, axes=axes)\n\n out -= self._calculate_coeff_spin_with_dvec((dveca, dvecb))\n return out","def test_get_ids(civic, main_data, updated_data):\n assert len(civic._get_ids(main_data['assertions'])) == 0\n assert len(civic._get_ids(main_data['variants'])) == 1\n assert len(civic._get_ids(main_data['genes'])) == 2\n assert len(civic._get_ids(main_data['evidence'])) == 1\n\n assert len(civic._get_ids(updated_data['assertions'])) == 1\n assert len(civic._get_ids(updated_data['variants'])) == 1\n assert len(civic._get_ids(updated_data['genes'])) == 1\n assert len(civic._get_ids(updated_data['evidence'])) == 1","def test_spin_loop_no_selection(self):\n\n # Spin data.\n select = [0, 1, 0, 0, 1, 1, 0, 1]\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 8)","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_scan_id_range(self):\n scan = '16~17'\n ref_idx = [1,2,3]\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_sampleId_pairs(self):\r\n # expected values\r\n dose_vps = \\\r\n [('1xDose', '2xDose'), ('1xDose', 'Control'),\r\n ('2xDose', 'Control')]\r\n ttd_vps = \\\r\n [('31', '21'), ('31', '55'), ('31', '67'), ('21', '55'),\r\n ('21', '67'), ('55', '67')]\r\n dose_sids = \\\r\n [(['Sam1', 'Sam2', 'Sam6'], ['Sam3', 'Sam4']),\r\n (['Sam1', 'Sam2', 'Sam6'], ['Sam5']),\r\n (['Sam3', 'Sam4'], ['Sam5'])]\r\n ttd_sids = \\\r\n [(['Sam1'], ['Sam3']),\r\n (['Sam1'], ['Sam4', 'Sam6']),\r\n (['Sam1'], ['Sam2', 'Sam5']),\r\n (['Sam3'], ['Sam4', 'Sam6']),\r\n (['Sam3'], ['Sam2', 'Sam5']),\r\n (['Sam4', 'Sam6'], ['Sam2', 'Sam5'])]\r\n\r\n # observed values\r\n obs_dose_sids, obs_dose_vps = sampleId_pairs(self.mapping_data,\r\n self.rarefaction_data, 'Dose')\r\n obs_ttd_sids, obs_ttd_vps = sampleId_pairs(self.mapping_data,\r\n self.rarefaction_data, 'TTD')\r\n\r\n # sort -- order is unimportant and depends on way presented in mf\r\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\r\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())\r\n self.assertEqual(ttd_vps.sort(), obs_ttd_vps.sort())\r\n self.assertEqual(ttd_sids.sort(), obs_ttd_sids.sort())\r\n\r\n # check errors when no samples had this category\r\n self.assertRaises(ValueError, sampleId_pairs, self.mapping_data,\r\n self.rarefaction_data, 'DNE')\r\n\r\n # check no error if map file has more sampleids than rarefaction data\r\n superset_mf = \\\r\n ['#SampleID\\tDose\\tLinkerPrimerSequence\\tWeight\\tTTD\\tDescription',\r\n '#Comment Line',\r\n 'Sam1\\t1xDose\\tATCG\\tHigh\\t31\\ts1_desc',\r\n 'Sam2\\t1xDose\\tACCG\\tLow\\t67\\ts2_desc',\r\n 'Sam3\\t2xDose\\tACGT\\tMed\\t21\\ts3_desc',\r\n 'Sam4\\t2xDose\\tAACG\\tLow\\t55\\ts4_desc',\r\n 'Sam5\\tControl\\tCGTC\\tLow\\t67\\ts5_desc',\r\n 'Sam6\\t1xDose\\tACCT\\tLow\\t55\\ts6_desc',\r\n 'Sam7\\t4xDose\\tACCT\\tLow\\t55\\ts7_desc',\r\n 'Sam8\\t3xDose\\tACCT\\tLow\\t55\\ts8_desc',\r\n 'Sam9\\t1xDose\\tACCT\\tLow\\t55\\ts9_desc']\r\n # (mf, comments)\r\n superset_mf = parse_mapping_file_to_dict(superset_mf)[0]\r\n obs_dose_sids, obs_dose_vps = sampleId_pairs(superset_mf,\r\n self.rarefaction_data, 'Dose')\r\n\r\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\r\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())","def test_weyl_specialize_id(self):\n a, b, c = 0.0, 0.0, 0.0\n for da, db, dc in DELTAS:\n for k1l, k1r, k2l, k2r in K1K2SB:\n k1 = np.kron(k1l.data, k1r.data)\n k2 = np.kron(k2l.data, k2r.data)\n self.check_two_qubit_weyl_specialization(\n k1 @ Ud(a + da, b + db, c + dc) @ k2,\n 0.999,\n TwoQubitWeylIdEquiv,\n {\"rz\": 4, \"ry\": 2},\n )","def test_split_id_otp(self):\n public_id, otp, = pyhsm.yubikey.split_id_otp(\"ft\" * 16)\n self.assertEqual(public_id, '')\n self.assertEqual(otp, \"ft\" * 16)\n\n public_id, otp, = pyhsm.yubikey.split_id_otp(\"cc\" + \"ft\" * 16)\n self.assertEqual(public_id, 'cc')\n self.assertEqual(otp, \"ft\" * 16)","def _get_rand_array(self):\n pass","def test_field_id_list(self):\n field = '5,8'\n ref_idx = [0,3]\n self.res=self.run_task(infile=self.rawfile,field=field,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def generate_new_ids(ids: np.array, n_required: int) -> np.array:\n\n current_max_id = ids.max()\n new_ids = np.arange(n_required) + current_max_id + 1\n\n return new_ids","def test_random_integers(self):\r\n # Check over two calls to see if the random state is correctly updated.\r\n random = RandomStreams(utt.fetch_seed())\r\n fn = function([], random.random_integers((20, 20), -5, 5))\r\n fn_val0 = fn()\r\n fn_val1 = fn()\r\n\r\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\r\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\r\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\r\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\r\n\r\n assert numpy.all(fn_val0 == numpy_val0)\r\n assert numpy.all(fn_val1 == numpy_val1)","def test_SampleIds(self):\r\n exp = [\"PC.354\", \"PC.355\", \"PC.356\", \"PC.481\", \"PC.593\", \"PC.607\",\r\n \"PC.634\", \"PC.635\", \"PC.636\"]\r\n obs = self.overview_map.SampleIds\r\n self.assertEqual(obs, exp)\r\n\r\n obs = self.no_metadata.SampleIds\r\n self.assertEqual(obs, exp)\r\n\r\n obs = self.empty_map.SampleIds\r\n self.assertEqual(obs, [])","def generate_T(number_obeservations):\n T = np.random.randint(0, 2, (number_obeservations,1))\n return T","def test_SampleIds(self):\n exp = [\"PC.354\", \"PC.355\", \"PC.356\", \"PC.481\", \"PC.593\", \"PC.607\",\n \"PC.634\", \"PC.635\", \"PC.636\"]\n obs = self.overview_map.SampleIds\n self.assertEqual(obs, exp)\n\n obs = self.no_metadata.SampleIds\n self.assertEqual(obs, exp)\n\n obs = self.empty_map.SampleIds\n self.assertEqual(obs, [])","def test_from_pdb_t4_n_residues(self):\n expected_n_residues = 164 # noqa\n raise NotImplementedError","def test_generate(self):\n cant_interations = int(random()*100)\n for i in range(cant_interations):\n number = self.sudoku.generate() # Generate number\n self.assertGreaterEqual(number, 0) # number >= 0\n self.assertLessEqual(number, 8) # number <= 8","def test_generateuuids(self):\n ret1 = {\"message\": \"No Random.org api key or api version found.\", \"res\": False}\n self.assertDictEqual(random_org.generateUUIDs(), ret1)\n\n ret2 = {\"message\": \"Required argument, number is missing.\", \"res\": False}\n self.assertDictEqual(\n random_org.generateUUIDs(api_key=\"peW\", api_version=\"1\"), ret2\n )\n\n ret3 = {\"message\": \"Number of UUIDs must be between 1 and 1000\", \"res\": False}\n self.assertDictEqual(\n random_org.generateUUIDs(api_key=\"peW\", api_version=\"1\", number=\"5\"), ret3\n )\n\n ret3 = {\"message\": \"Parameter 'apiKey' is malformed\", \"res\": False}\n self.assertDictEqual(\n random_org.generateUUIDs(api_key=\"peW\", api_version=\"1\", number=5), ret3\n )","def test_run_sim():\n rnd = rand.Arrivals(31, 40)\n sim.run_sim(2, 1, 3, 4, 24, rnd)","def test_if_array_is_good(self):\n testing_param = random.randint(1, 100)\n self.assertEqual(self.exercice.main(testing_param),\n list(range(2, testing_param+1, 2)))","def test_spin_type(get_pdos_generator_inputs):\n with pytest.raises(NotImplementedError):\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=spin_type)\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=SpinType.COLLINEAR)\n for namespace in [builder.scf, builder.nscf]:\n parameters = namespace['pw']['parameters'].get_dict()\n assert parameters['SYSTEM']['nspin'] == 2\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}","def get_test_split(self, fraction=0.1):\n rng = np.random.default_rng(42)\n test_size = int(round(len(self.all_asset_ids) * fraction))\n test_ids = rng.choice(self.all_asset_ids, size=test_size, replace=False)\n train_ids = [i for i in self.all_asset_ids if i not in test_ids]\n return train_ids, test_ids","def test_create_tornado_id(self):\n\n this_id_string = tornado_io.create_tornado_id(\n start_time_unix_sec=TORNADO_START_TIME_UNIX_SEC,\n start_latitude_deg=TORNADO_START_LATITUDE_DEG,\n start_longitude_deg=TORNADO_START_LONGITUDE_DEG)\n\n self.assertTrue(this_id_string == TORNADO_ID_STRING)","def test_residue_loop(self):\n\n # Loop over the residues.\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\n # Test the selection.\n self.assertEqual(res.num, 2)\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_run_sim_1():\n rnd = rand.Arrivals(36, 41)\n sim.run_sim(3, 2, 5, 6, 22, rnd)","def test_random_integers(self):\r\n # Check over two calls to see if the random state is correctly updated.\r\n m = Module()\r\n m.random = RandomStreams(utt.fetch_seed())\r\n m.fn = Method([], m.random.random_integers((20,20), -5, 5))\r\n\r\n made = m.make()\r\n made.random.initialize()\r\n fn_val0 = made.fn()\r\n fn_val1 = made.fn()\r\n\r\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\r\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\r\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\r\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\r\n\r\n assert numpy.all(fn_val0 == numpy_val0)\r\n assert numpy.all(fn_val1 == numpy_val1)","def myID() -> np.int:\r\n return 304976335","def myID() -> np.int:\r\n return 304976335","def test_pol_id_range(self):\n pol = '0~1'\n ref_idx = []\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def gen_data(min_coord, max_coord, size):\r\n data = np.random.randint(min_coord, max_coord, size)\r\n return data","def test_kf_id():\n\n for _ in range(1000):\n prefix = ''.join(random.sample(string.ascii_uppercase, 2))\n kf_id = kf_id_generator(prefix)()\n assert kf_id[:2] == prefix\n assert len(kf_id) == 11\n assert kf_id[2] == '_'\n\n assert 'I' not in kf_id[2:]\n assert 'L' not in kf_id[2:]\n assert 'O' not in kf_id[2:]\n assert 'U' not in kf_id[2:]\n\n assert re.search(r'^'+prefix+r'_[A-HJ-KM-NP-TV-Z0-9]{8}', kf_id)","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def genNumID(size):\n\tid = \"\"\n\tfor i in range(size):\n\t\tid = id + selectRandomFromList(numTokens)\n\treturn id","def generaterandomindices(dataSize, percentTest):\n\n TrainIndices = np.array([])\n while TrainIndices.__len__() < int(percentTest * dataSize):\n # Randomly select an index value and store it. If it has already been chosen, pick again.\n index = int(random.random() * dataSize)\n if not TrainIndices.__contains__(index):\n TrainIndices = np.append(TrainIndices, [index])\n\n # For aesthetic purposes:\n TrainIndices = np.sort(TrainIndices)\n\n return TrainIndices","def test_apply_ridit(self):\n x, x_rand, s = self.create_testdata()\n task = mmRDTR()\n s = task.check_sparse(s)\n\n for data in [x, x_rand, s]:\n #get ecdf for data\n Fn=task.make_ECDF(data)\n out=task.apply_ridit( data, Fn )\n # check same dimension\n self.assertEqual(np.all(data.shape==out.shape),True)\n # check mean almost equal to 0\n for i in range(data.shape[1]):\n self.assertEqual(round(out[:,i].mean(),8),0)\n # check if works with newdata\n newdata=data[:2]\n out=task.apply_ridit( newdata, Fn )\n # check same dimension\n self.assertEqual(np.all(newdata.shape==out.shape),True)","def test_returned_num_in_random_nums(self):\n self._setup_random_gen([1.], [42])\n self.assertEqual(self._random_gen.next_num(), 42)","def test_brains_id_get(self):\n pass","def test_arbitrary_rotation(self):\n \n # This test is run a bunch of times on various intervals, ranging from 50% to 1/6\n\t\t# (16.667%).\n for i in range(2, 7):\n \n interval = 1 / i # The amount to increase each qubit's probability by, relative to the previous qubit\n step_string = \"{:.4f}\".format(100 / i) # The decimal representation of the interval, as a percent\n target_probabilities = [0] * (i + 1) # This will store the desired probabilities of each qubit\n for j in range(0, i + 1):\n target_probability = j * interval\n target_probabilities[j] = target_probability\n\n # Run the test\n self.run_test(self.arbitrary_rotation_function, f\"Rotation with steps of 1/{i} ({step_string}%)\", 2000, target_probabilities, 0.05)","def test_scan_id_exprlist(self):\n scan = '15,>16'\n ref_idx = [0,3]\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def make_row(invalid_data=[]):\n\n ### Database Identifiers ###\n \n # phac_sample_id, valid/invalid error-grid information.\n phac_sample_id, phac_sample_id_error = lib.random_phac_id(invalid_data)\n # umbrella_bioproject_accession, valid/invalid error-grid information.\n ub_accession, ub_accession_error = lib.umbrella_bioproject_accession(invalid_data)\n # bioproject_accession, valid/invalid error-grid information.\n bp_accession, bp_accession_error = lib.random_bioproject_accession(invalid_data)\n # biosample_accession, valid/invalid error-grid information.\n bs_accession, bs_accession_error = lib.random_biosample_accession(invalid_data)\n # sra_accession, valid/invalid error-grid information.\n sra_accession, sra_accession_error = lib.random_sra_accession(invalid_data)\n # genbank_accession, valid/invalid error-grid information.\n gb_accession, gb_accession_error = lib.random_genbank_accession(invalid_data)\n # gisaid_accession, valid/invalid error-grid information.\n gisaid_accession, gisaid_accession_error = lib.random_gisaid_accession(invalid_data)\n \n ### Sample Collection and Processing ###\n \n # sample_collected_by, valid/invalid error-grid information.\n samp_col_by, samp_col_by_error = lib.random_agency(invalid_data)\n # sample_collector_contact_email, valid/invalid error-grid information.\n samp_col_email, samp_col_email_error = lib.random_email(invalid_data)\n # sample_collector_contact_address, valid/invalid error-grid information.\n samp_col_address, samp_col_address_error = lib.random_address(invalid_data)\n # sequence_submitter_contact_email, valid/invalid error-grid information.\n seq_sub_email, seq_sub_email_error = lib.random_email(invalid_data)\n # sequence_submitter_contact_address, valid/invalid error-grid information.\n seq_sub_address, seq_sub_address_error = lib.random_address(invalid_data)\n # sample_collection_date, valid/invalid error-grid information.\n samp_col_date, samp_col_date_error = lib.random_date(invalid_data)\n # sample_received_date, valid/invalid error-grid information.\n samp_rec_date, samp_rec_date_error = lib.random_date(invalid_data)\n # geo_loc_name_country, valid/invalid error-grid information.\n geo_loc_country, geo_loc_country_error = lib.random_country(invalid_data)\n # geo_loc_name_province_territory, valid/invalid error-grid information.\n geo_loc_prov_ter, geo_loc_prov_ter_error = lib.random_province_territory(invalid_data)\n # geo_loc_name_city, valid/invalid error-grid information.\n geo_loc_city, geo_loc_city_error = lib.random_city(invalid_data)\n # organism, valid/invalid error-grid information.\n organism, organism_error = lib.random_organism(invalid_data)\n # purpose_of_sampling, valid/invalid error-grid information.\n p_o_sampling, p_o_sampling_error = lib.random_purpose_of_sampling(invalid_data)\n # anatomical_material, valid/invalid error-grid information.\n anat_material, anat_material_error = lib.random_anatomical_material(invalid_data)\n # anatomical_part, valid/invalid error-grid information.\n anat_part, anat_part_error = lib.random_anatomical_part(invalid_data)\n # body_product, valid/invalid error-grid information.\n body_product, body_product_error = lib.random_body_product(invalid_data)\n # environmental_material, valid/invalid error-grid information.\n envi_material, envi_material_error = lib.random_environmental_material(invalid_data)\n # environmental_site, valid/invalid error-grid information.\n envi_site, envi_site_error = lib.random_environmental_site(invalid_data)\n # collection_device, valid/invalid error-grid information.\n col_device, col_device_error = lib.random_collection_device(invalid_data)\n # collection_method, valid/invalid error-grid information.\n col_method, col_method_error = lib.random_collection_method(invalid_data)\n # collection_protocol, valid/invalid error-grid information.\n col_protocol, col_protocol_error = lib.fake_protocol(invalid_data)\n # specimen_processing, valid/invalid error-grid information.\n spec_process, spec_process_error = lib.random_specimen_processing(invalid_data)\n # lab_host, valid/invalid error-grid information.\n lab_host, lab_host_error = lib.random_lab_host(invalid_data)\n # passage_number , valid/invalid error-grid information.\n passage_num, passage_num_error = lib.random_passage_number(invalid_data)\n # passage_method, valid/invalid error-grid information.\n passage_method, passage_method_error = lib.passage_method_text(invalid_data)\n # biomaterial_extracted, valid/invalid error-grid information.\n biom_extract, biom_extract_error = lib.random_biomaterial_extracted(invalid_data)\n \n ### Host Information ###\n \n # host_common_name, valid/invalid error-grid information.\n host_com_name, host_com_name_error = lib.random_host_common_name(invalid_data)\n # host_scientific_name, valid/invalid error-grid information.\n host_sci_name, host_sci_name_error = lib.random_host_scientific_name(invalid_data)\n # host_health_state, valid/invalid error-grid information.\n host_health_state, host_health_state_error = lib.random_host_health_state(invalid_data)\n # host_health_status_details, valid/invalid error-grid information.\n host_health_status, host_health_status_error = lib.random_host_health_status_details(invalid_data)\n # host_disease, valid/invalid error-grid information.\n host_disease, host_disease_error = lib.random_host_disease(invalid_data)\n # host_age, valid/invalid error-grid information.\n host_age, host_age_error = lib.random_host_age(invalid_data)\n # host_gender, valid/invalid error-grid information.\n host_gender, host_gender_error = lib.random_host_gender(invalid_data)\n # host_origin_geo_loc_name_country, valid/invalid error-grid information.\n host_loc_country, host_loc_country_error = lib.random_country(invalid_data)\n # host_subject_id, valid/invalid error-grid information.\n host_sub_id, host_sub_id_error = lib.random_host_subject_id(invalid_data)\n # symptom_onset_date, valid/invalid error-grid information.\n symp_onset_date, symp_onset_date_error = lib.random_date(invalid_data)\n # signs_and_symptoms, valid/invalid error-grid information.\n signs_symptoms, signs_symptoms_error = lib.random_signs_symptoms(invalid_data)\n \n ### Host Exposure Information ###\n \n # location_of_exposure_geo_loc_name_country, valid/invalid error-grid information.\n loc_exp_country, loc_exp_country_error = lib.random_country(invalid_data)\n # travel_history, valid/invalid error-grid information. \n trav_history, trav_history_error = lib.random_travel_history(invalid_data)\n # exposure_event, valid/invalid error-grid information.\n exp_event, exp_event_error = lib.random_exposure_event(invalid_data)\n \n ### Sequencing ###\n \n # minion_barcode, valid/invalid error-grid information.\n minion_barcode, minion_barcode_error = lib.random_minIon_barcode(invalid_data)\n # sequencing_instrument, valid/invalid error-grid information.\n seq_instrument, seq_instrument_error = lib.random_seq_instrument(invalid_data)\n # sequencing_protocol_name, valid/invalid error-grid information.\n seq_prot_name, seq_prot_name_error = lib.fake_protocol(invalid_data)\n # sequencing_protocol_source, valid/invalid error-grid information.\n seq_prot_source, seq_prot_source_error = lib.random_seq_protocol_source(invalid_data)\n # sequencing_kit_number, valid/invalid error-grid information.\n seq_kit_num, seq_kit_num_error = lib.random_seq_kit_num(invalid_data)\n # amplicon_pcr_primers_filename, valid/invalid error-grid information.\n amp_pcr_filename, amp_pcr_filename_error = lib.random_txt_filename(invalid_data)\n \n ### Bioinformatics and QC metrics ###\n \n # raw_sequence_data_processing, valid/invalid error-grid information.\n raw_seq_process, raw_seq_process_error = lib.random_seq_process(invalid_data)\n # sequencing_depth_average, valid/invalid error-grid information.\n seq_depth_avg, seq_depth_avg_error = lib.random_seq_depth(invalid_data)\n # assembly_method, valid/invalid error-grid information.\n assemb_method, assemb_method_error = lib.random_assembly_software(invalid_data)\n # assembly_coverage_breadth, valid/invalid error-grid information.\n assemb_cov_breadth, assemb_cov_breadth_error = lib.random_assembly_coverage_breadth(invalid_data)\n # assembly_coverage_depth, valid/invalid error-grid information.\n assemb_cov_depth, assemb_cov_depth_error = lib.random_seq_depth(invalid_data)\n # r1_fastq_filename, valid/invalid error-grid information.\n r1_filename, r1_filename_error = lib.random_fastq_filename(invalid_data)\n # r2_fastq_filename, valid/invalid error-grid information.\n r2_filename, r2_filename_error = lib.random_fastq_filename(invalid_data)\n # r1_fastq_filepath, valid/invalid error-grid information.\n r1_filepath, r1_filepath_error = lib.random_filepath(r1_filename, invalid_data)\n # r2_fastq_filepath, valid/invalid error-grid information.\n r2_filepath, r2_filepath_error = lib.random_filepath(r2_filename, invalid_data)\n # fast5_filename, valid/invalid error-grid information.\n fast5_filename, fast5_filename_error = lib.random_fast5_filename(invalid_data)\n # fast5_filepath, valid/invalid error-grid information.\n fast5_filepath, fast5_filepath_error = lib.random_filepath(fast5_filename, invalid_data)\n # fasta_filename, valid/invalid error-grid information.\n fasta_filename, fasta_filename_error = lib.random_fasta_filename(invalid_data)\n # fasta_filepath, valid/invalid error-grid information.\n fasta_filepath, fasta_filepath_error = lib.random_filepath(fasta_filename, invalid_data)\n # number_base_pairs, valid/invalid error-grid information.\n num_bp, num_bp_error = lib.random_bp_num(invalid_data)\n # consensus_genome_length, valid/invalid error-grid information.\n cons_genome_len, cons_genome_len_error = lib.random_genome_length(invalid_data)\n # mean_contig_length, valid/invalid error-grid information.\n mean_contig_len, mean_contig_len_error = lib.random_contig_length(invalid_data)\n # n50, valid/invalid error-grid information.\n n50, n50_error = lib.random_n50(invalid_data)\n # ns_per_100_kbp, valid/invalid error-grid information.\n ns_100kbp, ns_100kbp_error = lib.random_ns_100kbp(invalid_data)\n # reference_genome_accession, valid/invalid error-grid information.\n ref_genome_accession, ref_genome_accession_error = lib.random_ref_genome(invalid_data)\n # consensus_sequence_id, valid/invalid error-grid information.\n cons_seq_id, cons_seq_id_error = lib.random_consensus_seq_id(invalid_data)\n # consensus_sequence_method, valid/invalid error-grid information.\n cons_seq_method, cons_seq_method_error = lib.random_consensus_seq_method(invalid_data)\n # consensus_sequence_filename, valid/invalid error-grid information.\n cons_seq_filename, cons_seq_filename_error = lib.random_fasta_filename(invalid_data)\n # consensus_sequence_filepath, valid/invalid error-grid information.\n cons_seq_filepath, cons_seq_filepath_error = lib.random_filepath(cons_seq_filename, invalid_data)\n # annotation_feature_table_filename, valid/invalid error-grid information.\n annot_table_filename, annot_table_filename_error = lib.random_feature_table_filename(invalid_data)\n # bioinformatics_protocol, valid/invalid error-grid information.\n biof_protocol, biof_protocol_error = lib.bioinformatics_protocol(invalid_data)\n \n ### Pathogen Diagnostic Testing ###\n \n # gene_name_1, valid/invalid error-grid information.\n gene_1, gene_1_error = lib.random_gene(invalid_data)\n # diagnostic_pcr_protocol_1, valid/invalid error-grid information.\n pcr_protocol_1, pcr_protocol_1_error = lib.fake_protocol(invalid_data)\n # diagnostic_pcr_ct_value_1, valid/invalid error-grid information.\n pcr_ct_1, pcr_ct_1_error = lib.random_pcr_ct_val(invalid_data)\n # gene_name_2, valid/invalid error-grid information.\n gene_2, gene_2_error = lib.random_gene(invalid_data)\n # diagnostic_pcr_protocol_2, valid/invalid error-grid information.\n pcr_protocol_2, pcr_protocol_2_error = lib.fake_protocol(invalid_data)\n # diagnostic_pcr_ct_value_2, valid/invalid error-grid information.\n pcr_ct_2, pcr_ct_2_error = lib.random_pcr_ct_val(invalid_data)\n \n ### Contributor Acknowledgement ###\n \n # authors, valid/invalid error-grid information.\n authors, authors_error = lib.authors(invalid_data)\n \n ### Dependent IDs ###\n \n # specimen_collector_sample_id.\n spec_col_sample_id, spec_col_sample_id_error = lib.random_specimen_collector_sample_id(\n geo_loc_country, \n geo_loc_prov_ter,\n geo_loc_city,\n invalid_data)\n # irida_sample_name.\n irida_sample_id = spec_col_sample_id\n # sequence_submitted_by.\n seq_sub_by = samp_col_by\n # library_id, valid/invalid error-grid information.\n library_id, library_id_error = lib.random_library_id(spec_col_sample_id, invalid_data)\n # isolate.\n isolate = spec_col_sample_id\n # assembly_name, valid/invalid error-grid information.\n assemb_name, assemb_name_error = lib.random_assembly_name(spec_col_sample_id, invalid_data)\n\n # Row of generated data organised by column.\n cols = [spec_col_sample_id,\n phac_sample_id,\n irida_sample_id,\n ub_accession,\n bp_accession,\n bs_accession,\n sra_accession,\n gb_accession,\n gisaid_accession,\n samp_col_by,\n samp_col_email,\n samp_col_address,\n seq_sub_by,\n seq_sub_email,\n seq_sub_address,\n samp_col_date,\n samp_rec_date,\n geo_loc_country,\n geo_loc_prov_ter,\n geo_loc_city,\n organism,\n isolate,\n p_o_sampling,\n anat_material,\n anat_part,\n body_product,\n envi_material,\n envi_site,\n col_device,\n col_method,\n col_protocol,\n spec_process,\n lab_host,\n passage_num,\n passage_method,\n biom_extract,\n host_com_name,\n host_sci_name,\n host_health_state,\n host_health_status,\n host_disease,\n host_age,\n host_gender,\n host_loc_country,\n host_sub_id,\n symp_onset_date,\n signs_symptoms,\n loc_exp_country,\n trav_history,\n exp_event,\n library_id,\n minion_barcode,\n seq_instrument,\n seq_prot_name,\n seq_prot_source,\n seq_kit_num,\n amp_pcr_filename,\n raw_seq_process,\n seq_depth_avg,\n assemb_name,\n assemb_method,\n assemb_cov_breadth,\n assemb_cov_depth,\n r1_filename,\n r2_filename,\n r1_filepath,\n r2_filepath,\n fast5_filename,\n fast5_filepath,\n fasta_filename,\n fasta_filepath,\n num_bp,\n cons_genome_len,\n mean_contig_len,\n n50,\n ns_100kbp,\n ref_genome_accession,\n cons_seq_id,\n cons_seq_method,\n cons_seq_filename,\n cons_seq_filepath,\n annot_table_filename,\n biof_protocol,\n gene_1,\n pcr_protocol_1,\n pcr_ct_1,\n gene_2,\n pcr_protocol_2,\n pcr_ct_2,\n authors]\n\n # Error grid valid/invalid (error specific) information.\n grid = ['-', # spec_col_sample_id_error placeholder\n phac_sample_id_error,\n '-', # irida_sample_id_error placeholder\n ub_accession_error,\n bp_accession_error,\n bs_accession_error,\n sra_accession_error,\n gb_accession_error,\n gisaid_accession_error,\n samp_col_by_error,\n samp_col_email_error,\n samp_col_address_error,\n '-', # seq_sub_by_error placeholder\n seq_sub_email_error,\n seq_sub_address_error,\n samp_col_date_error,\n samp_rec_date_error,\n geo_loc_country_error,\n geo_loc_prov_ter_error,\n geo_loc_city_error,\n organism_error,\n '-', # isolate_error placeholder\n p_o_sampling_error,\n anat_material_error,\n anat_part_error,\n body_product_error,\n envi_material_error,\n envi_site_error,\n col_device_error,\n col_method_error,\n col_protocol_error,\n spec_process_error,\n lab_host_error,\n passage_num_error,\n passage_method_error,\n biom_extract_error,\n host_com_name_error,\n host_sci_name_error,\n host_health_state_error,\n host_health_status_error,\n host_disease_error,\n host_age_error,\n host_gender_error,\n host_loc_country_error,\n host_sub_id_error,\n symp_onset_date_error,\n signs_symptoms_error,\n loc_exp_country_error,\n trav_history_error,\n exp_event_error,\n library_id_error,\n minion_barcode_error,\n seq_instrument_error,\n seq_prot_name_error,\n seq_prot_source_error,\n seq_kit_num_error,\n amp_pcr_filename_error,\n raw_seq_process_error,\n seq_depth_avg_error,\n assemb_name_error,\n assemb_method_error,\n assemb_cov_breadth_error,\n assemb_cov_depth_error,\n r1_filename_error,\n r2_filename_error,\n r1_filepath_error,\n r2_filepath_error,\n fast5_filename_error,\n fast5_filepath_error,\n fasta_filename_error,\n fasta_filepath_error,\n num_bp_error,\n cons_genome_len_error,\n mean_contig_len_error,\n n50_error,\n ns_100kbp_error,\n ref_genome_accession_error,\n cons_seq_id_error,\n cons_seq_method_error,\n cons_seq_filename_error,\n cons_seq_filepath_error,\n annot_table_filename_error,\n biof_protocol_error,\n gene_1_error,\n pcr_protocol_1_error,\n pcr_ct_1_error,\n gene_2_error,\n pcr_protocol_2_error,\n pcr_ct_2_error,\n authors_error]\n\n # return row of data for data file and row of data validity for error grid.\n return cols, grid","def test_resisc45():\n if not os.path.isdir(os.path.join(DATASET_DIR, \"resisc45_split\", \"3.0.0\")):\n pytest.skip(\"resisc45_split dataset not locally available.\")\n\n for split, size in [(\"train\", 22500), (\"validation\", 4500), (\"test\", 4500)]:\n batch_size = 16\n epochs = 1\n dataset = datasets.resisc45(\n split=split, epochs=epochs, batch_size=batch_size, dataset_dir=DATASET_DIR,\n )\n assert dataset.size == size\n assert dataset.batch_size == batch_size\n assert dataset.batches_per_epoch == (\n size // batch_size + bool(size % batch_size)\n )\n\n x, y = dataset.get_batch()\n assert x.shape == (batch_size, 256, 256, 3)\n assert y.shape == (batch_size,)","def test_get_sample_ids(self):\n obs = self.tester._get_sample_ids(self.conn_handler)\n self.assertEqual(obs, self.exp_sample_ids)","def test_get_sample_ids(self):\n obs = self.tester._get_sample_ids(self.conn_handler)\n self.assertEqual(obs, self.exp_sample_ids)","def test_get_data_array():\n test_file = os.path.join(DATA_PATH, \"paper_test_file.uvh5\")\n test_uv = UVData()\n test_uv.read(test_file)\n\n baseline_array = np.array(list(set(test_uv.baseline_array)))\n data_array = utils.get_data_array(test_uv, reds=baseline_array)\n\n compare_data = np.zeros(\n (test_uv.Npols, test_uv.Nbls, test_uv.Ntimes, test_uv.Nfreqs),\n dtype=np.complex64,\n )\n\n pol_array = uvutils.polnum2str(test_uv.polarization_array)\n for pol_cnt, pol in enumerate(pol_array):\n for cnt, baseline in enumerate(list(set(test_uv.baseline_array))):\n ant_1, ant_2 = test_uv.baseline_to_antnums(baseline)\n compare_data[pol_cnt, cnt] = test_uv.get_data(ant_1, ant_2, pol)\n\n compare_data = compare_data.squeeze(axis=0)\n assert np.allclose(compare_data, data_array)","def test1():\n for test in pkl.load(open(TEST_RESOURCES_DIR / \"regression_vault.pkl\", \"rb\"))[:5]:\n init_dict, rslt = test\n np.testing.assert_array_equal(run_regression_test(init_dict), rslt)","def generate_raiz():\n\treturn os.urandom(12)","def _generate_id() -> str:\n return \"\".join(sample(\"abcdefghjkmopqrstuvqxyz\", 16))","def test_test_ids_request(get_interface_params):\n from sail_on_client.protocol.localinterface import LocalInterface\n\n config_directory, config_name = get_interface_params\n data_dir = f\"{os.path.dirname(__file__)}/data\"\n local_interface = LocalInterface(config_name, config_directory)\n\n assumptions_path = os.path.join(os.path.dirname(__file__), \"assumptions.json\")\n filename = local_interface.test_ids_request(\n \"OND\", \"image_classification\", \"5678\", assumptions_path\n )\n expected = os.path.join(data_dir, \"OND\", \"image_classification\", \"test_ids.csv\")\n assert os.stat(expected).st_size > 5\n assert expected == filename","def test_main(data, tmp_path):\n\n main(data, tmp_path)\n\n FILES = (\n \"gd32f888x(0-1)xx-pinctrl.h\",\n \"gd32f888x(2-3)xx-pinctrl.h\",\n \"gd32f888y(0-1)xx-pinctrl.h\",\n \"gd32f999x(0-1)xx-pinctrl.h\",\n \"gd32f999x(2-3)xx-pinctrl.h\",\n \"gd32f999y(0-1)xx-pinctrl.h\",\n )\n\n for file in FILES:\n ref_file = data / file\n gen_file = tmp_path / file\n\n assert gen_file.exists()\n\n with open(ref_file) as ref, open(gen_file) as gen:\n assert ref.read() == gen.read()","def test_spin_type(fixture_code, generate_structure):\n code = fixture_code('quantumespresso.pw')\n structure = generate_structure()\n\n with pytest.raises(NotImplementedError):\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\n PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=spin_type)\n\n builder = PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=SpinType.COLLINEAR)\n\n for namespace in [builder.relax['base'], builder.scf, builder.bands]:\n parameters = namespace['pw']['parameters'].get_dict()\n assert parameters['SYSTEM']['nspin'] == 2\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}","def _spin_sequence(self):\n self.return_position = self.motor.position\n \n for spin_num in range(self.num_spins):\n self.taxi()\n\n det_pre_acquire(self.detector)\n self.fly()\n det_post_acquire(self.detector)\n\n while self.detector.hdf1.write_file.value:\n time.sleep(0.01) # wait for file to be written\n\n event = OrderedDict()\n event[\"time\"] = time.time()\n event[\"seq_num\"] = spin_num + 1\n event[\"data\"] = {}\n event[\"timestamps\"] = {}\n for d_item in (self.detector.hdf1.full_file_name,):\n d = d_item.read()\n for k, v in d.items():\n event['data'][k] = v['value']\n event['timestamps'][k] = v['timestamp']\n\n self._data.append(event)\n\n self.set(\"Return\")\n self._completion_status._finished(success=True)","def test_ids(self):\n # AdapterID inherited from IOAdapter\n self.assertEqual('553713696', self.sriovs[0].id)\n self.assertEqual(1, self.sriovs[0].sriov_adap_id)\n\n self.assertEqual('553713680', self.sriovs[2].id)\n self.assertIsNone(self.sriovs[2].sriov_adap_id)","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def generate_fake_data(t0, num_array, period=5820, data_range=[0.0, 24.0],\n cyclic=True):\n\n if cyclic:\n uts_root = np.mod(t0, period)\n data = (np.mod(uts_root + num_array, period)\n * (np.diff(data_range)[0] / np.float64(period))) + data_range[0]\n else:\n data = ((t0 + num_array) / period).astype(int)\n\n return data","def generate_synth_data(n):","def test_random_generator(self):\n gen = random_data()\n data = [next(gen) for _ in range(100)]\n self.assertEqual(len(data), 100)","def test_return_residue(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_residue(':1')\n res2 = mol_res_spin.return_residue(selection=':2')\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\n\n # Test the data of residue 1.\n self.assertEqual(res1.num, 1)\n self.assertEqual(res1.name, None)\n\n # Test the data of residue 2.\n self.assertEqual(res2.num, 2)\n self.assertEqual(res2.name, 'Glu')\n\n # Test the data of residue 4.\n self.assertEqual(res4.num, 4)\n self.assertEqual(res4.name, 'Pro')\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5.num, -5)\n self.assertEqual(res5.name, None)\n self.assertEqual(res5.spin[1].name, 'N5')","def test_generate_factoid():\n generator = mockdata.generate_factoid()\n for i in range(100):\n factoid = next(generator)\n assert factoid[\"@id\"] == \"Factoid %03d\" % (i + 1)\n assert \"Person\" in factoid[\"person\"][\"@id\"]\n assert \"Source\" in factoid[\"source\"][\"@id\"]\n assert \"statement\" in factoid\n assert factoid[\"statement\"][\"@id\"] == \"F%dS1\" % (i + 1)","def test_field_id_range(self):\n field = '6~8'\n ref_idx = [1,2,3]\n self.res=self.run_task(infile=self.rawfile,field=field,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_start_ids_10(self):\n\n\t\texpected_num_layers = 11\n\t\texpected_ids = np.arange(10,21)\n\t\t# test describe\n\t\tdetails = self.watcher.describe(start_ids=10)\n\t\tprint(\"start id = 10\", details)\n\t\tactual_ids = details.layer_id.to_numpy().tolist()\n\t\tself.assertTrue(np.array_equal(actual_ids, expected_ids))\n\t\tself.assertEqual(len(expected_ids), expected_num_layers)\n\t\t\t\t\n\t\treturn","def data_gen(size, p):\n #print(np.random.get_state()[1][0])\n random_table = np.random.binomial(size = size, p = p, n = 1)\n test_array = np.zeros((size, 2), dtype = int)\n for i in range(size):\n test_array[i,0] = i\n test_array[i,1] = random_table[i]\n return test_array","def test_get_sample_ids(self):\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\n parse_metadata_state_descriptions('Study:Twin')), [])\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\n parse_metadata_state_descriptions('Study:Dog')), ['a','b'])\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\n parse_metadata_state_descriptions('Study:*,!Dog')), ['c','d','e'])\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\n parse_metadata_state_descriptions('Study:*,!Dog;BodySite:Stool')), ['e'])\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\n parse_metadata_state_descriptions('BodySite:Stool')), ['a','b','e'])","def test_get_sample_ids(self):\r\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\r\n parse_metadata_state_descriptions('Study:Twin')), [])\r\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\r\n parse_metadata_state_descriptions('Study:Dog')), ['a', 'b'])\r\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\r\n parse_metadata_state_descriptions('Study:*,!Dog')), ['c', 'd', 'e'])\r\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\r\n parse_metadata_state_descriptions('Study:*,!Dog;BodySite:Stool')), ['e'])\r\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\r\n parse_metadata_state_descriptions('BodySite:Stool')), ['a', 'b', 'e'])","def test_id(self):\n b1 = Base()\n self.assertEqual(b1.id, 1)\n b2 = Base()\n self.assertEqual(b2.id, 2)\n b3 = Base(98)\n self.assertEqual(b3.id, 98)\n b4 = Base(256)\n self.assertEqual(b4.id, 256)\n b5 = Base()\n self.assertEqual(b5.id, 3)\n b6 = Base(-98)\n self.assertEqual(b6.id, -98)\n b7 = Base(None)\n self.assertEqual(b7.id, 4)\n b8 = Base(4.4)\n self.assertEqual(b8.id, 4.4)","def __test_gen_report_id_check():\n # all fresh\n report = dp.Report(md_block, md_block, md_block)\n assert_report(report) # expected_id_count=5)\n # 2 fresh\n report = dp.Report(md_block, md_block_id, md_block)\n assert_report(report) # expected_id_count=4)\n # 0 fresh\n report = dp.Report(md_block_id, dp.Text(\"test\", name=\"test-2\"))\n assert_report(report) # expected_id_count=2)","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_spin_loop_wildcard(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N*'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def random_lottery():\n\treturn 0","def test_get_tid():\n tids = []\n def _foo():\n mytid = yield GetTid()\n tids.append(mytid)\n for i in range(5):\n yield i\n\n scheduler = Scheduler()\n scheduler.new(_foo())\n scheduler.new(_foo())\n scheduler.mainloop()\n\n # can we do better than hard code?\n assert tids == [4, 5]","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def _apply_array_spin1234(self, h1e: 'Nparray', h2e: 'Nparray',\n h3e: 'Nparray', h4e: 'Nparray') -> 'Nparray':\n norb = self.norb()\n tno = 2 * norb\n assert h4e.shape == (tno, tno, tno, tno, tno, tno, tno, tno)\n lena = self.lena()\n lenb = self.lenb()\n\n nh1e = numpy.copy(h1e)\n nh2e = numpy.copy(h2e)\n nh3e = numpy.copy(h3e)\n\n if fqe.settings.use_accelerated_code:\n _make_nh123(norb, h4e, nh1e, nh2e, nh3e)\n else:\n for i in range(norb * 2):\n for j in range(norb * 2):\n for k in range(norb * 2):\n nh1e[:, :] -= h4e[:, j, i, k, j, i, k, :]\n for l in range(norb * 2):\n nh2e[i, j, :, :] += (h4e[j, l, i, k, l, k, :, :] +\n h4e[i, j, l, k, l, k, :, :] +\n h4e[i, l, k, j, l, k, :, :] +\n h4e[j, i, k, l, l, k, :, :] +\n h4e[i, k, j, l, k, :, l, :] +\n h4e[j, i, k, l, k, :, l, :] +\n h4e[i, j, k, l, :, k, l, :])\n nh3e[i, j, k, :, :, :] += (\n h4e[k, i, j, l, l, :, :, :] +\n h4e[j, i, l, k, l, :, :, :] +\n h4e[i, l, j, k, l, :, :, :] +\n h4e[i, k, j, l, :, l, :, :] +\n h4e[i, j, l, k, :, l, :, :] +\n h4e[i, j, k, l, :, :, l, :])\n\n (dveca, dvecb) = self.calculate_dvec_spin()\n evecaa = numpy.zeros((norb, norb, norb, norb, lena, lenb),\n dtype=self._dtype)\n evecab = numpy.zeros((norb, norb, norb, norb, lena, lenb),\n dtype=self._dtype)\n evecba = numpy.zeros((norb, norb, norb, norb, lena, lenb),\n dtype=self._dtype)\n evecbb = numpy.zeros((norb, norb, norb, norb, lena, lenb),\n dtype=self._dtype)\n for i in range(norb):\n for j in range(norb):\n tmp = self._calculate_dvec_spin_with_coeff(dveca[i, j, :, :])\n evecaa[:, :, i, j, :, :] = tmp[0][:, :, :, :]\n evecba[:, :, i, j, :, :] = tmp[1][:, :, :, :]\n\n tmp = self._calculate_dvec_spin_with_coeff(dvecb[i, j, :, :])\n evecab[:, :, i, j, :, :] = tmp[0][:, :, :, :]\n evecbb[:, :, i, j, :, :] = tmp[1][:, :, :, :]\n\n out = self._apply_array_spin123(nh1e, nh2e, nh3e, (dveca, dvecb),\n (evecaa, evecab, evecba, evecbb))\n\n def ncon(A, B):\n \"\"\"Tensor contraction and transposition corresponding with\n einsum 'ikmojlnp,mnopxy->ijklxy'\n \"\"\"\n return numpy.transpose(numpy.tensordot(A,\n B,\n axes=((2, 6, 3, 7), (0, 1, 2,\n 3))),\n axes=(0, 2, 1, 3, 4, 5))\n\n n = norb # shorter\n nevecaa = ncon(h4e[:n, :n, :n, :n, :n, :n, :n, :n], evecaa) \\\n + 2.0 * ncon(h4e[:n, :n, :n, n:, :n, :n, :n, n:], evecab) \\\n + ncon(h4e[:n, :n, n:, n:, :n, :n, n:, n:], evecbb)\n\n nevecab = ncon(h4e[:n, n:, :n, :n, :n, n:, :n, :n], evecaa) \\\n + 2.0 * ncon(h4e[:n, n:, :n, n:, :n, n:, :n, n:], evecab) \\\n + ncon(h4e[:n, n:, n:, n:, :n, n:, n:, n:], evecbb)\n\n nevecbb = ncon(h4e[n:, n:, :n, :n, n:, n:, :n, :n], evecaa) \\\n + 2.0 * ncon(h4e[n:, n:, :n, n:, n:, n:, :n, n:], evecab) \\\n + ncon(h4e[n:, n:, n:, n:, n:, n:, n:, n:], evecbb)\n\n dveca2 = numpy.zeros(dveca.shape, dtype=self._dtype)\n dvecb2 = numpy.zeros(dvecb.shape, dtype=self._dtype)\n for i in range(norb):\n for j in range(norb):\n dveca[:, :, :, :] = nevecaa[i, j, :, :, :, :]\n dvecb[:, :, :, :] = nevecab[i, j, :, :, :, :]\n cvec = self._calculate_coeff_spin_with_dvec((dveca, dvecb))\n dveca2[i, j, :, :] += cvec[:, :]\n\n dveca[:, :, :, :] = nevecab[:, :, i, j, :, :]\n dvecb[:, :, :, :] = nevecbb[i, j, :, :, :, :]\n cvec = self._calculate_coeff_spin_with_dvec((dveca, dvecb))\n dvecb2[i, j, :, :] += cvec[:, :]\n\n out += self._calculate_coeff_spin_with_dvec((dveca2, dvecb2))\n return out","def test_periodic_boundary_one_ring_rod():\n\n n_elems = 5\n ring_rod = MockRingRod(n_elems)\n block_structure = MemoryBlockCosseratRod([ring_rod], [0])\n\n correct_periodic_boundary_node_idx = np.array(\n [[0, 6, 7], [5, 1, 2]], dtype=np.int64\n )\n correct_periodic_boundary_elem_idx = np.array([[0, 6], [5, 1]], dtype=np.int64)\n correct_periodic_boundary_voronoi_idx = np.array([[0], [5]], dtype=np.int64)\n\n assert_allclose(\n correct_periodic_boundary_node_idx,\n block_structure.periodic_boundary_nodes_idx,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_periodic_boundary_elem_idx,\n block_structure.periodic_boundary_elems_idx,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_periodic_boundary_voronoi_idx,\n block_structure.periodic_boundary_voronoi_idx,\n atol=Tolerance.atol(),\n )\n\n correct_start_node_idx = np.array([1], dtype=np.int64)\n correct_end_node_idx = np.array([6], dtype=np.int64)\n\n correct_start_elem_idx = np.array([1], dtype=np.int64)\n correct_end_elem_idx = np.array([6], dtype=np.int64)\n\n correct_start_voronoi_idx = np.array([1], dtype=np.int64)\n correct_end_voronoi_idx = np.array([6], dtype=np.int64)\n\n assert_allclose(\n correct_start_node_idx,\n block_structure.start_idx_in_rod_nodes,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_node_idx,\n block_structure.end_idx_in_rod_nodes,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_start_elem_idx,\n block_structure.start_idx_in_rod_elems,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_elem_idx,\n block_structure.end_idx_in_rod_elems,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_start_voronoi_idx,\n block_structure.start_idx_in_rod_voronoi,\n atol=Tolerance.atol(),\n )\n assert_allclose(\n correct_end_voronoi_idx,\n block_structure.end_idx_in_rod_voronoi,\n atol=Tolerance.atol(),\n )","def test_check_map_primer_pool(self):\r\n s = \"\"\"#SampleID\\tBarcodeSequence\\tLinkerPrimerSequence\\tX\\tDescription\r\n#fake data\r\nx\\tAA\\tAC\\t3\\tsample_x\r\ny\\t\"AC\"\\tAT,DC\\t4\\t\"sample_y\"\r\nz\\tGG\\tGC\\t5\\tsample_z\"\"\"\r\n f = StringIO(s)\r\n f.name = 'test.xls'\r\n headers, id_map, barcode_to_sample_id, warnings, errors, \\\r\n primer_seqs_lens, all_primers = check_map(f,\r\n disable_primer_check=False)\r\n\r\n self.assertEqual(\r\n barcode_to_sample_id,\r\n {'AA': 'x',\r\n 'AC': 'y',\r\n 'GG': 'z'})\r\n self.assertEqual(errors, [])\r\n self.assertEqual(warnings, [])\r\n\r\n # Returns all possible primers with lengths associated.\r\n expected_all_primers = {'AC': 2, 'GC': 2, 'AT': 2, 'TC': 2}\r\n self.assertEqual(all_primers, expected_all_primers)\r\n\r\n # Returns all primers associated with each barcode.\r\n expected_primer_seqs_lens = {'AA': {'AC': 2}, 'GG': {'GC': 2},\r\n 'AC': {'AC': 2, 'GC': 2, 'AT': 2, 'TC': 2}}\r\n\r\n self.assertEqual(primer_seqs_lens, expected_primer_seqs_lens)","def test_pid_ig1():\n d = bivariates['and']\n pid = PID_IG(d, ((0,), (1,)), (2,))\n assert pid[((0,), (1,))] == pytest.approx(0.08283, abs=1e-4)\n assert pid[((0,),)] == pytest.approx(0.22845, abs=1e-4)\n assert pid[((1,),)] == pytest.approx(0.22845, abs=1e-4)\n assert pid[((0, 1),)] == pytest.approx(0.27155, abs=1e-4)","def test_spw_id_list(self):\n spw = '21,25'\n ref_idx = [1,2]\n self.res=self.run_task(infile=self.rawfile,spw=spw,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_hdf5_reader_spinpol_dos(data_regression):\n from masci_tools.io.parsers.hdf5 import HDF5Reader\n from masci_tools.io.parsers.hdf5.recipes import FleurDOS\n\n TEST_BANDDOS_FILE = os.path.join(HDFTEST_DIR, 'banddos_spinpol_dos.hdf')\n\n with HDF5Reader(TEST_BANDDOS_FILE) as reader:\n data, attrs = reader.read(recipe=FleurDOS)\n\n data_regression.check({'datasets': convert_to_pystd(data), 'attributes': convert_to_pystd(attrs)})","def generate_subsegment_id():\n return uuid.uuid4().hex[:16]","def get_ids(data, N_max):\n\n id_data = data[['molecule_name', 'id']].copy()\n\n # write molecules into one line\n id_data = id_data.groupby('molecule_name').apply(lambda x:\n x.values.reshape(-1))\n\n # pad with nans\n id_list = []\n for i in range(len(id_data)):\n n = N_max*2 - len(id_data[i])\n id_list.append(np.pad(id_data[i], (0, n), 'constant',\n constant_values=(0, np.nan)))\n\n # build np array and remove molecule names\n id_data = np.vstack(id_list)\n del id_list\n id_data = np.delete(id_data, [2*i for i in range(N_max)], 1)\n\n return id_data","def generate_run_id(self):\n r_id_len = 4\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\n while r_id in self.cache:\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\n return r_id"],"string":"[\n \"def test_generate_spin_id_data_array6(self):\\n\\n # The data.\\n data = ['1', 'GLY', None, None]\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\\n\\n # Test the string.\\n self.assertEqual(id, ':1')\",\n \"def test_generate_spin_id_data_array1(self):\\n\\n # The data.\\n data = ['1', 'GLY']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\\n\\n # Test the string.\\n self.assertEqual(id, ':1')\",\n \"def test_generate_spin_id_data_array5(self):\\n\\n # The data.\\n data = ['Ap4Aase', '1', 'GLY', '234', 'NH']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5)\\n\\n # Test the string.\\n self.assertEqual(id, '#Ap4Aase:1@234')\",\n \"def test_generate_spin_id_data_array2(self):\\n\\n # The data.\\n data = ['1', 'GLY', '234', 'NH']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2, spin_num_col=3, spin_name_col=4)\\n\\n # Test the string.\\n self.assertEqual(id, ':1@234')\",\n \"def test_generate_spin_id_data_array3(self):\\n\\n # The data.\\n data = ['Ap4Aase', '234', 'NH']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=None, res_name_col=None, spin_num_col=2, spin_name_col=3)\\n\\n # Test the string.\\n self.assertEqual(id, '#Ap4Aase@234')\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def test_id_array(self):\\n arr = vtk.vtkIdTypeArray()\\n arr.SetNumberOfTuples(10)\\n for i in range(10):\\n arr.SetValue(i, i)\\n\\n np = array_handler.vtk2array(arr)\\n self.assertEqual(numpy.all(np == range(10)), True)\",\n \"def test_random_id(self):\\r\\n ids = \\\\\\r\\n \\\"R27DLI_4812 R27DLI_600 R27DLI_727 U1PLI_403 U1PLI_8969\\\".split(\\r\\n )\\r\\n assert random_id(ids, {}) in ids\\r\\n # just test we got something from the list, don't add stochastic test\\r\",\n \"def test_create_template(self):\\n m_size = 10\\n data = ecn.IDData(m_size)\\n self.assertEqual(np.shape(data.ID_MATRIX), (m_size, m_size))\\n self.assertEqual(sum(sum(data.ID_MATRIX)), m_size)\\n self.assertTrue((sum(data.ID_MATRIX) == np.ones(m_size)).all())\\n print('Finished testing template\\\\n')\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_spin_loop(self):\\n\\n # Spin data.\\n select = [1, 0]\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, 'N5')\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 2)\",\n \"def createArrayFunc(self):\\r\\n minVal = int(self.spinBoxMin_2.value())\\r\\n maxVal = int(self.spinBoxMax_2.value())\\r\\n arrayLength = int(self.spinBoxLength_2.value())\\r\\n different = maxVal - minVal\\r\\n if self.checkBoxNoRepeate_2.isChecked():\\r\\n if different > arrayLength:\\r\\n def unique_rand(initial, limit, total):\\r\\n data = []\\r\\n i = 0\\r\\n while i < total:\\r\\n number = numpy.random.randint(initial, limit)\\r\\n if number not in data:\\r\\n data.append(number)\\r\\n i += 1\\r\\n return data\\r\\n\\r\\n self.UnsortedArray_2 = unique_rand(minVal, maxVal, arrayLength)\\r\\n else:\\r\\n err = \\\"Array length must be greater than difference between limits\\\"\\r\\n self.labelUnsortedArray_2.setText(str(err))\\r\\n\\r\\n else:\\r\\n self.UnsortedArray_2 = numpy.random.randint(minVal, maxVal, arrayLength)\\r\\n self.labelUnsortedArray_2.setText(str(self.UnsortedArray_2))\\r\\n self.SortedArray_2 = Insertion.sorting(self.UnsortedArray_2)\\r\\n self.labelSortedArray_2.setText(str(self.SortedArray_2))\\r\\n binaryMax = int(self.spinBoxMax_2.value())\\r\\n binaryMin = int(self.spinBoxMin_2.value())\\r\\n self.spinBoxBinary.setMaximum(binaryMax)\\r\\n self.spinBoxBinary.setMinimum(binaryMin)\\r\\n self.spinBoxIthSmallest.setMaximum(arrayLength + 1)\",\n \"def test_scan_id_list(self):\\n scan = '15,17'\\n ref_idx = [0,3]\\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_arr2vtkIdList(self):\\n a = [1, 2, 3, 4, 5]\\n p = array_handler.array2vtkIdList(a)\\n for i, j in enumerate(a): \\n self.assertEqual(p.GetId(i), j)\\n p = vtk.vtkIdList()\\n ident = id(p)\\n p = array_handler.array2vtkIdList(numpy.array(a), p)\\n for i, j in enumerate(a): \\n self.assertEqual(p.GetId(i), j)\\n self.assertEqual(id(p), ident)\\n \\n self.assertRaises(AssertionError, array_handler.array2vtkIdList,\\n [[1,2,3]])\",\n \"def test_id_rot():\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_axis_angle(pr.a_id))\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_quaternion(pr.q_id))\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_xyz(pr.e_xyz_id))\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_zyx(pr.e_zyx_id))\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_pol_id_list(self):\\n pol = '0,1'\\n ref_idx = []\\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_uuid():\\n for _ in range(1000):\\n uuid = uuid_generator()\\n assert len(uuid) == 36\\n assert uuid.count('-') == 4\",\n \"def _apply_array_spin123(self,\\n h1e: 'Nparray',\\n h2e: 'Nparray',\\n h3e: 'Nparray',\\n dvec: Optional[Tuple['Nparray', 'Nparray']] = None,\\n evec: Optional[Tuple['Nparray', 'Nparray', 'Nparray', 'Nparray']] \\\\\\n = None) -> 'Nparray':\\n norb = self.norb()\\n assert h3e.shape == (norb * 2,) * 6\\n assert not (dvec is None) ^ (evec is None)\\n\\n from1234 = (dvec is not None) and (evec is not None)\\n\\n nh1e = numpy.copy(h1e)\\n nh2e = numpy.copy(h2e)\\n\\n for i in range(norb * 2):\\n for j in range(norb * 2):\\n for k in range(norb * 2):\\n nh2e[j, k, :, :] += (-h3e[k, j, i, i, :, :] -\\n h3e[j, i, k, i, :, :] -\\n h3e[j, k, i, :, i, :])\\n\\n nh1e[:, :] += h3e[:, i, j, i, j, :]\\n\\n out = self._apply_array_spin12_halffilling(nh1e, nh2e)\\n\\n n = norb # This is just shorter\\n if not from1234:\\n symfac = 2.0\\n axes = ((1, 3), (0, 1))\\n (odveca, odvecb) = self.calculate_dvec_spin()\\n dveca = numpy.zeros_like(odveca)\\n dvecb = numpy.zeros_like(odvecb)\\n\\n for i in range(norb):\\n for j in range(norb):\\n evecaa, _ = self._calculate_dvec_spin_with_coeff(\\n odveca[i, j, :, :])\\n evecab, evecbb = self._calculate_dvec_spin_with_coeff(\\n odvecb[i, j, :, :])\\n\\n dveca += numpy.tensordot(h3e[:n, :n, i, :n, :n, j],\\n evecaa,\\n axes=axes)\\n dveca += numpy.tensordot(h3e[:n, :n, n + i, :n, :n, n + j],\\n evecab,\\n axes=axes) * symfac\\n dveca += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\\n evecbb,\\n axes=axes)\\n\\n dvecb += numpy.tensordot(h3e[n:, :n, i, n:, :n, j],\\n evecaa,\\n axes=axes)\\n dvecb += numpy.tensordot(h3e[n:, :n, n + i, n:, :n, n + j],\\n evecab,\\n axes=axes) * symfac\\n dvecb += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\\n evecbb,\\n axes=axes)\\n else:\\n symfac = 1.0\\n axes = ((1, 4, 2, 5), (0, 1, 2, 3)) # type: ignore\\n dveca, dvecb = dvec # type: ignore\\n evecaa, evecab, evecba, evecbb = evec # type: ignore\\n\\n dveca = numpy.tensordot(h3e[:n, :n, :n, :n, :n, :n],\\n evecaa, axes=axes) \\\\\\n + numpy.tensordot(h3e[:n, :n, n:, :n, :n, n:],\\n evecab, axes=axes) * symfac \\\\\\n + numpy.tensordot(h3e[:n, n:, n:, :n, n:, n:],\\n evecbb, axes=axes) + \\\\\\n + numpy.tensordot(h3e[:n, n:, :n, :n, n:, :n],\\n evecba, axes=axes)\\n\\n dvecb = numpy.tensordot(h3e[n:, :n, :n, n:, :n, :n],\\n evecaa, axes=axes) \\\\\\n + numpy.tensordot(h3e[n:, :n, n:, n:, :n, n:],\\n evecab, axes=axes) * symfac \\\\\\n + numpy.tensordot(h3e[n:, n:, n:, n:, n:, n:],\\n evecbb, axes=axes) + \\\\\\n + numpy.tensordot(h3e[n:, n:, :n, n:, n:, :n],\\n evecba, axes=axes)\\n\\n out -= self._calculate_coeff_spin_with_dvec((dveca, dvecb))\\n return out\",\n \"def test_get_ids(civic, main_data, updated_data):\\n assert len(civic._get_ids(main_data['assertions'])) == 0\\n assert len(civic._get_ids(main_data['variants'])) == 1\\n assert len(civic._get_ids(main_data['genes'])) == 2\\n assert len(civic._get_ids(main_data['evidence'])) == 1\\n\\n assert len(civic._get_ids(updated_data['assertions'])) == 1\\n assert len(civic._get_ids(updated_data['variants'])) == 1\\n assert len(civic._get_ids(updated_data['genes'])) == 1\\n assert len(civic._get_ids(updated_data['evidence'])) == 1\",\n \"def test_spin_loop_no_selection(self):\\n\\n # Spin data.\\n select = [0, 1, 0, 0, 1, 1, 0, 1]\\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 8)\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_scan_id_range(self):\\n scan = '16~17'\\n ref_idx = [1,2,3]\\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_sampleId_pairs(self):\\r\\n # expected values\\r\\n dose_vps = \\\\\\r\\n [('1xDose', '2xDose'), ('1xDose', 'Control'),\\r\\n ('2xDose', 'Control')]\\r\\n ttd_vps = \\\\\\r\\n [('31', '21'), ('31', '55'), ('31', '67'), ('21', '55'),\\r\\n ('21', '67'), ('55', '67')]\\r\\n dose_sids = \\\\\\r\\n [(['Sam1', 'Sam2', 'Sam6'], ['Sam3', 'Sam4']),\\r\\n (['Sam1', 'Sam2', 'Sam6'], ['Sam5']),\\r\\n (['Sam3', 'Sam4'], ['Sam5'])]\\r\\n ttd_sids = \\\\\\r\\n [(['Sam1'], ['Sam3']),\\r\\n (['Sam1'], ['Sam4', 'Sam6']),\\r\\n (['Sam1'], ['Sam2', 'Sam5']),\\r\\n (['Sam3'], ['Sam4', 'Sam6']),\\r\\n (['Sam3'], ['Sam2', 'Sam5']),\\r\\n (['Sam4', 'Sam6'], ['Sam2', 'Sam5'])]\\r\\n\\r\\n # observed values\\r\\n obs_dose_sids, obs_dose_vps = sampleId_pairs(self.mapping_data,\\r\\n self.rarefaction_data, 'Dose')\\r\\n obs_ttd_sids, obs_ttd_vps = sampleId_pairs(self.mapping_data,\\r\\n self.rarefaction_data, 'TTD')\\r\\n\\r\\n # sort -- order is unimportant and depends on way presented in mf\\r\\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\\r\\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())\\r\\n self.assertEqual(ttd_vps.sort(), obs_ttd_vps.sort())\\r\\n self.assertEqual(ttd_sids.sort(), obs_ttd_sids.sort())\\r\\n\\r\\n # check errors when no samples had this category\\r\\n self.assertRaises(ValueError, sampleId_pairs, self.mapping_data,\\r\\n self.rarefaction_data, 'DNE')\\r\\n\\r\\n # check no error if map file has more sampleids than rarefaction data\\r\\n superset_mf = \\\\\\r\\n ['#SampleID\\\\tDose\\\\tLinkerPrimerSequence\\\\tWeight\\\\tTTD\\\\tDescription',\\r\\n '#Comment Line',\\r\\n 'Sam1\\\\t1xDose\\\\tATCG\\\\tHigh\\\\t31\\\\ts1_desc',\\r\\n 'Sam2\\\\t1xDose\\\\tACCG\\\\tLow\\\\t67\\\\ts2_desc',\\r\\n 'Sam3\\\\t2xDose\\\\tACGT\\\\tMed\\\\t21\\\\ts3_desc',\\r\\n 'Sam4\\\\t2xDose\\\\tAACG\\\\tLow\\\\t55\\\\ts4_desc',\\r\\n 'Sam5\\\\tControl\\\\tCGTC\\\\tLow\\\\t67\\\\ts5_desc',\\r\\n 'Sam6\\\\t1xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts6_desc',\\r\\n 'Sam7\\\\t4xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts7_desc',\\r\\n 'Sam8\\\\t3xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts8_desc',\\r\\n 'Sam9\\\\t1xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts9_desc']\\r\\n # (mf, comments)\\r\\n superset_mf = parse_mapping_file_to_dict(superset_mf)[0]\\r\\n obs_dose_sids, obs_dose_vps = sampleId_pairs(superset_mf,\\r\\n self.rarefaction_data, 'Dose')\\r\\n\\r\\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\\r\\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())\",\n \"def test_weyl_specialize_id(self):\\n a, b, c = 0.0, 0.0, 0.0\\n for da, db, dc in DELTAS:\\n for k1l, k1r, k2l, k2r in K1K2SB:\\n k1 = np.kron(k1l.data, k1r.data)\\n k2 = np.kron(k2l.data, k2r.data)\\n self.check_two_qubit_weyl_specialization(\\n k1 @ Ud(a + da, b + db, c + dc) @ k2,\\n 0.999,\\n TwoQubitWeylIdEquiv,\\n {\\\"rz\\\": 4, \\\"ry\\\": 2},\\n )\",\n \"def test_split_id_otp(self):\\n public_id, otp, = pyhsm.yubikey.split_id_otp(\\\"ft\\\" * 16)\\n self.assertEqual(public_id, '')\\n self.assertEqual(otp, \\\"ft\\\" * 16)\\n\\n public_id, otp, = pyhsm.yubikey.split_id_otp(\\\"cc\\\" + \\\"ft\\\" * 16)\\n self.assertEqual(public_id, 'cc')\\n self.assertEqual(otp, \\\"ft\\\" * 16)\",\n \"def _get_rand_array(self):\\n pass\",\n \"def test_field_id_list(self):\\n field = '5,8'\\n ref_idx = [0,3]\\n self.res=self.run_task(infile=self.rawfile,field=field,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def generate_new_ids(ids: np.array, n_required: int) -> np.array:\\n\\n current_max_id = ids.max()\\n new_ids = np.arange(n_required) + current_max_id + 1\\n\\n return new_ids\",\n \"def test_random_integers(self):\\r\\n # Check over two calls to see if the random state is correctly updated.\\r\\n random = RandomStreams(utt.fetch_seed())\\r\\n fn = function([], random.random_integers((20, 20), -5, 5))\\r\\n fn_val0 = fn()\\r\\n fn_val1 = fn()\\r\\n\\r\\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\\r\\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\\r\\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\\r\\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\\r\\n\\r\\n assert numpy.all(fn_val0 == numpy_val0)\\r\\n assert numpy.all(fn_val1 == numpy_val1)\",\n \"def test_SampleIds(self):\\r\\n exp = [\\\"PC.354\\\", \\\"PC.355\\\", \\\"PC.356\\\", \\\"PC.481\\\", \\\"PC.593\\\", \\\"PC.607\\\",\\r\\n \\\"PC.634\\\", \\\"PC.635\\\", \\\"PC.636\\\"]\\r\\n obs = self.overview_map.SampleIds\\r\\n self.assertEqual(obs, exp)\\r\\n\\r\\n obs = self.no_metadata.SampleIds\\r\\n self.assertEqual(obs, exp)\\r\\n\\r\\n obs = self.empty_map.SampleIds\\r\\n self.assertEqual(obs, [])\",\n \"def generate_T(number_obeservations):\\n T = np.random.randint(0, 2, (number_obeservations,1))\\n return T\",\n \"def test_SampleIds(self):\\n exp = [\\\"PC.354\\\", \\\"PC.355\\\", \\\"PC.356\\\", \\\"PC.481\\\", \\\"PC.593\\\", \\\"PC.607\\\",\\n \\\"PC.634\\\", \\\"PC.635\\\", \\\"PC.636\\\"]\\n obs = self.overview_map.SampleIds\\n self.assertEqual(obs, exp)\\n\\n obs = self.no_metadata.SampleIds\\n self.assertEqual(obs, exp)\\n\\n obs = self.empty_map.SampleIds\\n self.assertEqual(obs, [])\",\n \"def test_from_pdb_t4_n_residues(self):\\n expected_n_residues = 164 # noqa\\n raise NotImplementedError\",\n \"def test_generate(self):\\n cant_interations = int(random()*100)\\n for i in range(cant_interations):\\n number = self.sudoku.generate() # Generate number\\n self.assertGreaterEqual(number, 0) # number >= 0\\n self.assertLessEqual(number, 8) # number <= 8\",\n \"def test_generateuuids(self):\\n ret1 = {\\\"message\\\": \\\"No Random.org api key or api version found.\\\", \\\"res\\\": False}\\n self.assertDictEqual(random_org.generateUUIDs(), ret1)\\n\\n ret2 = {\\\"message\\\": \\\"Required argument, number is missing.\\\", \\\"res\\\": False}\\n self.assertDictEqual(\\n random_org.generateUUIDs(api_key=\\\"peW\\\", api_version=\\\"1\\\"), ret2\\n )\\n\\n ret3 = {\\\"message\\\": \\\"Number of UUIDs must be between 1 and 1000\\\", \\\"res\\\": False}\\n self.assertDictEqual(\\n random_org.generateUUIDs(api_key=\\\"peW\\\", api_version=\\\"1\\\", number=\\\"5\\\"), ret3\\n )\\n\\n ret3 = {\\\"message\\\": \\\"Parameter 'apiKey' is malformed\\\", \\\"res\\\": False}\\n self.assertDictEqual(\\n random_org.generateUUIDs(api_key=\\\"peW\\\", api_version=\\\"1\\\", number=5), ret3\\n )\",\n \"def test_run_sim():\\n rnd = rand.Arrivals(31, 40)\\n sim.run_sim(2, 1, 3, 4, 24, rnd)\",\n \"def test_if_array_is_good(self):\\n testing_param = random.randint(1, 100)\\n self.assertEqual(self.exercice.main(testing_param),\\n list(range(2, testing_param+1, 2)))\",\n \"def test_spin_type(get_pdos_generator_inputs):\\n with pytest.raises(NotImplementedError):\\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=spin_type)\\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=SpinType.COLLINEAR)\\n for namespace in [builder.scf, builder.nscf]:\\n parameters = namespace['pw']['parameters'].get_dict()\\n assert parameters['SYSTEM']['nspin'] == 2\\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}\",\n \"def get_test_split(self, fraction=0.1):\\n rng = np.random.default_rng(42)\\n test_size = int(round(len(self.all_asset_ids) * fraction))\\n test_ids = rng.choice(self.all_asset_ids, size=test_size, replace=False)\\n train_ids = [i for i in self.all_asset_ids if i not in test_ids]\\n return train_ids, test_ids\",\n \"def test_create_tornado_id(self):\\n\\n this_id_string = tornado_io.create_tornado_id(\\n start_time_unix_sec=TORNADO_START_TIME_UNIX_SEC,\\n start_latitude_deg=TORNADO_START_LATITUDE_DEG,\\n start_longitude_deg=TORNADO_START_LONGITUDE_DEG)\\n\\n self.assertTrue(this_id_string == TORNADO_ID_STRING)\",\n \"def test_residue_loop(self):\\n\\n # Loop over the residues.\\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\\n # Test the selection.\\n self.assertEqual(res.num, 2)\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_run_sim_1():\\n rnd = rand.Arrivals(36, 41)\\n sim.run_sim(3, 2, 5, 6, 22, rnd)\",\n \"def test_random_integers(self):\\r\\n # Check over two calls to see if the random state is correctly updated.\\r\\n m = Module()\\r\\n m.random = RandomStreams(utt.fetch_seed())\\r\\n m.fn = Method([], m.random.random_integers((20,20), -5, 5))\\r\\n\\r\\n made = m.make()\\r\\n made.random.initialize()\\r\\n fn_val0 = made.fn()\\r\\n fn_val1 = made.fn()\\r\\n\\r\\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\\r\\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\\r\\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\\r\\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\\r\\n\\r\\n assert numpy.all(fn_val0 == numpy_val0)\\r\\n assert numpy.all(fn_val1 == numpy_val1)\",\n \"def myID() -> np.int:\\r\\n return 304976335\",\n \"def myID() -> np.int:\\r\\n return 304976335\",\n \"def test_pol_id_range(self):\\n pol = '0~1'\\n ref_idx = []\\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def gen_data(min_coord, max_coord, size):\\r\\n data = np.random.randint(min_coord, max_coord, size)\\r\\n return data\",\n \"def test_kf_id():\\n\\n for _ in range(1000):\\n prefix = ''.join(random.sample(string.ascii_uppercase, 2))\\n kf_id = kf_id_generator(prefix)()\\n assert kf_id[:2] == prefix\\n assert len(kf_id) == 11\\n assert kf_id[2] == '_'\\n\\n assert 'I' not in kf_id[2:]\\n assert 'L' not in kf_id[2:]\\n assert 'O' not in kf_id[2:]\\n assert 'U' not in kf_id[2:]\\n\\n assert re.search(r'^'+prefix+r'_[A-HJ-KM-NP-TV-Z0-9]{8}', kf_id)\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def genNumID(size):\\n\\tid = \\\"\\\"\\n\\tfor i in range(size):\\n\\t\\tid = id + selectRandomFromList(numTokens)\\n\\treturn id\",\n \"def generaterandomindices(dataSize, percentTest):\\n\\n TrainIndices = np.array([])\\n while TrainIndices.__len__() < int(percentTest * dataSize):\\n # Randomly select an index value and store it. If it has already been chosen, pick again.\\n index = int(random.random() * dataSize)\\n if not TrainIndices.__contains__(index):\\n TrainIndices = np.append(TrainIndices, [index])\\n\\n # For aesthetic purposes:\\n TrainIndices = np.sort(TrainIndices)\\n\\n return TrainIndices\",\n \"def test_apply_ridit(self):\\n x, x_rand, s = self.create_testdata()\\n task = mmRDTR()\\n s = task.check_sparse(s)\\n\\n for data in [x, x_rand, s]:\\n #get ecdf for data\\n Fn=task.make_ECDF(data)\\n out=task.apply_ridit( data, Fn )\\n # check same dimension\\n self.assertEqual(np.all(data.shape==out.shape),True)\\n # check mean almost equal to 0\\n for i in range(data.shape[1]):\\n self.assertEqual(round(out[:,i].mean(),8),0)\\n # check if works with newdata\\n newdata=data[:2]\\n out=task.apply_ridit( newdata, Fn )\\n # check same dimension\\n self.assertEqual(np.all(newdata.shape==out.shape),True)\",\n \"def test_returned_num_in_random_nums(self):\\n self._setup_random_gen([1.], [42])\\n self.assertEqual(self._random_gen.next_num(), 42)\",\n \"def test_brains_id_get(self):\\n pass\",\n \"def test_arbitrary_rotation(self):\\n \\n # This test is run a bunch of times on various intervals, ranging from 50% to 1/6\\n\\t\\t# (16.667%).\\n for i in range(2, 7):\\n \\n interval = 1 / i # The amount to increase each qubit's probability by, relative to the previous qubit\\n step_string = \\\"{:.4f}\\\".format(100 / i) # The decimal representation of the interval, as a percent\\n target_probabilities = [0] * (i + 1) # This will store the desired probabilities of each qubit\\n for j in range(0, i + 1):\\n target_probability = j * interval\\n target_probabilities[j] = target_probability\\n\\n # Run the test\\n self.run_test(self.arbitrary_rotation_function, f\\\"Rotation with steps of 1/{i} ({step_string}%)\\\", 2000, target_probabilities, 0.05)\",\n \"def test_scan_id_exprlist(self):\\n scan = '15,>16'\\n ref_idx = [0,3]\\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def make_row(invalid_data=[]):\\n\\n ### Database Identifiers ###\\n \\n # phac_sample_id, valid/invalid error-grid information.\\n phac_sample_id, phac_sample_id_error = lib.random_phac_id(invalid_data)\\n # umbrella_bioproject_accession, valid/invalid error-grid information.\\n ub_accession, ub_accession_error = lib.umbrella_bioproject_accession(invalid_data)\\n # bioproject_accession, valid/invalid error-grid information.\\n bp_accession, bp_accession_error = lib.random_bioproject_accession(invalid_data)\\n # biosample_accession, valid/invalid error-grid information.\\n bs_accession, bs_accession_error = lib.random_biosample_accession(invalid_data)\\n # sra_accession, valid/invalid error-grid information.\\n sra_accession, sra_accession_error = lib.random_sra_accession(invalid_data)\\n # genbank_accession, valid/invalid error-grid information.\\n gb_accession, gb_accession_error = lib.random_genbank_accession(invalid_data)\\n # gisaid_accession, valid/invalid error-grid information.\\n gisaid_accession, gisaid_accession_error = lib.random_gisaid_accession(invalid_data)\\n \\n ### Sample Collection and Processing ###\\n \\n # sample_collected_by, valid/invalid error-grid information.\\n samp_col_by, samp_col_by_error = lib.random_agency(invalid_data)\\n # sample_collector_contact_email, valid/invalid error-grid information.\\n samp_col_email, samp_col_email_error = lib.random_email(invalid_data)\\n # sample_collector_contact_address, valid/invalid error-grid information.\\n samp_col_address, samp_col_address_error = lib.random_address(invalid_data)\\n # sequence_submitter_contact_email, valid/invalid error-grid information.\\n seq_sub_email, seq_sub_email_error = lib.random_email(invalid_data)\\n # sequence_submitter_contact_address, valid/invalid error-grid information.\\n seq_sub_address, seq_sub_address_error = lib.random_address(invalid_data)\\n # sample_collection_date, valid/invalid error-grid information.\\n samp_col_date, samp_col_date_error = lib.random_date(invalid_data)\\n # sample_received_date, valid/invalid error-grid information.\\n samp_rec_date, samp_rec_date_error = lib.random_date(invalid_data)\\n # geo_loc_name_country, valid/invalid error-grid information.\\n geo_loc_country, geo_loc_country_error = lib.random_country(invalid_data)\\n # geo_loc_name_province_territory, valid/invalid error-grid information.\\n geo_loc_prov_ter, geo_loc_prov_ter_error = lib.random_province_territory(invalid_data)\\n # geo_loc_name_city, valid/invalid error-grid information.\\n geo_loc_city, geo_loc_city_error = lib.random_city(invalid_data)\\n # organism, valid/invalid error-grid information.\\n organism, organism_error = lib.random_organism(invalid_data)\\n # purpose_of_sampling, valid/invalid error-grid information.\\n p_o_sampling, p_o_sampling_error = lib.random_purpose_of_sampling(invalid_data)\\n # anatomical_material, valid/invalid error-grid information.\\n anat_material, anat_material_error = lib.random_anatomical_material(invalid_data)\\n # anatomical_part, valid/invalid error-grid information.\\n anat_part, anat_part_error = lib.random_anatomical_part(invalid_data)\\n # body_product, valid/invalid error-grid information.\\n body_product, body_product_error = lib.random_body_product(invalid_data)\\n # environmental_material, valid/invalid error-grid information.\\n envi_material, envi_material_error = lib.random_environmental_material(invalid_data)\\n # environmental_site, valid/invalid error-grid information.\\n envi_site, envi_site_error = lib.random_environmental_site(invalid_data)\\n # collection_device, valid/invalid error-grid information.\\n col_device, col_device_error = lib.random_collection_device(invalid_data)\\n # collection_method, valid/invalid error-grid information.\\n col_method, col_method_error = lib.random_collection_method(invalid_data)\\n # collection_protocol, valid/invalid error-grid information.\\n col_protocol, col_protocol_error = lib.fake_protocol(invalid_data)\\n # specimen_processing, valid/invalid error-grid information.\\n spec_process, spec_process_error = lib.random_specimen_processing(invalid_data)\\n # lab_host, valid/invalid error-grid information.\\n lab_host, lab_host_error = lib.random_lab_host(invalid_data)\\n # passage_number , valid/invalid error-grid information.\\n passage_num, passage_num_error = lib.random_passage_number(invalid_data)\\n # passage_method, valid/invalid error-grid information.\\n passage_method, passage_method_error = lib.passage_method_text(invalid_data)\\n # biomaterial_extracted, valid/invalid error-grid information.\\n biom_extract, biom_extract_error = lib.random_biomaterial_extracted(invalid_data)\\n \\n ### Host Information ###\\n \\n # host_common_name, valid/invalid error-grid information.\\n host_com_name, host_com_name_error = lib.random_host_common_name(invalid_data)\\n # host_scientific_name, valid/invalid error-grid information.\\n host_sci_name, host_sci_name_error = lib.random_host_scientific_name(invalid_data)\\n # host_health_state, valid/invalid error-grid information.\\n host_health_state, host_health_state_error = lib.random_host_health_state(invalid_data)\\n # host_health_status_details, valid/invalid error-grid information.\\n host_health_status, host_health_status_error = lib.random_host_health_status_details(invalid_data)\\n # host_disease, valid/invalid error-grid information.\\n host_disease, host_disease_error = lib.random_host_disease(invalid_data)\\n # host_age, valid/invalid error-grid information.\\n host_age, host_age_error = lib.random_host_age(invalid_data)\\n # host_gender, valid/invalid error-grid information.\\n host_gender, host_gender_error = lib.random_host_gender(invalid_data)\\n # host_origin_geo_loc_name_country, valid/invalid error-grid information.\\n host_loc_country, host_loc_country_error = lib.random_country(invalid_data)\\n # host_subject_id, valid/invalid error-grid information.\\n host_sub_id, host_sub_id_error = lib.random_host_subject_id(invalid_data)\\n # symptom_onset_date, valid/invalid error-grid information.\\n symp_onset_date, symp_onset_date_error = lib.random_date(invalid_data)\\n # signs_and_symptoms, valid/invalid error-grid information.\\n signs_symptoms, signs_symptoms_error = lib.random_signs_symptoms(invalid_data)\\n \\n ### Host Exposure Information ###\\n \\n # location_of_exposure_geo_loc_name_country, valid/invalid error-grid information.\\n loc_exp_country, loc_exp_country_error = lib.random_country(invalid_data)\\n # travel_history, valid/invalid error-grid information. \\n trav_history, trav_history_error = lib.random_travel_history(invalid_data)\\n # exposure_event, valid/invalid error-grid information.\\n exp_event, exp_event_error = lib.random_exposure_event(invalid_data)\\n \\n ### Sequencing ###\\n \\n # minion_barcode, valid/invalid error-grid information.\\n minion_barcode, minion_barcode_error = lib.random_minIon_barcode(invalid_data)\\n # sequencing_instrument, valid/invalid error-grid information.\\n seq_instrument, seq_instrument_error = lib.random_seq_instrument(invalid_data)\\n # sequencing_protocol_name, valid/invalid error-grid information.\\n seq_prot_name, seq_prot_name_error = lib.fake_protocol(invalid_data)\\n # sequencing_protocol_source, valid/invalid error-grid information.\\n seq_prot_source, seq_prot_source_error = lib.random_seq_protocol_source(invalid_data)\\n # sequencing_kit_number, valid/invalid error-grid information.\\n seq_kit_num, seq_kit_num_error = lib.random_seq_kit_num(invalid_data)\\n # amplicon_pcr_primers_filename, valid/invalid error-grid information.\\n amp_pcr_filename, amp_pcr_filename_error = lib.random_txt_filename(invalid_data)\\n \\n ### Bioinformatics and QC metrics ###\\n \\n # raw_sequence_data_processing, valid/invalid error-grid information.\\n raw_seq_process, raw_seq_process_error = lib.random_seq_process(invalid_data)\\n # sequencing_depth_average, valid/invalid error-grid information.\\n seq_depth_avg, seq_depth_avg_error = lib.random_seq_depth(invalid_data)\\n # assembly_method, valid/invalid error-grid information.\\n assemb_method, assemb_method_error = lib.random_assembly_software(invalid_data)\\n # assembly_coverage_breadth, valid/invalid error-grid information.\\n assemb_cov_breadth, assemb_cov_breadth_error = lib.random_assembly_coverage_breadth(invalid_data)\\n # assembly_coverage_depth, valid/invalid error-grid information.\\n assemb_cov_depth, assemb_cov_depth_error = lib.random_seq_depth(invalid_data)\\n # r1_fastq_filename, valid/invalid error-grid information.\\n r1_filename, r1_filename_error = lib.random_fastq_filename(invalid_data)\\n # r2_fastq_filename, valid/invalid error-grid information.\\n r2_filename, r2_filename_error = lib.random_fastq_filename(invalid_data)\\n # r1_fastq_filepath, valid/invalid error-grid information.\\n r1_filepath, r1_filepath_error = lib.random_filepath(r1_filename, invalid_data)\\n # r2_fastq_filepath, valid/invalid error-grid information.\\n r2_filepath, r2_filepath_error = lib.random_filepath(r2_filename, invalid_data)\\n # fast5_filename, valid/invalid error-grid information.\\n fast5_filename, fast5_filename_error = lib.random_fast5_filename(invalid_data)\\n # fast5_filepath, valid/invalid error-grid information.\\n fast5_filepath, fast5_filepath_error = lib.random_filepath(fast5_filename, invalid_data)\\n # fasta_filename, valid/invalid error-grid information.\\n fasta_filename, fasta_filename_error = lib.random_fasta_filename(invalid_data)\\n # fasta_filepath, valid/invalid error-grid information.\\n fasta_filepath, fasta_filepath_error = lib.random_filepath(fasta_filename, invalid_data)\\n # number_base_pairs, valid/invalid error-grid information.\\n num_bp, num_bp_error = lib.random_bp_num(invalid_data)\\n # consensus_genome_length, valid/invalid error-grid information.\\n cons_genome_len, cons_genome_len_error = lib.random_genome_length(invalid_data)\\n # mean_contig_length, valid/invalid error-grid information.\\n mean_contig_len, mean_contig_len_error = lib.random_contig_length(invalid_data)\\n # n50, valid/invalid error-grid information.\\n n50, n50_error = lib.random_n50(invalid_data)\\n # ns_per_100_kbp, valid/invalid error-grid information.\\n ns_100kbp, ns_100kbp_error = lib.random_ns_100kbp(invalid_data)\\n # reference_genome_accession, valid/invalid error-grid information.\\n ref_genome_accession, ref_genome_accession_error = lib.random_ref_genome(invalid_data)\\n # consensus_sequence_id, valid/invalid error-grid information.\\n cons_seq_id, cons_seq_id_error = lib.random_consensus_seq_id(invalid_data)\\n # consensus_sequence_method, valid/invalid error-grid information.\\n cons_seq_method, cons_seq_method_error = lib.random_consensus_seq_method(invalid_data)\\n # consensus_sequence_filename, valid/invalid error-grid information.\\n cons_seq_filename, cons_seq_filename_error = lib.random_fasta_filename(invalid_data)\\n # consensus_sequence_filepath, valid/invalid error-grid information.\\n cons_seq_filepath, cons_seq_filepath_error = lib.random_filepath(cons_seq_filename, invalid_data)\\n # annotation_feature_table_filename, valid/invalid error-grid information.\\n annot_table_filename, annot_table_filename_error = lib.random_feature_table_filename(invalid_data)\\n # bioinformatics_protocol, valid/invalid error-grid information.\\n biof_protocol, biof_protocol_error = lib.bioinformatics_protocol(invalid_data)\\n \\n ### Pathogen Diagnostic Testing ###\\n \\n # gene_name_1, valid/invalid error-grid information.\\n gene_1, gene_1_error = lib.random_gene(invalid_data)\\n # diagnostic_pcr_protocol_1, valid/invalid error-grid information.\\n pcr_protocol_1, pcr_protocol_1_error = lib.fake_protocol(invalid_data)\\n # diagnostic_pcr_ct_value_1, valid/invalid error-grid information.\\n pcr_ct_1, pcr_ct_1_error = lib.random_pcr_ct_val(invalid_data)\\n # gene_name_2, valid/invalid error-grid information.\\n gene_2, gene_2_error = lib.random_gene(invalid_data)\\n # diagnostic_pcr_protocol_2, valid/invalid error-grid information.\\n pcr_protocol_2, pcr_protocol_2_error = lib.fake_protocol(invalid_data)\\n # diagnostic_pcr_ct_value_2, valid/invalid error-grid information.\\n pcr_ct_2, pcr_ct_2_error = lib.random_pcr_ct_val(invalid_data)\\n \\n ### Contributor Acknowledgement ###\\n \\n # authors, valid/invalid error-grid information.\\n authors, authors_error = lib.authors(invalid_data)\\n \\n ### Dependent IDs ###\\n \\n # specimen_collector_sample_id.\\n spec_col_sample_id, spec_col_sample_id_error = lib.random_specimen_collector_sample_id(\\n geo_loc_country, \\n geo_loc_prov_ter,\\n geo_loc_city,\\n invalid_data)\\n # irida_sample_name.\\n irida_sample_id = spec_col_sample_id\\n # sequence_submitted_by.\\n seq_sub_by = samp_col_by\\n # library_id, valid/invalid error-grid information.\\n library_id, library_id_error = lib.random_library_id(spec_col_sample_id, invalid_data)\\n # isolate.\\n isolate = spec_col_sample_id\\n # assembly_name, valid/invalid error-grid information.\\n assemb_name, assemb_name_error = lib.random_assembly_name(spec_col_sample_id, invalid_data)\\n\\n # Row of generated data organised by column.\\n cols = [spec_col_sample_id,\\n phac_sample_id,\\n irida_sample_id,\\n ub_accession,\\n bp_accession,\\n bs_accession,\\n sra_accession,\\n gb_accession,\\n gisaid_accession,\\n samp_col_by,\\n samp_col_email,\\n samp_col_address,\\n seq_sub_by,\\n seq_sub_email,\\n seq_sub_address,\\n samp_col_date,\\n samp_rec_date,\\n geo_loc_country,\\n geo_loc_prov_ter,\\n geo_loc_city,\\n organism,\\n isolate,\\n p_o_sampling,\\n anat_material,\\n anat_part,\\n body_product,\\n envi_material,\\n envi_site,\\n col_device,\\n col_method,\\n col_protocol,\\n spec_process,\\n lab_host,\\n passage_num,\\n passage_method,\\n biom_extract,\\n host_com_name,\\n host_sci_name,\\n host_health_state,\\n host_health_status,\\n host_disease,\\n host_age,\\n host_gender,\\n host_loc_country,\\n host_sub_id,\\n symp_onset_date,\\n signs_symptoms,\\n loc_exp_country,\\n trav_history,\\n exp_event,\\n library_id,\\n minion_barcode,\\n seq_instrument,\\n seq_prot_name,\\n seq_prot_source,\\n seq_kit_num,\\n amp_pcr_filename,\\n raw_seq_process,\\n seq_depth_avg,\\n assemb_name,\\n assemb_method,\\n assemb_cov_breadth,\\n assemb_cov_depth,\\n r1_filename,\\n r2_filename,\\n r1_filepath,\\n r2_filepath,\\n fast5_filename,\\n fast5_filepath,\\n fasta_filename,\\n fasta_filepath,\\n num_bp,\\n cons_genome_len,\\n mean_contig_len,\\n n50,\\n ns_100kbp,\\n ref_genome_accession,\\n cons_seq_id,\\n cons_seq_method,\\n cons_seq_filename,\\n cons_seq_filepath,\\n annot_table_filename,\\n biof_protocol,\\n gene_1,\\n pcr_protocol_1,\\n pcr_ct_1,\\n gene_2,\\n pcr_protocol_2,\\n pcr_ct_2,\\n authors]\\n\\n # Error grid valid/invalid (error specific) information.\\n grid = ['-', # spec_col_sample_id_error placeholder\\n phac_sample_id_error,\\n '-', # irida_sample_id_error placeholder\\n ub_accession_error,\\n bp_accession_error,\\n bs_accession_error,\\n sra_accession_error,\\n gb_accession_error,\\n gisaid_accession_error,\\n samp_col_by_error,\\n samp_col_email_error,\\n samp_col_address_error,\\n '-', # seq_sub_by_error placeholder\\n seq_sub_email_error,\\n seq_sub_address_error,\\n samp_col_date_error,\\n samp_rec_date_error,\\n geo_loc_country_error,\\n geo_loc_prov_ter_error,\\n geo_loc_city_error,\\n organism_error,\\n '-', # isolate_error placeholder\\n p_o_sampling_error,\\n anat_material_error,\\n anat_part_error,\\n body_product_error,\\n envi_material_error,\\n envi_site_error,\\n col_device_error,\\n col_method_error,\\n col_protocol_error,\\n spec_process_error,\\n lab_host_error,\\n passage_num_error,\\n passage_method_error,\\n biom_extract_error,\\n host_com_name_error,\\n host_sci_name_error,\\n host_health_state_error,\\n host_health_status_error,\\n host_disease_error,\\n host_age_error,\\n host_gender_error,\\n host_loc_country_error,\\n host_sub_id_error,\\n symp_onset_date_error,\\n signs_symptoms_error,\\n loc_exp_country_error,\\n trav_history_error,\\n exp_event_error,\\n library_id_error,\\n minion_barcode_error,\\n seq_instrument_error,\\n seq_prot_name_error,\\n seq_prot_source_error,\\n seq_kit_num_error,\\n amp_pcr_filename_error,\\n raw_seq_process_error,\\n seq_depth_avg_error,\\n assemb_name_error,\\n assemb_method_error,\\n assemb_cov_breadth_error,\\n assemb_cov_depth_error,\\n r1_filename_error,\\n r2_filename_error,\\n r1_filepath_error,\\n r2_filepath_error,\\n fast5_filename_error,\\n fast5_filepath_error,\\n fasta_filename_error,\\n fasta_filepath_error,\\n num_bp_error,\\n cons_genome_len_error,\\n mean_contig_len_error,\\n n50_error,\\n ns_100kbp_error,\\n ref_genome_accession_error,\\n cons_seq_id_error,\\n cons_seq_method_error,\\n cons_seq_filename_error,\\n cons_seq_filepath_error,\\n annot_table_filename_error,\\n biof_protocol_error,\\n gene_1_error,\\n pcr_protocol_1_error,\\n pcr_ct_1_error,\\n gene_2_error,\\n pcr_protocol_2_error,\\n pcr_ct_2_error,\\n authors_error]\\n\\n # return row of data for data file and row of data validity for error grid.\\n return cols, grid\",\n \"def test_resisc45():\\n if not os.path.isdir(os.path.join(DATASET_DIR, \\\"resisc45_split\\\", \\\"3.0.0\\\")):\\n pytest.skip(\\\"resisc45_split dataset not locally available.\\\")\\n\\n for split, size in [(\\\"train\\\", 22500), (\\\"validation\\\", 4500), (\\\"test\\\", 4500)]:\\n batch_size = 16\\n epochs = 1\\n dataset = datasets.resisc45(\\n split=split, epochs=epochs, batch_size=batch_size, dataset_dir=DATASET_DIR,\\n )\\n assert dataset.size == size\\n assert dataset.batch_size == batch_size\\n assert dataset.batches_per_epoch == (\\n size // batch_size + bool(size % batch_size)\\n )\\n\\n x, y = dataset.get_batch()\\n assert x.shape == (batch_size, 256, 256, 3)\\n assert y.shape == (batch_size,)\",\n \"def test_get_sample_ids(self):\\n obs = self.tester._get_sample_ids(self.conn_handler)\\n self.assertEqual(obs, self.exp_sample_ids)\",\n \"def test_get_sample_ids(self):\\n obs = self.tester._get_sample_ids(self.conn_handler)\\n self.assertEqual(obs, self.exp_sample_ids)\",\n \"def test_get_data_array():\\n test_file = os.path.join(DATA_PATH, \\\"paper_test_file.uvh5\\\")\\n test_uv = UVData()\\n test_uv.read(test_file)\\n\\n baseline_array = np.array(list(set(test_uv.baseline_array)))\\n data_array = utils.get_data_array(test_uv, reds=baseline_array)\\n\\n compare_data = np.zeros(\\n (test_uv.Npols, test_uv.Nbls, test_uv.Ntimes, test_uv.Nfreqs),\\n dtype=np.complex64,\\n )\\n\\n pol_array = uvutils.polnum2str(test_uv.polarization_array)\\n for pol_cnt, pol in enumerate(pol_array):\\n for cnt, baseline in enumerate(list(set(test_uv.baseline_array))):\\n ant_1, ant_2 = test_uv.baseline_to_antnums(baseline)\\n compare_data[pol_cnt, cnt] = test_uv.get_data(ant_1, ant_2, pol)\\n\\n compare_data = compare_data.squeeze(axis=0)\\n assert np.allclose(compare_data, data_array)\",\n \"def test1():\\n for test in pkl.load(open(TEST_RESOURCES_DIR / \\\"regression_vault.pkl\\\", \\\"rb\\\"))[:5]:\\n init_dict, rslt = test\\n np.testing.assert_array_equal(run_regression_test(init_dict), rslt)\",\n \"def generate_raiz():\\n\\treturn os.urandom(12)\",\n \"def _generate_id() -> str:\\n return \\\"\\\".join(sample(\\\"abcdefghjkmopqrstuvqxyz\\\", 16))\",\n \"def test_test_ids_request(get_interface_params):\\n from sail_on_client.protocol.localinterface import LocalInterface\\n\\n config_directory, config_name = get_interface_params\\n data_dir = f\\\"{os.path.dirname(__file__)}/data\\\"\\n local_interface = LocalInterface(config_name, config_directory)\\n\\n assumptions_path = os.path.join(os.path.dirname(__file__), \\\"assumptions.json\\\")\\n filename = local_interface.test_ids_request(\\n \\\"OND\\\", \\\"image_classification\\\", \\\"5678\\\", assumptions_path\\n )\\n expected = os.path.join(data_dir, \\\"OND\\\", \\\"image_classification\\\", \\\"test_ids.csv\\\")\\n assert os.stat(expected).st_size > 5\\n assert expected == filename\",\n \"def test_main(data, tmp_path):\\n\\n main(data, tmp_path)\\n\\n FILES = (\\n \\\"gd32f888x(0-1)xx-pinctrl.h\\\",\\n \\\"gd32f888x(2-3)xx-pinctrl.h\\\",\\n \\\"gd32f888y(0-1)xx-pinctrl.h\\\",\\n \\\"gd32f999x(0-1)xx-pinctrl.h\\\",\\n \\\"gd32f999x(2-3)xx-pinctrl.h\\\",\\n \\\"gd32f999y(0-1)xx-pinctrl.h\\\",\\n )\\n\\n for file in FILES:\\n ref_file = data / file\\n gen_file = tmp_path / file\\n\\n assert gen_file.exists()\\n\\n with open(ref_file) as ref, open(gen_file) as gen:\\n assert ref.read() == gen.read()\",\n \"def test_spin_type(fixture_code, generate_structure):\\n code = fixture_code('quantumespresso.pw')\\n structure = generate_structure()\\n\\n with pytest.raises(NotImplementedError):\\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\\n PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=spin_type)\\n\\n builder = PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=SpinType.COLLINEAR)\\n\\n for namespace in [builder.relax['base'], builder.scf, builder.bands]:\\n parameters = namespace['pw']['parameters'].get_dict()\\n assert parameters['SYSTEM']['nspin'] == 2\\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}\",\n \"def _spin_sequence(self):\\n self.return_position = self.motor.position\\n \\n for spin_num in range(self.num_spins):\\n self.taxi()\\n\\n det_pre_acquire(self.detector)\\n self.fly()\\n det_post_acquire(self.detector)\\n\\n while self.detector.hdf1.write_file.value:\\n time.sleep(0.01) # wait for file to be written\\n\\n event = OrderedDict()\\n event[\\\"time\\\"] = time.time()\\n event[\\\"seq_num\\\"] = spin_num + 1\\n event[\\\"data\\\"] = {}\\n event[\\\"timestamps\\\"] = {}\\n for d_item in (self.detector.hdf1.full_file_name,):\\n d = d_item.read()\\n for k, v in d.items():\\n event['data'][k] = v['value']\\n event['timestamps'][k] = v['timestamp']\\n\\n self._data.append(event)\\n\\n self.set(\\\"Return\\\")\\n self._completion_status._finished(success=True)\",\n \"def test_ids(self):\\n # AdapterID inherited from IOAdapter\\n self.assertEqual('553713696', self.sriovs[0].id)\\n self.assertEqual(1, self.sriovs[0].sriov_adap_id)\\n\\n self.assertEqual('553713680', self.sriovs[2].id)\\n self.assertIsNone(self.sriovs[2].sriov_adap_id)\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def generate_fake_data(t0, num_array, period=5820, data_range=[0.0, 24.0],\\n cyclic=True):\\n\\n if cyclic:\\n uts_root = np.mod(t0, period)\\n data = (np.mod(uts_root + num_array, period)\\n * (np.diff(data_range)[0] / np.float64(period))) + data_range[0]\\n else:\\n data = ((t0 + num_array) / period).astype(int)\\n\\n return data\",\n \"def generate_synth_data(n):\",\n \"def test_random_generator(self):\\n gen = random_data()\\n data = [next(gen) for _ in range(100)]\\n self.assertEqual(len(data), 100)\",\n \"def test_return_residue(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_residue(':1')\\n res2 = mol_res_spin.return_residue(selection=':2')\\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1.num, 1)\\n self.assertEqual(res1.name, None)\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2.num, 2)\\n self.assertEqual(res2.name, 'Glu')\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4.num, 4)\\n self.assertEqual(res4.name, 'Pro')\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5.num, -5)\\n self.assertEqual(res5.name, None)\\n self.assertEqual(res5.spin[1].name, 'N5')\",\n \"def test_generate_factoid():\\n generator = mockdata.generate_factoid()\\n for i in range(100):\\n factoid = next(generator)\\n assert factoid[\\\"@id\\\"] == \\\"Factoid %03d\\\" % (i + 1)\\n assert \\\"Person\\\" in factoid[\\\"person\\\"][\\\"@id\\\"]\\n assert \\\"Source\\\" in factoid[\\\"source\\\"][\\\"@id\\\"]\\n assert \\\"statement\\\" in factoid\\n assert factoid[\\\"statement\\\"][\\\"@id\\\"] == \\\"F%dS1\\\" % (i + 1)\",\n \"def test_field_id_range(self):\\n field = '6~8'\\n ref_idx = [1,2,3]\\n self.res=self.run_task(infile=self.rawfile,field=field,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_start_ids_10(self):\\n\\n\\t\\texpected_num_layers = 11\\n\\t\\texpected_ids = np.arange(10,21)\\n\\t\\t# test describe\\n\\t\\tdetails = self.watcher.describe(start_ids=10)\\n\\t\\tprint(\\\"start id = 10\\\", details)\\n\\t\\tactual_ids = details.layer_id.to_numpy().tolist()\\n\\t\\tself.assertTrue(np.array_equal(actual_ids, expected_ids))\\n\\t\\tself.assertEqual(len(expected_ids), expected_num_layers)\\n\\t\\t\\t\\t\\n\\t\\treturn\",\n \"def data_gen(size, p):\\n #print(np.random.get_state()[1][0])\\n random_table = np.random.binomial(size = size, p = p, n = 1)\\n test_array = np.zeros((size, 2), dtype = int)\\n for i in range(size):\\n test_array[i,0] = i\\n test_array[i,1] = random_table[i]\\n return test_array\",\n \"def test_get_sample_ids(self):\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\\\\n parse_metadata_state_descriptions('Study:Twin')), [])\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\\\\n parse_metadata_state_descriptions('Study:Dog')), ['a','b'])\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\\\\n parse_metadata_state_descriptions('Study:*,!Dog')), ['c','d','e'])\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\\\\n parse_metadata_state_descriptions('Study:*,!Dog;BodySite:Stool')), ['e'])\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\\\\n parse_metadata_state_descriptions('BodySite:Stool')), ['a','b','e'])\",\n \"def test_get_sample_ids(self):\\r\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\r\\n parse_metadata_state_descriptions('Study:Twin')), [])\\r\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\r\\n parse_metadata_state_descriptions('Study:Dog')), ['a', 'b'])\\r\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\r\\n parse_metadata_state_descriptions('Study:*,!Dog')), ['c', 'd', 'e'])\\r\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\r\\n parse_metadata_state_descriptions('Study:*,!Dog;BodySite:Stool')), ['e'])\\r\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\r\\n parse_metadata_state_descriptions('BodySite:Stool')), ['a', 'b', 'e'])\",\n \"def test_id(self):\\n b1 = Base()\\n self.assertEqual(b1.id, 1)\\n b2 = Base()\\n self.assertEqual(b2.id, 2)\\n b3 = Base(98)\\n self.assertEqual(b3.id, 98)\\n b4 = Base(256)\\n self.assertEqual(b4.id, 256)\\n b5 = Base()\\n self.assertEqual(b5.id, 3)\\n b6 = Base(-98)\\n self.assertEqual(b6.id, -98)\\n b7 = Base(None)\\n self.assertEqual(b7.id, 4)\\n b8 = Base(4.4)\\n self.assertEqual(b8.id, 4.4)\",\n \"def __test_gen_report_id_check():\\n # all fresh\\n report = dp.Report(md_block, md_block, md_block)\\n assert_report(report) # expected_id_count=5)\\n # 2 fresh\\n report = dp.Report(md_block, md_block_id, md_block)\\n assert_report(report) # expected_id_count=4)\\n # 0 fresh\\n report = dp.Report(md_block_id, dp.Text(\\\"test\\\", name=\\\"test-2\\\"))\\n assert_report(report) # expected_id_count=2)\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_spin_loop_wildcard(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N*'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def random_lottery():\\n\\treturn 0\",\n \"def test_get_tid():\\n tids = []\\n def _foo():\\n mytid = yield GetTid()\\n tids.append(mytid)\\n for i in range(5):\\n yield i\\n\\n scheduler = Scheduler()\\n scheduler.new(_foo())\\n scheduler.new(_foo())\\n scheduler.mainloop()\\n\\n # can we do better than hard code?\\n assert tids == [4, 5]\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def _apply_array_spin1234(self, h1e: 'Nparray', h2e: 'Nparray',\\n h3e: 'Nparray', h4e: 'Nparray') -> 'Nparray':\\n norb = self.norb()\\n tno = 2 * norb\\n assert h4e.shape == (tno, tno, tno, tno, tno, tno, tno, tno)\\n lena = self.lena()\\n lenb = self.lenb()\\n\\n nh1e = numpy.copy(h1e)\\n nh2e = numpy.copy(h2e)\\n nh3e = numpy.copy(h3e)\\n\\n if fqe.settings.use_accelerated_code:\\n _make_nh123(norb, h4e, nh1e, nh2e, nh3e)\\n else:\\n for i in range(norb * 2):\\n for j in range(norb * 2):\\n for k in range(norb * 2):\\n nh1e[:, :] -= h4e[:, j, i, k, j, i, k, :]\\n for l in range(norb * 2):\\n nh2e[i, j, :, :] += (h4e[j, l, i, k, l, k, :, :] +\\n h4e[i, j, l, k, l, k, :, :] +\\n h4e[i, l, k, j, l, k, :, :] +\\n h4e[j, i, k, l, l, k, :, :] +\\n h4e[i, k, j, l, k, :, l, :] +\\n h4e[j, i, k, l, k, :, l, :] +\\n h4e[i, j, k, l, :, k, l, :])\\n nh3e[i, j, k, :, :, :] += (\\n h4e[k, i, j, l, l, :, :, :] +\\n h4e[j, i, l, k, l, :, :, :] +\\n h4e[i, l, j, k, l, :, :, :] +\\n h4e[i, k, j, l, :, l, :, :] +\\n h4e[i, j, l, k, :, l, :, :] +\\n h4e[i, j, k, l, :, :, l, :])\\n\\n (dveca, dvecb) = self.calculate_dvec_spin()\\n evecaa = numpy.zeros((norb, norb, norb, norb, lena, lenb),\\n dtype=self._dtype)\\n evecab = numpy.zeros((norb, norb, norb, norb, lena, lenb),\\n dtype=self._dtype)\\n evecba = numpy.zeros((norb, norb, norb, norb, lena, lenb),\\n dtype=self._dtype)\\n evecbb = numpy.zeros((norb, norb, norb, norb, lena, lenb),\\n dtype=self._dtype)\\n for i in range(norb):\\n for j in range(norb):\\n tmp = self._calculate_dvec_spin_with_coeff(dveca[i, j, :, :])\\n evecaa[:, :, i, j, :, :] = tmp[0][:, :, :, :]\\n evecba[:, :, i, j, :, :] = tmp[1][:, :, :, :]\\n\\n tmp = self._calculate_dvec_spin_with_coeff(dvecb[i, j, :, :])\\n evecab[:, :, i, j, :, :] = tmp[0][:, :, :, :]\\n evecbb[:, :, i, j, :, :] = tmp[1][:, :, :, :]\\n\\n out = self._apply_array_spin123(nh1e, nh2e, nh3e, (dveca, dvecb),\\n (evecaa, evecab, evecba, evecbb))\\n\\n def ncon(A, B):\\n \\\"\\\"\\\"Tensor contraction and transposition corresponding with\\n einsum 'ikmojlnp,mnopxy->ijklxy'\\n \\\"\\\"\\\"\\n return numpy.transpose(numpy.tensordot(A,\\n B,\\n axes=((2, 6, 3, 7), (0, 1, 2,\\n 3))),\\n axes=(0, 2, 1, 3, 4, 5))\\n\\n n = norb # shorter\\n nevecaa = ncon(h4e[:n, :n, :n, :n, :n, :n, :n, :n], evecaa) \\\\\\n + 2.0 * ncon(h4e[:n, :n, :n, n:, :n, :n, :n, n:], evecab) \\\\\\n + ncon(h4e[:n, :n, n:, n:, :n, :n, n:, n:], evecbb)\\n\\n nevecab = ncon(h4e[:n, n:, :n, :n, :n, n:, :n, :n], evecaa) \\\\\\n + 2.0 * ncon(h4e[:n, n:, :n, n:, :n, n:, :n, n:], evecab) \\\\\\n + ncon(h4e[:n, n:, n:, n:, :n, n:, n:, n:], evecbb)\\n\\n nevecbb = ncon(h4e[n:, n:, :n, :n, n:, n:, :n, :n], evecaa) \\\\\\n + 2.0 * ncon(h4e[n:, n:, :n, n:, n:, n:, :n, n:], evecab) \\\\\\n + ncon(h4e[n:, n:, n:, n:, n:, n:, n:, n:], evecbb)\\n\\n dveca2 = numpy.zeros(dveca.shape, dtype=self._dtype)\\n dvecb2 = numpy.zeros(dvecb.shape, dtype=self._dtype)\\n for i in range(norb):\\n for j in range(norb):\\n dveca[:, :, :, :] = nevecaa[i, j, :, :, :, :]\\n dvecb[:, :, :, :] = nevecab[i, j, :, :, :, :]\\n cvec = self._calculate_coeff_spin_with_dvec((dveca, dvecb))\\n dveca2[i, j, :, :] += cvec[:, :]\\n\\n dveca[:, :, :, :] = nevecab[:, :, i, j, :, :]\\n dvecb[:, :, :, :] = nevecbb[i, j, :, :, :, :]\\n cvec = self._calculate_coeff_spin_with_dvec((dveca, dvecb))\\n dvecb2[i, j, :, :] += cvec[:, :]\\n\\n out += self._calculate_coeff_spin_with_dvec((dveca2, dvecb2))\\n return out\",\n \"def test_periodic_boundary_one_ring_rod():\\n\\n n_elems = 5\\n ring_rod = MockRingRod(n_elems)\\n block_structure = MemoryBlockCosseratRod([ring_rod], [0])\\n\\n correct_periodic_boundary_node_idx = np.array(\\n [[0, 6, 7], [5, 1, 2]], dtype=np.int64\\n )\\n correct_periodic_boundary_elem_idx = np.array([[0, 6], [5, 1]], dtype=np.int64)\\n correct_periodic_boundary_voronoi_idx = np.array([[0], [5]], dtype=np.int64)\\n\\n assert_allclose(\\n correct_periodic_boundary_node_idx,\\n block_structure.periodic_boundary_nodes_idx,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_periodic_boundary_elem_idx,\\n block_structure.periodic_boundary_elems_idx,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_periodic_boundary_voronoi_idx,\\n block_structure.periodic_boundary_voronoi_idx,\\n atol=Tolerance.atol(),\\n )\\n\\n correct_start_node_idx = np.array([1], dtype=np.int64)\\n correct_end_node_idx = np.array([6], dtype=np.int64)\\n\\n correct_start_elem_idx = np.array([1], dtype=np.int64)\\n correct_end_elem_idx = np.array([6], dtype=np.int64)\\n\\n correct_start_voronoi_idx = np.array([1], dtype=np.int64)\\n correct_end_voronoi_idx = np.array([6], dtype=np.int64)\\n\\n assert_allclose(\\n correct_start_node_idx,\\n block_structure.start_idx_in_rod_nodes,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_node_idx,\\n block_structure.end_idx_in_rod_nodes,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_start_elem_idx,\\n block_structure.start_idx_in_rod_elems,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_elem_idx,\\n block_structure.end_idx_in_rod_elems,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_start_voronoi_idx,\\n block_structure.start_idx_in_rod_voronoi,\\n atol=Tolerance.atol(),\\n )\\n assert_allclose(\\n correct_end_voronoi_idx,\\n block_structure.end_idx_in_rod_voronoi,\\n atol=Tolerance.atol(),\\n )\",\n \"def test_check_map_primer_pool(self):\\r\\n s = \\\"\\\"\\\"#SampleID\\\\tBarcodeSequence\\\\tLinkerPrimerSequence\\\\tX\\\\tDescription\\r\\n#fake data\\r\\nx\\\\tAA\\\\tAC\\\\t3\\\\tsample_x\\r\\ny\\\\t\\\"AC\\\"\\\\tAT,DC\\\\t4\\\\t\\\"sample_y\\\"\\r\\nz\\\\tGG\\\\tGC\\\\t5\\\\tsample_z\\\"\\\"\\\"\\r\\n f = StringIO(s)\\r\\n f.name = 'test.xls'\\r\\n headers, id_map, barcode_to_sample_id, warnings, errors, \\\\\\r\\n primer_seqs_lens, all_primers = check_map(f,\\r\\n disable_primer_check=False)\\r\\n\\r\\n self.assertEqual(\\r\\n barcode_to_sample_id,\\r\\n {'AA': 'x',\\r\\n 'AC': 'y',\\r\\n 'GG': 'z'})\\r\\n self.assertEqual(errors, [])\\r\\n self.assertEqual(warnings, [])\\r\\n\\r\\n # Returns all possible primers with lengths associated.\\r\\n expected_all_primers = {'AC': 2, 'GC': 2, 'AT': 2, 'TC': 2}\\r\\n self.assertEqual(all_primers, expected_all_primers)\\r\\n\\r\\n # Returns all primers associated with each barcode.\\r\\n expected_primer_seqs_lens = {'AA': {'AC': 2}, 'GG': {'GC': 2},\\r\\n 'AC': {'AC': 2, 'GC': 2, 'AT': 2, 'TC': 2}}\\r\\n\\r\\n self.assertEqual(primer_seqs_lens, expected_primer_seqs_lens)\",\n \"def test_pid_ig1():\\n d = bivariates['and']\\n pid = PID_IG(d, ((0,), (1,)), (2,))\\n assert pid[((0,), (1,))] == pytest.approx(0.08283, abs=1e-4)\\n assert pid[((0,),)] == pytest.approx(0.22845, abs=1e-4)\\n assert pid[((1,),)] == pytest.approx(0.22845, abs=1e-4)\\n assert pid[((0, 1),)] == pytest.approx(0.27155, abs=1e-4)\",\n \"def test_spw_id_list(self):\\n spw = '21,25'\\n ref_idx = [1,2]\\n self.res=self.run_task(infile=self.rawfile,spw=spw,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_hdf5_reader_spinpol_dos(data_regression):\\n from masci_tools.io.parsers.hdf5 import HDF5Reader\\n from masci_tools.io.parsers.hdf5.recipes import FleurDOS\\n\\n TEST_BANDDOS_FILE = os.path.join(HDFTEST_DIR, 'banddos_spinpol_dos.hdf')\\n\\n with HDF5Reader(TEST_BANDDOS_FILE) as reader:\\n data, attrs = reader.read(recipe=FleurDOS)\\n\\n data_regression.check({'datasets': convert_to_pystd(data), 'attributes': convert_to_pystd(attrs)})\",\n \"def generate_subsegment_id():\\n return uuid.uuid4().hex[:16]\",\n \"def get_ids(data, N_max):\\n\\n id_data = data[['molecule_name', 'id']].copy()\\n\\n # write molecules into one line\\n id_data = id_data.groupby('molecule_name').apply(lambda x:\\n x.values.reshape(-1))\\n\\n # pad with nans\\n id_list = []\\n for i in range(len(id_data)):\\n n = N_max*2 - len(id_data[i])\\n id_list.append(np.pad(id_data[i], (0, n), 'constant',\\n constant_values=(0, np.nan)))\\n\\n # build np array and remove molecule names\\n id_data = np.vstack(id_list)\\n del id_list\\n id_data = np.delete(id_data, [2*i for i in range(N_max)], 1)\\n\\n return id_data\",\n \"def generate_run_id(self):\\n r_id_len = 4\\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\\n while r_id in self.cache:\\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\\n return r_id\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.8070005","0.8019214","0.79400337","0.7837104","0.7815383","0.64224803","0.59210145","0.5868475","0.57858336","0.57399845","0.56103945","0.53635967","0.53469247","0.53459364","0.53184336","0.5314746","0.5255449","0.5224802","0.5213441","0.515649","0.5151696","0.5136614","0.5131555","0.5113025","0.51012325","0.51006216","0.5100394","0.5082885","0.50750875","0.50398463","0.50348264","0.5030728","0.50255525","0.5011074","0.5010093","0.5008411","0.50082093","0.50057364","0.50046575","0.49988216","0.4998288","0.49980685","0.49937266","0.49913043","0.49909598","0.49880508","0.4983878","0.49826846","0.49826846","0.49808145","0.49788448","0.49749902","0.49696895","0.4968511","0.49662533","0.4951719","0.49504232","0.49262613","0.49158055","0.48972246","0.48784852","0.4869017","0.48682597","0.48682597","0.48616707","0.4859823","0.4855966","0.48547482","0.4853141","0.4852773","0.48522004","0.4851282","0.48494706","0.4844214","0.48441517","0.4843647","0.48290592","0.4828145","0.48246115","0.48226246","0.48200047","0.481517","0.48114932","0.4811097","0.48002937","0.47986916","0.47982225","0.47931027","0.4785614","0.4785323","0.47828647","0.47811437","0.47751877","0.4769631","0.4768708","0.4766383","0.475974","0.47582865","0.47547317","0.4743201"],"string":"[\n \"0.8070005\",\n \"0.8019214\",\n \"0.79400337\",\n \"0.7837104\",\n \"0.7815383\",\n \"0.64224803\",\n \"0.59210145\",\n \"0.5868475\",\n \"0.57858336\",\n \"0.57399845\",\n \"0.56103945\",\n \"0.53635967\",\n \"0.53469247\",\n \"0.53459364\",\n \"0.53184336\",\n \"0.5314746\",\n \"0.5255449\",\n \"0.5224802\",\n \"0.5213441\",\n \"0.515649\",\n \"0.5151696\",\n \"0.5136614\",\n \"0.5131555\",\n \"0.5113025\",\n \"0.51012325\",\n \"0.51006216\",\n \"0.5100394\",\n \"0.5082885\",\n \"0.50750875\",\n \"0.50398463\",\n \"0.50348264\",\n \"0.5030728\",\n \"0.50255525\",\n \"0.5011074\",\n \"0.5010093\",\n \"0.5008411\",\n \"0.50082093\",\n \"0.50057364\",\n \"0.50046575\",\n \"0.49988216\",\n \"0.4998288\",\n \"0.49980685\",\n \"0.49937266\",\n \"0.49913043\",\n \"0.49909598\",\n \"0.49880508\",\n \"0.4983878\",\n \"0.49826846\",\n \"0.49826846\",\n \"0.49808145\",\n \"0.49788448\",\n \"0.49749902\",\n \"0.49696895\",\n \"0.4968511\",\n \"0.49662533\",\n \"0.4951719\",\n \"0.49504232\",\n \"0.49262613\",\n \"0.49158055\",\n \"0.48972246\",\n \"0.48784852\",\n \"0.4869017\",\n \"0.48682597\",\n \"0.48682597\",\n \"0.48616707\",\n \"0.4859823\",\n \"0.4855966\",\n \"0.48547482\",\n \"0.4853141\",\n \"0.4852773\",\n \"0.48522004\",\n \"0.4851282\",\n \"0.48494706\",\n \"0.4844214\",\n \"0.48441517\",\n \"0.4843647\",\n \"0.48290592\",\n \"0.4828145\",\n \"0.48246115\",\n \"0.48226246\",\n \"0.48200047\",\n \"0.481517\",\n \"0.48114932\",\n \"0.4811097\",\n \"0.48002937\",\n \"0.47986916\",\n \"0.47982225\",\n \"0.47931027\",\n \"0.4785614\",\n \"0.4785323\",\n \"0.47828647\",\n \"0.47811437\",\n \"0.47751877\",\n \"0.4769631\",\n \"0.4768708\",\n \"0.4766383\",\n \"0.475974\",\n \"0.47582865\",\n \"0.47547317\",\n \"0.4743201\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.80017376"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":81487,"cells":{"query":{"kind":"string","value":"Fifth test of the spin ID generation function. The function tested is pipe_control.mol_res_spin.generate_spin_id_data_array()."},"document":{"kind":"string","value":"def test_generate_spin_id_data_array5(self):\n\n # The data.\n data = ['Ap4Aase', '1', 'GLY', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5)\n\n # Test the string.\n self.assertEqual(id, '#Ap4Aase:1@234')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_generate_spin_id_data_array6(self):\n\n # The data.\n data = ['1', 'GLY', None, None]\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')","def test_generate_spin_id_data_array1(self):\n\n # The data.\n data = ['1', 'GLY']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')","def test_generate_spin_id_data_array2(self):\n\n # The data.\n data = ['1', 'GLY', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2, spin_num_col=3, spin_name_col=4)\n\n # Test the string.\n self.assertEqual(id, ':1@234')","def test_generate_spin_id_data_array4(self):\n\n # The data.\n data = ['Ap4Aase', '1', 'GLY']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3)\n\n # Test the string.\n self.assertEqual(id, '#Ap4Aase:1')","def test_generate_spin_id_data_array3(self):\n\n # The data.\n data = ['Ap4Aase', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=None, res_name_col=None, spin_num_col=2, spin_name_col=3)\n\n # Test the string.\n self.assertEqual(id, '#Ap4Aase@234')","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def test_id_array(self):\n arr = vtk.vtkIdTypeArray()\n arr.SetNumberOfTuples(10)\n for i in range(10):\n arr.SetValue(i, i)\n\n np = array_handler.vtk2array(arr)\n self.assertEqual(numpy.all(np == range(10)), True)","def test_spin_loop(self):\n\n # Spin data.\n select = [1, 0]\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, 'N5')\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 2)","def test_random_id(self):\r\n ids = \\\r\n \"R27DLI_4812 R27DLI_600 R27DLI_727 U1PLI_403 U1PLI_8969\".split(\r\n )\r\n assert random_id(ids, {}) in ids\r\n # just test we got something from the list, don't add stochastic test\r","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_create_template(self):\n m_size = 10\n data = ecn.IDData(m_size)\n self.assertEqual(np.shape(data.ID_MATRIX), (m_size, m_size))\n self.assertEqual(sum(sum(data.ID_MATRIX)), m_size)\n self.assertTrue((sum(data.ID_MATRIX) == np.ones(m_size)).all())\n print('Finished testing template\\n')","def createArrayFunc(self):\r\n minVal = int(self.spinBoxMin_2.value())\r\n maxVal = int(self.spinBoxMax_2.value())\r\n arrayLength = int(self.spinBoxLength_2.value())\r\n different = maxVal - minVal\r\n if self.checkBoxNoRepeate_2.isChecked():\r\n if different > arrayLength:\r\n def unique_rand(initial, limit, total):\r\n data = []\r\n i = 0\r\n while i < total:\r\n number = numpy.random.randint(initial, limit)\r\n if number not in data:\r\n data.append(number)\r\n i += 1\r\n return data\r\n\r\n self.UnsortedArray_2 = unique_rand(minVal, maxVal, arrayLength)\r\n else:\r\n err = \"Array length must be greater than difference between limits\"\r\n self.labelUnsortedArray_2.setText(str(err))\r\n\r\n else:\r\n self.UnsortedArray_2 = numpy.random.randint(minVal, maxVal, arrayLength)\r\n self.labelUnsortedArray_2.setText(str(self.UnsortedArray_2))\r\n self.SortedArray_2 = Insertion.sorting(self.UnsortedArray_2)\r\n self.labelSortedArray_2.setText(str(self.SortedArray_2))\r\n binaryMax = int(self.spinBoxMax_2.value())\r\n binaryMin = int(self.spinBoxMin_2.value())\r\n self.spinBoxBinary.setMaximum(binaryMax)\r\n self.spinBoxBinary.setMinimum(binaryMin)\r\n self.spinBoxIthSmallest.setMaximum(arrayLength + 1)","def test_scan_id_list(self):\n scan = '15,17'\n ref_idx = [0,3]\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_spin_loop_no_selection(self):\n\n # Spin data.\n select = [0, 1, 0, 0, 1, 1, 0, 1]\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 8)","def test_uuid():\n for _ in range(1000):\n uuid = uuid_generator()\n assert len(uuid) == 36\n assert uuid.count('-') == 4","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_arr2vtkIdList(self):\n a = [1, 2, 3, 4, 5]\n p = array_handler.array2vtkIdList(a)\n for i, j in enumerate(a): \n self.assertEqual(p.GetId(i), j)\n p = vtk.vtkIdList()\n ident = id(p)\n p = array_handler.array2vtkIdList(numpy.array(a), p)\n for i, j in enumerate(a): \n self.assertEqual(p.GetId(i), j)\n self.assertEqual(id(p), ident)\n \n self.assertRaises(AssertionError, array_handler.array2vtkIdList,\n [[1,2,3]])","def generate_T(number_obeservations):\n T = np.random.randint(0, 2, (number_obeservations,1))\n return T","def test_random_integers(self):\r\n # Check over two calls to see if the random state is correctly updated.\r\n random = RandomStreams(utt.fetch_seed())\r\n fn = function([], random.random_integers((20, 20), -5, 5))\r\n fn_val0 = fn()\r\n fn_val1 = fn()\r\n\r\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\r\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\r\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\r\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\r\n\r\n assert numpy.all(fn_val0 == numpy_val0)\r\n assert numpy.all(fn_val1 == numpy_val1)","def test_random_integers(self):\r\n # Check over two calls to see if the random state is correctly updated.\r\n m = Module()\r\n m.random = RandomStreams(utt.fetch_seed())\r\n m.fn = Method([], m.random.random_integers((20,20), -5, 5))\r\n\r\n made = m.make()\r\n made.random.initialize()\r\n fn_val0 = made.fn()\r\n fn_val1 = made.fn()\r\n\r\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\r\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\r\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\r\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\r\n\r\n assert numpy.all(fn_val0 == numpy_val0)\r\n assert numpy.all(fn_val1 == numpy_val1)","def test_run_sim_1():\n rnd = rand.Arrivals(36, 41)\n sim.run_sim(3, 2, 5, 6, 22, rnd)","def test_id_rot():\n assert_array_almost_equal(pr.R_id, pr.matrix_from_axis_angle(pr.a_id))\n assert_array_almost_equal(pr.R_id, pr.matrix_from_quaternion(pr.q_id))\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_xyz(pr.e_xyz_id))\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_zyx(pr.e_zyx_id))","def test_run_sim():\n rnd = rand.Arrivals(31, 40)\n sim.run_sim(2, 1, 3, 4, 24, rnd)","def test_scan_id_range(self):\n scan = '16~17'\n ref_idx = [1,2,3]\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_generate(self):\n cant_interations = int(random()*100)\n for i in range(cant_interations):\n number = self.sudoku.generate() # Generate number\n self.assertGreaterEqual(number, 0) # number >= 0\n self.assertLessEqual(number, 8) # number <= 8","def test_spin_type(get_pdos_generator_inputs):\n with pytest.raises(NotImplementedError):\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=spin_type)\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=SpinType.COLLINEAR)\n for namespace in [builder.scf, builder.nscf]:\n parameters = namespace['pw']['parameters'].get_dict()\n assert parameters['SYSTEM']['nspin'] == 2\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}","def test_generateuuids(self):\n ret1 = {\"message\": \"No Random.org api key or api version found.\", \"res\": False}\n self.assertDictEqual(random_org.generateUUIDs(), ret1)\n\n ret2 = {\"message\": \"Required argument, number is missing.\", \"res\": False}\n self.assertDictEqual(\n random_org.generateUUIDs(api_key=\"peW\", api_version=\"1\"), ret2\n )\n\n ret3 = {\"message\": \"Number of UUIDs must be between 1 and 1000\", \"res\": False}\n self.assertDictEqual(\n random_org.generateUUIDs(api_key=\"peW\", api_version=\"1\", number=\"5\"), ret3\n )\n\n ret3 = {\"message\": \"Parameter 'apiKey' is malformed\", \"res\": False}\n self.assertDictEqual(\n random_org.generateUUIDs(api_key=\"peW\", api_version=\"1\", number=5), ret3\n )","def test_pol_id_list(self):\n pol = '0,1'\n ref_idx = []\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def generate_new_ids(ids: np.array, n_required: int) -> np.array:\n\n current_max_id = ids.max()\n new_ids = np.arange(n_required) + current_max_id + 1\n\n return new_ids","def _get_rand_array(self):\n pass","def _apply_array_spin123(self,\n h1e: 'Nparray',\n h2e: 'Nparray',\n h3e: 'Nparray',\n dvec: Optional[Tuple['Nparray', 'Nparray']] = None,\n evec: Optional[Tuple['Nparray', 'Nparray', 'Nparray', 'Nparray']] \\\n = None) -> 'Nparray':\n norb = self.norb()\n assert h3e.shape == (norb * 2,) * 6\n assert not (dvec is None) ^ (evec is None)\n\n from1234 = (dvec is not None) and (evec is not None)\n\n nh1e = numpy.copy(h1e)\n nh2e = numpy.copy(h2e)\n\n for i in range(norb * 2):\n for j in range(norb * 2):\n for k in range(norb * 2):\n nh2e[j, k, :, :] += (-h3e[k, j, i, i, :, :] -\n h3e[j, i, k, i, :, :] -\n h3e[j, k, i, :, i, :])\n\n nh1e[:, :] += h3e[:, i, j, i, j, :]\n\n out = self._apply_array_spin12_halffilling(nh1e, nh2e)\n\n n = norb # This is just shorter\n if not from1234:\n symfac = 2.0\n axes = ((1, 3), (0, 1))\n (odveca, odvecb) = self.calculate_dvec_spin()\n dveca = numpy.zeros_like(odveca)\n dvecb = numpy.zeros_like(odvecb)\n\n for i in range(norb):\n for j in range(norb):\n evecaa, _ = self._calculate_dvec_spin_with_coeff(\n odveca[i, j, :, :])\n evecab, evecbb = self._calculate_dvec_spin_with_coeff(\n odvecb[i, j, :, :])\n\n dveca += numpy.tensordot(h3e[:n, :n, i, :n, :n, j],\n evecaa,\n axes=axes)\n dveca += numpy.tensordot(h3e[:n, :n, n + i, :n, :n, n + j],\n evecab,\n axes=axes) * symfac\n dveca += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\n evecbb,\n axes=axes)\n\n dvecb += numpy.tensordot(h3e[n:, :n, i, n:, :n, j],\n evecaa,\n axes=axes)\n dvecb += numpy.tensordot(h3e[n:, :n, n + i, n:, :n, n + j],\n evecab,\n axes=axes) * symfac\n dvecb += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\n evecbb,\n axes=axes)\n else:\n symfac = 1.0\n axes = ((1, 4, 2, 5), (0, 1, 2, 3)) # type: ignore\n dveca, dvecb = dvec # type: ignore\n evecaa, evecab, evecba, evecbb = evec # type: ignore\n\n dveca = numpy.tensordot(h3e[:n, :n, :n, :n, :n, :n],\n evecaa, axes=axes) \\\n + numpy.tensordot(h3e[:n, :n, n:, :n, :n, n:],\n evecab, axes=axes) * symfac \\\n + numpy.tensordot(h3e[:n, n:, n:, :n, n:, n:],\n evecbb, axes=axes) + \\\n + numpy.tensordot(h3e[:n, n:, :n, :n, n:, :n],\n evecba, axes=axes)\n\n dvecb = numpy.tensordot(h3e[n:, :n, :n, n:, :n, :n],\n evecaa, axes=axes) \\\n + numpy.tensordot(h3e[n:, :n, n:, n:, :n, n:],\n evecab, axes=axes) * symfac \\\n + numpy.tensordot(h3e[n:, n:, n:, n:, n:, n:],\n evecbb, axes=axes) + \\\n + numpy.tensordot(h3e[n:, n:, :n, n:, n:, :n],\n evecba, axes=axes)\n\n out -= self._calculate_coeff_spin_with_dvec((dveca, dvecb))\n return out","def test_split_id_otp(self):\n public_id, otp, = pyhsm.yubikey.split_id_otp(\"ft\" * 16)\n self.assertEqual(public_id, '')\n self.assertEqual(otp, \"ft\" * 16)\n\n public_id, otp, = pyhsm.yubikey.split_id_otp(\"cc\" + \"ft\" * 16)\n self.assertEqual(public_id, 'cc')\n self.assertEqual(otp, \"ft\" * 16)","def gen_data(min_coord, max_coord, size):\r\n data = np.random.randint(min_coord, max_coord, size)\r\n return data","def test_SampleIds(self):\r\n exp = [\"PC.354\", \"PC.355\", \"PC.356\", \"PC.481\", \"PC.593\", \"PC.607\",\r\n \"PC.634\", \"PC.635\", \"PC.636\"]\r\n obs = self.overview_map.SampleIds\r\n self.assertEqual(obs, exp)\r\n\r\n obs = self.no_metadata.SampleIds\r\n self.assertEqual(obs, exp)\r\n\r\n obs = self.empty_map.SampleIds\r\n self.assertEqual(obs, [])","def genNumID(size):\n\tid = \"\"\n\tfor i in range(size):\n\t\tid = id + selectRandomFromList(numTokens)\n\treturn id","def test_spin_loop_wildcard(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N*'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_SampleIds(self):\n exp = [\"PC.354\", \"PC.355\", \"PC.356\", \"PC.481\", \"PC.593\", \"PC.607\",\n \"PC.634\", \"PC.635\", \"PC.636\"]\n obs = self.overview_map.SampleIds\n self.assertEqual(obs, exp)\n\n obs = self.no_metadata.SampleIds\n self.assertEqual(obs, exp)\n\n obs = self.empty_map.SampleIds\n self.assertEqual(obs, [])","def test_weyl_specialize_id(self):\n a, b, c = 0.0, 0.0, 0.0\n for da, db, dc in DELTAS:\n for k1l, k1r, k2l, k2r in K1K2SB:\n k1 = np.kron(k1l.data, k1r.data)\n k2 = np.kron(k2l.data, k2r.data)\n self.check_two_qubit_weyl_specialization(\n k1 @ Ud(a + da, b + db, c + dc) @ k2,\n 0.999,\n TwoQubitWeylIdEquiv,\n {\"rz\": 4, \"ry\": 2},\n )","def generate_raiz():\n\treturn os.urandom(12)","def myID() -> np.int:\r\n return 304976335","def myID() -> np.int:\r\n return 304976335","def generate_synth_data(n):","def test_spin_loop_multiatom(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_get_ids(civic, main_data, updated_data):\n assert len(civic._get_ids(main_data['assertions'])) == 0\n assert len(civic._get_ids(main_data['variants'])) == 1\n assert len(civic._get_ids(main_data['genes'])) == 2\n assert len(civic._get_ids(main_data['evidence'])) == 1\n\n assert len(civic._get_ids(updated_data['assertions'])) == 1\n assert len(civic._get_ids(updated_data['variants'])) == 1\n assert len(civic._get_ids(updated_data['genes'])) == 1\n assert len(civic._get_ids(updated_data['evidence'])) == 1","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_returned_num_in_random_nums(self):\n self._setup_random_gen([1.], [42])\n self.assertEqual(self._random_gen.next_num(), 42)","def test_kf_id():\n\n for _ in range(1000):\n prefix = ''.join(random.sample(string.ascii_uppercase, 2))\n kf_id = kf_id_generator(prefix)()\n assert kf_id[:2] == prefix\n assert len(kf_id) == 11\n assert kf_id[2] == '_'\n\n assert 'I' not in kf_id[2:]\n assert 'L' not in kf_id[2:]\n assert 'O' not in kf_id[2:]\n assert 'U' not in kf_id[2:]\n\n assert re.search(r'^'+prefix+r'_[A-HJ-KM-NP-TV-Z0-9]{8}', kf_id)","def test_spin_type(fixture_code, generate_structure):\n code = fixture_code('quantumespresso.pw')\n structure = generate_structure()\n\n with pytest.raises(NotImplementedError):\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\n PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=spin_type)\n\n builder = PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=SpinType.COLLINEAR)\n\n for namespace in [builder.relax['base'], builder.scf, builder.bands]:\n parameters = namespace['pw']['parameters'].get_dict()\n assert parameters['SYSTEM']['nspin'] == 2\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}","def test_brains_id_get(self):\n pass","def test_if_array_is_good(self):\n testing_param = random.randint(1, 100)\n self.assertEqual(self.exercice.main(testing_param),\n list(range(2, testing_param+1, 2)))","def test_get_tid():\n tids = []\n def _foo():\n mytid = yield GetTid()\n tids.append(mytid)\n for i in range(5):\n yield i\n\n scheduler = Scheduler()\n scheduler.new(_foo())\n scheduler.new(_foo())\n scheduler.mainloop()\n\n # can we do better than hard code?\n assert tids == [4, 5]","def test_scan_id_exprlist(self):\n scan = '15,>16'\n ref_idx = [0,3]\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_start_ids_10(self):\n\n\t\texpected_num_layers = 11\n\t\texpected_ids = np.arange(10,21)\n\t\t# test describe\n\t\tdetails = self.watcher.describe(start_ids=10)\n\t\tprint(\"start id = 10\", details)\n\t\tactual_ids = details.layer_id.to_numpy().tolist()\n\t\tself.assertTrue(np.array_equal(actual_ids, expected_ids))\n\t\tself.assertEqual(len(expected_ids), expected_num_layers)\n\t\t\t\t\n\t\treturn","def random_lottery():\n\treturn 0","def test_sampleId_pairs(self):\r\n # expected values\r\n dose_vps = \\\r\n [('1xDose', '2xDose'), ('1xDose', 'Control'),\r\n ('2xDose', 'Control')]\r\n ttd_vps = \\\r\n [('31', '21'), ('31', '55'), ('31', '67'), ('21', '55'),\r\n ('21', '67'), ('55', '67')]\r\n dose_sids = \\\r\n [(['Sam1', 'Sam2', 'Sam6'], ['Sam3', 'Sam4']),\r\n (['Sam1', 'Sam2', 'Sam6'], ['Sam5']),\r\n (['Sam3', 'Sam4'], ['Sam5'])]\r\n ttd_sids = \\\r\n [(['Sam1'], ['Sam3']),\r\n (['Sam1'], ['Sam4', 'Sam6']),\r\n (['Sam1'], ['Sam2', 'Sam5']),\r\n (['Sam3'], ['Sam4', 'Sam6']),\r\n (['Sam3'], ['Sam2', 'Sam5']),\r\n (['Sam4', 'Sam6'], ['Sam2', 'Sam5'])]\r\n\r\n # observed values\r\n obs_dose_sids, obs_dose_vps = sampleId_pairs(self.mapping_data,\r\n self.rarefaction_data, 'Dose')\r\n obs_ttd_sids, obs_ttd_vps = sampleId_pairs(self.mapping_data,\r\n self.rarefaction_data, 'TTD')\r\n\r\n # sort -- order is unimportant and depends on way presented in mf\r\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\r\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())\r\n self.assertEqual(ttd_vps.sort(), obs_ttd_vps.sort())\r\n self.assertEqual(ttd_sids.sort(), obs_ttd_sids.sort())\r\n\r\n # check errors when no samples had this category\r\n self.assertRaises(ValueError, sampleId_pairs, self.mapping_data,\r\n self.rarefaction_data, 'DNE')\r\n\r\n # check no error if map file has more sampleids than rarefaction data\r\n superset_mf = \\\r\n ['#SampleID\\tDose\\tLinkerPrimerSequence\\tWeight\\tTTD\\tDescription',\r\n '#Comment Line',\r\n 'Sam1\\t1xDose\\tATCG\\tHigh\\t31\\ts1_desc',\r\n 'Sam2\\t1xDose\\tACCG\\tLow\\t67\\ts2_desc',\r\n 'Sam3\\t2xDose\\tACGT\\tMed\\t21\\ts3_desc',\r\n 'Sam4\\t2xDose\\tAACG\\tLow\\t55\\ts4_desc',\r\n 'Sam5\\tControl\\tCGTC\\tLow\\t67\\ts5_desc',\r\n 'Sam6\\t1xDose\\tACCT\\tLow\\t55\\ts6_desc',\r\n 'Sam7\\t4xDose\\tACCT\\tLow\\t55\\ts7_desc',\r\n 'Sam8\\t3xDose\\tACCT\\tLow\\t55\\ts8_desc',\r\n 'Sam9\\t1xDose\\tACCT\\tLow\\t55\\ts9_desc']\r\n # (mf, comments)\r\n superset_mf = parse_mapping_file_to_dict(superset_mf)[0]\r\n obs_dose_sids, obs_dose_vps = sampleId_pairs(superset_mf,\r\n self.rarefaction_data, 'Dose')\r\n\r\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\r\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())","def test_pol_id_range(self):\n pol = '0~1'\n ref_idx = []\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_test_ids_request(get_interface_params):\n from sail_on_client.protocol.localinterface import LocalInterface\n\n config_directory, config_name = get_interface_params\n data_dir = f\"{os.path.dirname(__file__)}/data\"\n local_interface = LocalInterface(config_name, config_directory)\n\n assumptions_path = os.path.join(os.path.dirname(__file__), \"assumptions.json\")\n filename = local_interface.test_ids_request(\n \"OND\", \"image_classification\", \"5678\", assumptions_path\n )\n expected = os.path.join(data_dir, \"OND\", \"image_classification\", \"test_ids.csv\")\n assert os.stat(expected).st_size > 5\n assert expected == filename","def test_create_tornado_id(self):\n\n this_id_string = tornado_io.create_tornado_id(\n start_time_unix_sec=TORNADO_START_TIME_UNIX_SEC,\n start_latitude_deg=TORNADO_START_LATITUDE_DEG,\n start_longitude_deg=TORNADO_START_LONGITUDE_DEG)\n\n self.assertTrue(this_id_string == TORNADO_ID_STRING)","def generate_mixture_indicator(number_obeservations):\n mixture_indicator = np.random.randint(0, 2, (number_obeservations,1))\n return mixture_indicator","def _spin_sequence(self):\n self.return_position = self.motor.position\n \n for spin_num in range(self.num_spins):\n self.taxi()\n\n det_pre_acquire(self.detector)\n self.fly()\n det_post_acquire(self.detector)\n\n while self.detector.hdf1.write_file.value:\n time.sleep(0.01) # wait for file to be written\n\n event = OrderedDict()\n event[\"time\"] = time.time()\n event[\"seq_num\"] = spin_num + 1\n event[\"data\"] = {}\n event[\"timestamps\"] = {}\n for d_item in (self.detector.hdf1.full_file_name,):\n d = d_item.read()\n for k, v in d.items():\n event['data'][k] = v['value']\n event['timestamps'][k] = v['timestamp']\n\n self._data.append(event)\n\n self.set(\"Return\")\n self._completion_status._finished(success=True)","def _generate_id() -> str:\n return \"\".join(sample(\"abcdefghjkmopqrstuvqxyz\", 16))","def test_ids(self):\n # AdapterID inherited from IOAdapter\n self.assertEqual('553713696', self.sriovs[0].id)\n self.assertEqual(1, self.sriovs[0].sriov_adap_id)\n\n self.assertEqual('553713680', self.sriovs[2].id)\n self.assertIsNone(self.sriovs[2].sriov_adap_id)","def test_residue_loop(self):\n\n # Loop over the residues.\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\n # Test the selection.\n self.assertEqual(res.num, 2)\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)","def get_refresh_ids(self):\n ids = []\n for bucket in self.router.lonely_buckets():\n rid = random.randint(*bucket.range).to_bytes(20, byteorder='big')\n ids.append(rid)\n return ids","def test_rand_func2(self):\n for i in range(0, 100000):\n num = random.randint(0, 32535143990)\n func2_comp(num)","def test_arbitrary_rotation(self):\n \n # This test is run a bunch of times on various intervals, ranging from 50% to 1/6\n\t\t# (16.667%).\n for i in range(2, 7):\n \n interval = 1 / i # The amount to increase each qubit's probability by, relative to the previous qubit\n step_string = \"{:.4f}\".format(100 / i) # The decimal representation of the interval, as a percent\n target_probabilities = [0] * (i + 1) # This will store the desired probabilities of each qubit\n for j in range(0, i + 1):\n target_probability = j * interval\n target_probabilities[j] = target_probability\n\n # Run the test\n self.run_test(self.arbitrary_rotation_function, f\"Rotation with steps of 1/{i} ({step_string}%)\", 2000, target_probabilities, 0.05)","def generaterandomindices(dataSize, percentTest):\n\n TrainIndices = np.array([])\n while TrainIndices.__len__() < int(percentTest * dataSize):\n # Randomly select an index value and store it. If it has already been chosen, pick again.\n index = int(random.random() * dataSize)\n if not TrainIndices.__contains__(index):\n TrainIndices = np.append(TrainIndices, [index])\n\n # For aesthetic purposes:\n TrainIndices = np.sort(TrainIndices)\n\n return TrainIndices","def get_test_split(self, fraction=0.1):\n rng = np.random.default_rng(42)\n test_size = int(round(len(self.all_asset_ids) * fraction))\n test_ids = rng.choice(self.all_asset_ids, size=test_size, replace=False)\n train_ids = [i for i in self.all_asset_ids if i not in test_ids]\n return train_ids, test_ids","def test_random_generator(self):\n gen = random_data()\n data = [next(gen) for _ in range(100)]\n self.assertEqual(len(data), 100)","def gen_all_arms_ids(\n self,\n ) -> None:\n num_all_arms = (\n self.num_unique_batches * self.batch_size * self.num_arms_per_episode\n )\n all_arms_ids = torch.randperm(num_all_arms)\n self.all_unique_arm_ids = all_arms_ids.reshape(\n [self.num_unique_batches, self.batch_size, self.num_arms_per_episode]\n )\n assert self.all_unique_arm_ids.ndim == 3\n return","def generate_license_plate(self, num):\n license_plate = []\n for _ in range(num):\n license_plate.append(self.fake.license_plate())\n return license_plate","def test_field_id_list(self):\n field = '5,8'\n ref_idx = [0,3]\n self.res=self.run_task(infile=self.rawfile,field=field,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_get_sample_ids(self):\n obs = self.tester._get_sample_ids(self.conn_handler)\n self.assertEqual(obs, self.exp_sample_ids)","def test_get_sample_ids(self):\n obs = self.tester._get_sample_ids(self.conn_handler)\n self.assertEqual(obs, self.exp_sample_ids)","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_15(self):\n\t self.assertTrue(prime_generator(15), [2, 3, 5, 7, 11, 13])","def create_code():\n\n code = [0, 0, 0, 0]\n\n for i in range(4):\n value = random.randint(1, 8) # 8 possible digits\n while value in code:\n value = random.randint(1, 8) # 8 possible digits\n code[i] = value\n \n #print(code)\n return code","def test_generate_mine_sequence(self):\n mine_list = utils.generate_mine_sequence(1)\n self.assertEqual(len(mine_list), utils.MINE_COUNT)","def generate_fake_data(t0, num_array, period=5820, data_range=[0.0, 24.0],\n cyclic=True):\n\n if cyclic:\n uts_root = np.mod(t0, period)\n data = (np.mod(uts_root + num_array, period)\n * (np.diff(data_range)[0] / np.float64(period))) + data_range[0]\n else:\n data = ((t0 + num_array) / period).astype(int)\n\n return data","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def spinWheel():\n\tt = random.randrange(8)\n\tif t == 7:\n\t\treturn \"00\"\n\treturn str(t)","def NSK129_user_ids():\n return [\n707057500045751944,\n707057500045752170,\n707057500045752255,\n707057500045752231,\n707057500045752217,\n707057500045752194,\n707057500045752156,\n707057500045752132,\n707057500045752118,\n707057500045752088,\n707057500045752064,\n707057500045752057,\n707057500045752033,\n707057500045752002,\n707057500045751982,\n707057500045751975,\n707057500045751937,\n707057500045751913,\n707057500045745844,\n707057500045745851,\n707057500045745929,\n707057500045745936,\n707057500045746001,\n707057500045746018,\n707057500045745868,\n707057500045745875,\n707057500045745943,\n707057500045745950,\n707057500045746025,\n707057500045746032,\n707057500045745882,\n707057500045745837,\n707057500045745899,\n707057500045745974,\n707057500045746049,\n707057500045746056,\n707057500045745905,\n707057500045745981,\n707057500045745998,\n707057500045746063,\n707057500045746070,\n707057500045745912,\n707057500045745639,\n707057500045745707,\n707057500045745714,\n707057500045745783,\n707057500045745790,\n707057500045745646,\n707057500045745653,\n707057500045745738,\n707057500045745806,\n707057500045745615,\n707057500045745776,\n707057500045745622,\n707057500045745578,\n707057500045745585,\n707057500045745592,\n707057500045745813,\n707057500045745660,\n707057500045745684,\n707057500045745721,\n707057500045745769,\n707057500045745677,\n707057500045745745,\n707057500045745752,\n707057500045745608,\n707057500045750442,\n707057500045752613,\n707057500045752606,\n707057500045752163,\n707057500045752200,\n707057500045752224,\n707057500045752149,\n707057500045752187,\n707057500045752293,\n707057500045752286,\n707057500045752071,\n707057500045752040,\n707057500045752095,\n707057500045752125,\n707057500045752101,\n707057500045752026,\n707057500045752279,\n707057500045752262,\n707057500045751814,\n707057500045751807,\n707057500045751890,\n707057500045751883,\n707057500045751876,\n707057500045751869,\n707057500045751821,\n707057500045751838,\n707057500045751845,\n707057500045751852,\n707057500045751999,\n707057500045751951,\n707057500045752019,\n707057500045751920,\n707057500045751968,\n707057500045751906,\n707057500045745691,\n707057500045745967]","def iv_gen():\r\n rndiv = os.urandom(16)\r\n return rndiv","def test_resisc45():\n if not os.path.isdir(os.path.join(DATASET_DIR, \"resisc45_split\", \"3.0.0\")):\n pytest.skip(\"resisc45_split dataset not locally available.\")\n\n for split, size in [(\"train\", 22500), (\"validation\", 4500), (\"test\", 4500)]:\n batch_size = 16\n epochs = 1\n dataset = datasets.resisc45(\n split=split, epochs=epochs, batch_size=batch_size, dataset_dir=DATASET_DIR,\n )\n assert dataset.size == size\n assert dataset.batch_size == batch_size\n assert dataset.batches_per_epoch == (\n size // batch_size + bool(size % batch_size)\n )\n\n x, y = dataset.get_batch()\n assert x.shape == (batch_size, 256, 256, 3)\n assert y.shape == (batch_size,)","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def data(i):\n m = i*100\n return [random.randint(0, m) for j in range(i)]","def test_id_get(mocker):\n mocker.patch('serial.Serial.open')\n mocker.patch('serial.Serial.flushInput')\n css = mocker.patch('pysds011.driver.SDS011.cmd_set_sleep')\n css.return_value = True\n cfv = mocker.patch('pysds011.driver.SDS011.cmd_firmware_ver')\n cfv.return_value = {'id': b'\\x12\\x34', 'paperino': 'maciomicio'}\n runner = CliRunner()\n result = runner.invoke(main, ['id'])\n\n calls = [call(0, id=b'\\xff\\xff'), call(1, id=b'\\xff\\xff')]\n css.assert_has_calls(calls, any_order=False)\n\n assert '12' in result.output and '34' in result.output\n assert result.exit_code == 0","def test_generate_factoid():\n generator = mockdata.generate_factoid()\n for i in range(100):\n factoid = next(generator)\n assert factoid[\"@id\"] == \"Factoid %03d\" % (i + 1)\n assert \"Person\" in factoid[\"person\"][\"@id\"]\n assert \"Source\" in factoid[\"source\"][\"@id\"]\n assert \"statement\" in factoid\n assert factoid[\"statement\"][\"@id\"] == \"F%dS1\" % (i + 1)","def generate_run_id(self):\n r_id_len = 4\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\n while r_id in self.cache:\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\n return r_id","def test_get_sample_ids(self):\r\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\r\n parse_metadata_state_descriptions('Study:Twin')), [])\r\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\r\n parse_metadata_state_descriptions('Study:Dog')), ['a', 'b'])\r\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\r\n parse_metadata_state_descriptions('Study:*,!Dog')), ['c', 'd', 'e'])\r\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\r\n parse_metadata_state_descriptions('Study:*,!Dog;BodySite:Stool')), ['e'])\r\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\r\n parse_metadata_state_descriptions('BodySite:Stool')), ['a', 'b', 'e'])","def test_id(self):\n b1 = Base()\n self.assertEqual(b1.id, 1)\n b2 = Base()\n self.assertEqual(b2.id, 2)\n b3 = Base(98)\n self.assertEqual(b3.id, 98)\n b4 = Base(256)\n self.assertEqual(b4.id, 256)\n b5 = Base()\n self.assertEqual(b5.id, 3)\n b6 = Base(-98)\n self.assertEqual(b6.id, -98)\n b7 = Base(None)\n self.assertEqual(b7.id, 4)\n b8 = Base(4.4)\n self.assertEqual(b8.id, 4.4)","def test_get_sample_ids(self):\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\n parse_metadata_state_descriptions('Study:Twin')), [])\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\n parse_metadata_state_descriptions('Study:Dog')), ['a','b'])\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\n parse_metadata_state_descriptions('Study:*,!Dog')), ['c','d','e'])\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\n parse_metadata_state_descriptions('Study:*,!Dog;BodySite:Stool')), ['e'])\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\n parse_metadata_state_descriptions('BodySite:Stool')), ['a','b','e'])","def test_main(data, tmp_path):\n\n main(data, tmp_path)\n\n FILES = (\n \"gd32f888x(0-1)xx-pinctrl.h\",\n \"gd32f888x(2-3)xx-pinctrl.h\",\n \"gd32f888y(0-1)xx-pinctrl.h\",\n \"gd32f999x(0-1)xx-pinctrl.h\",\n \"gd32f999x(2-3)xx-pinctrl.h\",\n \"gd32f999y(0-1)xx-pinctrl.h\",\n )\n\n for file in FILES:\n ref_file = data / file\n gen_file = tmp_path / file\n\n assert gen_file.exists()\n\n with open(ref_file) as ref, open(gen_file) as gen:\n assert ref.read() == gen.read()","def get_ids(data, N_max):\n\n id_data = data[['molecule_name', 'id']].copy()\n\n # write molecules into one line\n id_data = id_data.groupby('molecule_name').apply(lambda x:\n x.values.reshape(-1))\n\n # pad with nans\n id_list = []\n for i in range(len(id_data)):\n n = N_max*2 - len(id_data[i])\n id_list.append(np.pad(id_data[i], (0, n), 'constant',\n constant_values=(0, np.nan)))\n\n # build np array and remove molecule names\n id_data = np.vstack(id_list)\n del id_list\n id_data = np.delete(id_data, [2*i for i in range(N_max)], 1)\n\n return id_data","def test1():\n for test in pkl.load(open(TEST_RESOURCES_DIR / \"regression_vault.pkl\", \"rb\"))[:5]:\n init_dict, rslt = test\n np.testing.assert_array_equal(run_regression_test(init_dict), rslt)","def data_gen(size, p):\n #print(np.random.get_state()[1][0])\n random_table = np.random.binomial(size = size, p = p, n = 1)\n test_array = np.zeros((size, 2), dtype = int)\n for i in range(size):\n test_array[i,0] = i\n test_array[i,1] = random_table[i]\n return test_array","def test_assign_resources_to_tmc_subarray_in_low():"],"string":"[\n \"def test_generate_spin_id_data_array6(self):\\n\\n # The data.\\n data = ['1', 'GLY', None, None]\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\\n\\n # Test the string.\\n self.assertEqual(id, ':1')\",\n \"def test_generate_spin_id_data_array1(self):\\n\\n # The data.\\n data = ['1', 'GLY']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\\n\\n # Test the string.\\n self.assertEqual(id, ':1')\",\n \"def test_generate_spin_id_data_array2(self):\\n\\n # The data.\\n data = ['1', 'GLY', '234', 'NH']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2, spin_num_col=3, spin_name_col=4)\\n\\n # Test the string.\\n self.assertEqual(id, ':1@234')\",\n \"def test_generate_spin_id_data_array4(self):\\n\\n # The data.\\n data = ['Ap4Aase', '1', 'GLY']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3)\\n\\n # Test the string.\\n self.assertEqual(id, '#Ap4Aase:1')\",\n \"def test_generate_spin_id_data_array3(self):\\n\\n # The data.\\n data = ['Ap4Aase', '234', 'NH']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=None, res_name_col=None, spin_num_col=2, spin_name_col=3)\\n\\n # Test the string.\\n self.assertEqual(id, '#Ap4Aase@234')\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def test_id_array(self):\\n arr = vtk.vtkIdTypeArray()\\n arr.SetNumberOfTuples(10)\\n for i in range(10):\\n arr.SetValue(i, i)\\n\\n np = array_handler.vtk2array(arr)\\n self.assertEqual(numpy.all(np == range(10)), True)\",\n \"def test_spin_loop(self):\\n\\n # Spin data.\\n select = [1, 0]\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, 'N5')\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 2)\",\n \"def test_random_id(self):\\r\\n ids = \\\\\\r\\n \\\"R27DLI_4812 R27DLI_600 R27DLI_727 U1PLI_403 U1PLI_8969\\\".split(\\r\\n )\\r\\n assert random_id(ids, {}) in ids\\r\\n # just test we got something from the list, don't add stochastic test\\r\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_create_template(self):\\n m_size = 10\\n data = ecn.IDData(m_size)\\n self.assertEqual(np.shape(data.ID_MATRIX), (m_size, m_size))\\n self.assertEqual(sum(sum(data.ID_MATRIX)), m_size)\\n self.assertTrue((sum(data.ID_MATRIX) == np.ones(m_size)).all())\\n print('Finished testing template\\\\n')\",\n \"def createArrayFunc(self):\\r\\n minVal = int(self.spinBoxMin_2.value())\\r\\n maxVal = int(self.spinBoxMax_2.value())\\r\\n arrayLength = int(self.spinBoxLength_2.value())\\r\\n different = maxVal - minVal\\r\\n if self.checkBoxNoRepeate_2.isChecked():\\r\\n if different > arrayLength:\\r\\n def unique_rand(initial, limit, total):\\r\\n data = []\\r\\n i = 0\\r\\n while i < total:\\r\\n number = numpy.random.randint(initial, limit)\\r\\n if number not in data:\\r\\n data.append(number)\\r\\n i += 1\\r\\n return data\\r\\n\\r\\n self.UnsortedArray_2 = unique_rand(minVal, maxVal, arrayLength)\\r\\n else:\\r\\n err = \\\"Array length must be greater than difference between limits\\\"\\r\\n self.labelUnsortedArray_2.setText(str(err))\\r\\n\\r\\n else:\\r\\n self.UnsortedArray_2 = numpy.random.randint(minVal, maxVal, arrayLength)\\r\\n self.labelUnsortedArray_2.setText(str(self.UnsortedArray_2))\\r\\n self.SortedArray_2 = Insertion.sorting(self.UnsortedArray_2)\\r\\n self.labelSortedArray_2.setText(str(self.SortedArray_2))\\r\\n binaryMax = int(self.spinBoxMax_2.value())\\r\\n binaryMin = int(self.spinBoxMin_2.value())\\r\\n self.spinBoxBinary.setMaximum(binaryMax)\\r\\n self.spinBoxBinary.setMinimum(binaryMin)\\r\\n self.spinBoxIthSmallest.setMaximum(arrayLength + 1)\",\n \"def test_scan_id_list(self):\\n scan = '15,17'\\n ref_idx = [0,3]\\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_spin_loop_no_selection(self):\\n\\n # Spin data.\\n select = [0, 1, 0, 0, 1, 1, 0, 1]\\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 8)\",\n \"def test_uuid():\\n for _ in range(1000):\\n uuid = uuid_generator()\\n assert len(uuid) == 36\\n assert uuid.count('-') == 4\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_arr2vtkIdList(self):\\n a = [1, 2, 3, 4, 5]\\n p = array_handler.array2vtkIdList(a)\\n for i, j in enumerate(a): \\n self.assertEqual(p.GetId(i), j)\\n p = vtk.vtkIdList()\\n ident = id(p)\\n p = array_handler.array2vtkIdList(numpy.array(a), p)\\n for i, j in enumerate(a): \\n self.assertEqual(p.GetId(i), j)\\n self.assertEqual(id(p), ident)\\n \\n self.assertRaises(AssertionError, array_handler.array2vtkIdList,\\n [[1,2,3]])\",\n \"def generate_T(number_obeservations):\\n T = np.random.randint(0, 2, (number_obeservations,1))\\n return T\",\n \"def test_random_integers(self):\\r\\n # Check over two calls to see if the random state is correctly updated.\\r\\n random = RandomStreams(utt.fetch_seed())\\r\\n fn = function([], random.random_integers((20, 20), -5, 5))\\r\\n fn_val0 = fn()\\r\\n fn_val1 = fn()\\r\\n\\r\\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\\r\\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\\r\\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\\r\\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\\r\\n\\r\\n assert numpy.all(fn_val0 == numpy_val0)\\r\\n assert numpy.all(fn_val1 == numpy_val1)\",\n \"def test_random_integers(self):\\r\\n # Check over two calls to see if the random state is correctly updated.\\r\\n m = Module()\\r\\n m.random = RandomStreams(utt.fetch_seed())\\r\\n m.fn = Method([], m.random.random_integers((20,20), -5, 5))\\r\\n\\r\\n made = m.make()\\r\\n made.random.initialize()\\r\\n fn_val0 = made.fn()\\r\\n fn_val1 = made.fn()\\r\\n\\r\\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\\r\\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\\r\\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\\r\\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\\r\\n\\r\\n assert numpy.all(fn_val0 == numpy_val0)\\r\\n assert numpy.all(fn_val1 == numpy_val1)\",\n \"def test_run_sim_1():\\n rnd = rand.Arrivals(36, 41)\\n sim.run_sim(3, 2, 5, 6, 22, rnd)\",\n \"def test_id_rot():\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_axis_angle(pr.a_id))\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_quaternion(pr.q_id))\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_xyz(pr.e_xyz_id))\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_zyx(pr.e_zyx_id))\",\n \"def test_run_sim():\\n rnd = rand.Arrivals(31, 40)\\n sim.run_sim(2, 1, 3, 4, 24, rnd)\",\n \"def test_scan_id_range(self):\\n scan = '16~17'\\n ref_idx = [1,2,3]\\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_generate(self):\\n cant_interations = int(random()*100)\\n for i in range(cant_interations):\\n number = self.sudoku.generate() # Generate number\\n self.assertGreaterEqual(number, 0) # number >= 0\\n self.assertLessEqual(number, 8) # number <= 8\",\n \"def test_spin_type(get_pdos_generator_inputs):\\n with pytest.raises(NotImplementedError):\\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=spin_type)\\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=SpinType.COLLINEAR)\\n for namespace in [builder.scf, builder.nscf]:\\n parameters = namespace['pw']['parameters'].get_dict()\\n assert parameters['SYSTEM']['nspin'] == 2\\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}\",\n \"def test_generateuuids(self):\\n ret1 = {\\\"message\\\": \\\"No Random.org api key or api version found.\\\", \\\"res\\\": False}\\n self.assertDictEqual(random_org.generateUUIDs(), ret1)\\n\\n ret2 = {\\\"message\\\": \\\"Required argument, number is missing.\\\", \\\"res\\\": False}\\n self.assertDictEqual(\\n random_org.generateUUIDs(api_key=\\\"peW\\\", api_version=\\\"1\\\"), ret2\\n )\\n\\n ret3 = {\\\"message\\\": \\\"Number of UUIDs must be between 1 and 1000\\\", \\\"res\\\": False}\\n self.assertDictEqual(\\n random_org.generateUUIDs(api_key=\\\"peW\\\", api_version=\\\"1\\\", number=\\\"5\\\"), ret3\\n )\\n\\n ret3 = {\\\"message\\\": \\\"Parameter 'apiKey' is malformed\\\", \\\"res\\\": False}\\n self.assertDictEqual(\\n random_org.generateUUIDs(api_key=\\\"peW\\\", api_version=\\\"1\\\", number=5), ret3\\n )\",\n \"def test_pol_id_list(self):\\n pol = '0,1'\\n ref_idx = []\\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def generate_new_ids(ids: np.array, n_required: int) -> np.array:\\n\\n current_max_id = ids.max()\\n new_ids = np.arange(n_required) + current_max_id + 1\\n\\n return new_ids\",\n \"def _get_rand_array(self):\\n pass\",\n \"def _apply_array_spin123(self,\\n h1e: 'Nparray',\\n h2e: 'Nparray',\\n h3e: 'Nparray',\\n dvec: Optional[Tuple['Nparray', 'Nparray']] = None,\\n evec: Optional[Tuple['Nparray', 'Nparray', 'Nparray', 'Nparray']] \\\\\\n = None) -> 'Nparray':\\n norb = self.norb()\\n assert h3e.shape == (norb * 2,) * 6\\n assert not (dvec is None) ^ (evec is None)\\n\\n from1234 = (dvec is not None) and (evec is not None)\\n\\n nh1e = numpy.copy(h1e)\\n nh2e = numpy.copy(h2e)\\n\\n for i in range(norb * 2):\\n for j in range(norb * 2):\\n for k in range(norb * 2):\\n nh2e[j, k, :, :] += (-h3e[k, j, i, i, :, :] -\\n h3e[j, i, k, i, :, :] -\\n h3e[j, k, i, :, i, :])\\n\\n nh1e[:, :] += h3e[:, i, j, i, j, :]\\n\\n out = self._apply_array_spin12_halffilling(nh1e, nh2e)\\n\\n n = norb # This is just shorter\\n if not from1234:\\n symfac = 2.0\\n axes = ((1, 3), (0, 1))\\n (odveca, odvecb) = self.calculate_dvec_spin()\\n dveca = numpy.zeros_like(odveca)\\n dvecb = numpy.zeros_like(odvecb)\\n\\n for i in range(norb):\\n for j in range(norb):\\n evecaa, _ = self._calculate_dvec_spin_with_coeff(\\n odveca[i, j, :, :])\\n evecab, evecbb = self._calculate_dvec_spin_with_coeff(\\n odvecb[i, j, :, :])\\n\\n dveca += numpy.tensordot(h3e[:n, :n, i, :n, :n, j],\\n evecaa,\\n axes=axes)\\n dveca += numpy.tensordot(h3e[:n, :n, n + i, :n, :n, n + j],\\n evecab,\\n axes=axes) * symfac\\n dveca += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\\n evecbb,\\n axes=axes)\\n\\n dvecb += numpy.tensordot(h3e[n:, :n, i, n:, :n, j],\\n evecaa,\\n axes=axes)\\n dvecb += numpy.tensordot(h3e[n:, :n, n + i, n:, :n, n + j],\\n evecab,\\n axes=axes) * symfac\\n dvecb += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\\n evecbb,\\n axes=axes)\\n else:\\n symfac = 1.0\\n axes = ((1, 4, 2, 5), (0, 1, 2, 3)) # type: ignore\\n dveca, dvecb = dvec # type: ignore\\n evecaa, evecab, evecba, evecbb = evec # type: ignore\\n\\n dveca = numpy.tensordot(h3e[:n, :n, :n, :n, :n, :n],\\n evecaa, axes=axes) \\\\\\n + numpy.tensordot(h3e[:n, :n, n:, :n, :n, n:],\\n evecab, axes=axes) * symfac \\\\\\n + numpy.tensordot(h3e[:n, n:, n:, :n, n:, n:],\\n evecbb, axes=axes) + \\\\\\n + numpy.tensordot(h3e[:n, n:, :n, :n, n:, :n],\\n evecba, axes=axes)\\n\\n dvecb = numpy.tensordot(h3e[n:, :n, :n, n:, :n, :n],\\n evecaa, axes=axes) \\\\\\n + numpy.tensordot(h3e[n:, :n, n:, n:, :n, n:],\\n evecab, axes=axes) * symfac \\\\\\n + numpy.tensordot(h3e[n:, n:, n:, n:, n:, n:],\\n evecbb, axes=axes) + \\\\\\n + numpy.tensordot(h3e[n:, n:, :n, n:, n:, :n],\\n evecba, axes=axes)\\n\\n out -= self._calculate_coeff_spin_with_dvec((dveca, dvecb))\\n return out\",\n \"def test_split_id_otp(self):\\n public_id, otp, = pyhsm.yubikey.split_id_otp(\\\"ft\\\" * 16)\\n self.assertEqual(public_id, '')\\n self.assertEqual(otp, \\\"ft\\\" * 16)\\n\\n public_id, otp, = pyhsm.yubikey.split_id_otp(\\\"cc\\\" + \\\"ft\\\" * 16)\\n self.assertEqual(public_id, 'cc')\\n self.assertEqual(otp, \\\"ft\\\" * 16)\",\n \"def gen_data(min_coord, max_coord, size):\\r\\n data = np.random.randint(min_coord, max_coord, size)\\r\\n return data\",\n \"def test_SampleIds(self):\\r\\n exp = [\\\"PC.354\\\", \\\"PC.355\\\", \\\"PC.356\\\", \\\"PC.481\\\", \\\"PC.593\\\", \\\"PC.607\\\",\\r\\n \\\"PC.634\\\", \\\"PC.635\\\", \\\"PC.636\\\"]\\r\\n obs = self.overview_map.SampleIds\\r\\n self.assertEqual(obs, exp)\\r\\n\\r\\n obs = self.no_metadata.SampleIds\\r\\n self.assertEqual(obs, exp)\\r\\n\\r\\n obs = self.empty_map.SampleIds\\r\\n self.assertEqual(obs, [])\",\n \"def genNumID(size):\\n\\tid = \\\"\\\"\\n\\tfor i in range(size):\\n\\t\\tid = id + selectRandomFromList(numTokens)\\n\\treturn id\",\n \"def test_spin_loop_wildcard(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N*'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_SampleIds(self):\\n exp = [\\\"PC.354\\\", \\\"PC.355\\\", \\\"PC.356\\\", \\\"PC.481\\\", \\\"PC.593\\\", \\\"PC.607\\\",\\n \\\"PC.634\\\", \\\"PC.635\\\", \\\"PC.636\\\"]\\n obs = self.overview_map.SampleIds\\n self.assertEqual(obs, exp)\\n\\n obs = self.no_metadata.SampleIds\\n self.assertEqual(obs, exp)\\n\\n obs = self.empty_map.SampleIds\\n self.assertEqual(obs, [])\",\n \"def test_weyl_specialize_id(self):\\n a, b, c = 0.0, 0.0, 0.0\\n for da, db, dc in DELTAS:\\n for k1l, k1r, k2l, k2r in K1K2SB:\\n k1 = np.kron(k1l.data, k1r.data)\\n k2 = np.kron(k2l.data, k2r.data)\\n self.check_two_qubit_weyl_specialization(\\n k1 @ Ud(a + da, b + db, c + dc) @ k2,\\n 0.999,\\n TwoQubitWeylIdEquiv,\\n {\\\"rz\\\": 4, \\\"ry\\\": 2},\\n )\",\n \"def generate_raiz():\\n\\treturn os.urandom(12)\",\n \"def myID() -> np.int:\\r\\n return 304976335\",\n \"def myID() -> np.int:\\r\\n return 304976335\",\n \"def generate_synth_data(n):\",\n \"def test_spin_loop_multiatom(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_get_ids(civic, main_data, updated_data):\\n assert len(civic._get_ids(main_data['assertions'])) == 0\\n assert len(civic._get_ids(main_data['variants'])) == 1\\n assert len(civic._get_ids(main_data['genes'])) == 2\\n assert len(civic._get_ids(main_data['evidence'])) == 1\\n\\n assert len(civic._get_ids(updated_data['assertions'])) == 1\\n assert len(civic._get_ids(updated_data['variants'])) == 1\\n assert len(civic._get_ids(updated_data['genes'])) == 1\\n assert len(civic._get_ids(updated_data['evidence'])) == 1\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_returned_num_in_random_nums(self):\\n self._setup_random_gen([1.], [42])\\n self.assertEqual(self._random_gen.next_num(), 42)\",\n \"def test_kf_id():\\n\\n for _ in range(1000):\\n prefix = ''.join(random.sample(string.ascii_uppercase, 2))\\n kf_id = kf_id_generator(prefix)()\\n assert kf_id[:2] == prefix\\n assert len(kf_id) == 11\\n assert kf_id[2] == '_'\\n\\n assert 'I' not in kf_id[2:]\\n assert 'L' not in kf_id[2:]\\n assert 'O' not in kf_id[2:]\\n assert 'U' not in kf_id[2:]\\n\\n assert re.search(r'^'+prefix+r'_[A-HJ-KM-NP-TV-Z0-9]{8}', kf_id)\",\n \"def test_spin_type(fixture_code, generate_structure):\\n code = fixture_code('quantumespresso.pw')\\n structure = generate_structure()\\n\\n with pytest.raises(NotImplementedError):\\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\\n PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=spin_type)\\n\\n builder = PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=SpinType.COLLINEAR)\\n\\n for namespace in [builder.relax['base'], builder.scf, builder.bands]:\\n parameters = namespace['pw']['parameters'].get_dict()\\n assert parameters['SYSTEM']['nspin'] == 2\\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}\",\n \"def test_brains_id_get(self):\\n pass\",\n \"def test_if_array_is_good(self):\\n testing_param = random.randint(1, 100)\\n self.assertEqual(self.exercice.main(testing_param),\\n list(range(2, testing_param+1, 2)))\",\n \"def test_get_tid():\\n tids = []\\n def _foo():\\n mytid = yield GetTid()\\n tids.append(mytid)\\n for i in range(5):\\n yield i\\n\\n scheduler = Scheduler()\\n scheduler.new(_foo())\\n scheduler.new(_foo())\\n scheduler.mainloop()\\n\\n # can we do better than hard code?\\n assert tids == [4, 5]\",\n \"def test_scan_id_exprlist(self):\\n scan = '15,>16'\\n ref_idx = [0,3]\\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_start_ids_10(self):\\n\\n\\t\\texpected_num_layers = 11\\n\\t\\texpected_ids = np.arange(10,21)\\n\\t\\t# test describe\\n\\t\\tdetails = self.watcher.describe(start_ids=10)\\n\\t\\tprint(\\\"start id = 10\\\", details)\\n\\t\\tactual_ids = details.layer_id.to_numpy().tolist()\\n\\t\\tself.assertTrue(np.array_equal(actual_ids, expected_ids))\\n\\t\\tself.assertEqual(len(expected_ids), expected_num_layers)\\n\\t\\t\\t\\t\\n\\t\\treturn\",\n \"def random_lottery():\\n\\treturn 0\",\n \"def test_sampleId_pairs(self):\\r\\n # expected values\\r\\n dose_vps = \\\\\\r\\n [('1xDose', '2xDose'), ('1xDose', 'Control'),\\r\\n ('2xDose', 'Control')]\\r\\n ttd_vps = \\\\\\r\\n [('31', '21'), ('31', '55'), ('31', '67'), ('21', '55'),\\r\\n ('21', '67'), ('55', '67')]\\r\\n dose_sids = \\\\\\r\\n [(['Sam1', 'Sam2', 'Sam6'], ['Sam3', 'Sam4']),\\r\\n (['Sam1', 'Sam2', 'Sam6'], ['Sam5']),\\r\\n (['Sam3', 'Sam4'], ['Sam5'])]\\r\\n ttd_sids = \\\\\\r\\n [(['Sam1'], ['Sam3']),\\r\\n (['Sam1'], ['Sam4', 'Sam6']),\\r\\n (['Sam1'], ['Sam2', 'Sam5']),\\r\\n (['Sam3'], ['Sam4', 'Sam6']),\\r\\n (['Sam3'], ['Sam2', 'Sam5']),\\r\\n (['Sam4', 'Sam6'], ['Sam2', 'Sam5'])]\\r\\n\\r\\n # observed values\\r\\n obs_dose_sids, obs_dose_vps = sampleId_pairs(self.mapping_data,\\r\\n self.rarefaction_data, 'Dose')\\r\\n obs_ttd_sids, obs_ttd_vps = sampleId_pairs(self.mapping_data,\\r\\n self.rarefaction_data, 'TTD')\\r\\n\\r\\n # sort -- order is unimportant and depends on way presented in mf\\r\\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\\r\\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())\\r\\n self.assertEqual(ttd_vps.sort(), obs_ttd_vps.sort())\\r\\n self.assertEqual(ttd_sids.sort(), obs_ttd_sids.sort())\\r\\n\\r\\n # check errors when no samples had this category\\r\\n self.assertRaises(ValueError, sampleId_pairs, self.mapping_data,\\r\\n self.rarefaction_data, 'DNE')\\r\\n\\r\\n # check no error if map file has more sampleids than rarefaction data\\r\\n superset_mf = \\\\\\r\\n ['#SampleID\\\\tDose\\\\tLinkerPrimerSequence\\\\tWeight\\\\tTTD\\\\tDescription',\\r\\n '#Comment Line',\\r\\n 'Sam1\\\\t1xDose\\\\tATCG\\\\tHigh\\\\t31\\\\ts1_desc',\\r\\n 'Sam2\\\\t1xDose\\\\tACCG\\\\tLow\\\\t67\\\\ts2_desc',\\r\\n 'Sam3\\\\t2xDose\\\\tACGT\\\\tMed\\\\t21\\\\ts3_desc',\\r\\n 'Sam4\\\\t2xDose\\\\tAACG\\\\tLow\\\\t55\\\\ts4_desc',\\r\\n 'Sam5\\\\tControl\\\\tCGTC\\\\tLow\\\\t67\\\\ts5_desc',\\r\\n 'Sam6\\\\t1xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts6_desc',\\r\\n 'Sam7\\\\t4xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts7_desc',\\r\\n 'Sam8\\\\t3xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts8_desc',\\r\\n 'Sam9\\\\t1xDose\\\\tACCT\\\\tLow\\\\t55\\\\ts9_desc']\\r\\n # (mf, comments)\\r\\n superset_mf = parse_mapping_file_to_dict(superset_mf)[0]\\r\\n obs_dose_sids, obs_dose_vps = sampleId_pairs(superset_mf,\\r\\n self.rarefaction_data, 'Dose')\\r\\n\\r\\n self.assertEqual(dose_vps.sort(), obs_dose_vps.sort())\\r\\n self.assertEqual(dose_sids.sort(), obs_dose_sids.sort())\",\n \"def test_pol_id_range(self):\\n pol = '0~1'\\n ref_idx = []\\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_test_ids_request(get_interface_params):\\n from sail_on_client.protocol.localinterface import LocalInterface\\n\\n config_directory, config_name = get_interface_params\\n data_dir = f\\\"{os.path.dirname(__file__)}/data\\\"\\n local_interface = LocalInterface(config_name, config_directory)\\n\\n assumptions_path = os.path.join(os.path.dirname(__file__), \\\"assumptions.json\\\")\\n filename = local_interface.test_ids_request(\\n \\\"OND\\\", \\\"image_classification\\\", \\\"5678\\\", assumptions_path\\n )\\n expected = os.path.join(data_dir, \\\"OND\\\", \\\"image_classification\\\", \\\"test_ids.csv\\\")\\n assert os.stat(expected).st_size > 5\\n assert expected == filename\",\n \"def test_create_tornado_id(self):\\n\\n this_id_string = tornado_io.create_tornado_id(\\n start_time_unix_sec=TORNADO_START_TIME_UNIX_SEC,\\n start_latitude_deg=TORNADO_START_LATITUDE_DEG,\\n start_longitude_deg=TORNADO_START_LONGITUDE_DEG)\\n\\n self.assertTrue(this_id_string == TORNADO_ID_STRING)\",\n \"def generate_mixture_indicator(number_obeservations):\\n mixture_indicator = np.random.randint(0, 2, (number_obeservations,1))\\n return mixture_indicator\",\n \"def _spin_sequence(self):\\n self.return_position = self.motor.position\\n \\n for spin_num in range(self.num_spins):\\n self.taxi()\\n\\n det_pre_acquire(self.detector)\\n self.fly()\\n det_post_acquire(self.detector)\\n\\n while self.detector.hdf1.write_file.value:\\n time.sleep(0.01) # wait for file to be written\\n\\n event = OrderedDict()\\n event[\\\"time\\\"] = time.time()\\n event[\\\"seq_num\\\"] = spin_num + 1\\n event[\\\"data\\\"] = {}\\n event[\\\"timestamps\\\"] = {}\\n for d_item in (self.detector.hdf1.full_file_name,):\\n d = d_item.read()\\n for k, v in d.items():\\n event['data'][k] = v['value']\\n event['timestamps'][k] = v['timestamp']\\n\\n self._data.append(event)\\n\\n self.set(\\\"Return\\\")\\n self._completion_status._finished(success=True)\",\n \"def _generate_id() -> str:\\n return \\\"\\\".join(sample(\\\"abcdefghjkmopqrstuvqxyz\\\", 16))\",\n \"def test_ids(self):\\n # AdapterID inherited from IOAdapter\\n self.assertEqual('553713696', self.sriovs[0].id)\\n self.assertEqual(1, self.sriovs[0].sriov_adap_id)\\n\\n self.assertEqual('553713680', self.sriovs[2].id)\\n self.assertIsNone(self.sriovs[2].sriov_adap_id)\",\n \"def test_residue_loop(self):\\n\\n # Loop over the residues.\\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\\n # Test the selection.\\n self.assertEqual(res.num, 2)\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)\",\n \"def get_refresh_ids(self):\\n ids = []\\n for bucket in self.router.lonely_buckets():\\n rid = random.randint(*bucket.range).to_bytes(20, byteorder='big')\\n ids.append(rid)\\n return ids\",\n \"def test_rand_func2(self):\\n for i in range(0, 100000):\\n num = random.randint(0, 32535143990)\\n func2_comp(num)\",\n \"def test_arbitrary_rotation(self):\\n \\n # This test is run a bunch of times on various intervals, ranging from 50% to 1/6\\n\\t\\t# (16.667%).\\n for i in range(2, 7):\\n \\n interval = 1 / i # The amount to increase each qubit's probability by, relative to the previous qubit\\n step_string = \\\"{:.4f}\\\".format(100 / i) # The decimal representation of the interval, as a percent\\n target_probabilities = [0] * (i + 1) # This will store the desired probabilities of each qubit\\n for j in range(0, i + 1):\\n target_probability = j * interval\\n target_probabilities[j] = target_probability\\n\\n # Run the test\\n self.run_test(self.arbitrary_rotation_function, f\\\"Rotation with steps of 1/{i} ({step_string}%)\\\", 2000, target_probabilities, 0.05)\",\n \"def generaterandomindices(dataSize, percentTest):\\n\\n TrainIndices = np.array([])\\n while TrainIndices.__len__() < int(percentTest * dataSize):\\n # Randomly select an index value and store it. If it has already been chosen, pick again.\\n index = int(random.random() * dataSize)\\n if not TrainIndices.__contains__(index):\\n TrainIndices = np.append(TrainIndices, [index])\\n\\n # For aesthetic purposes:\\n TrainIndices = np.sort(TrainIndices)\\n\\n return TrainIndices\",\n \"def get_test_split(self, fraction=0.1):\\n rng = np.random.default_rng(42)\\n test_size = int(round(len(self.all_asset_ids) * fraction))\\n test_ids = rng.choice(self.all_asset_ids, size=test_size, replace=False)\\n train_ids = [i for i in self.all_asset_ids if i not in test_ids]\\n return train_ids, test_ids\",\n \"def test_random_generator(self):\\n gen = random_data()\\n data = [next(gen) for _ in range(100)]\\n self.assertEqual(len(data), 100)\",\n \"def gen_all_arms_ids(\\n self,\\n ) -> None:\\n num_all_arms = (\\n self.num_unique_batches * self.batch_size * self.num_arms_per_episode\\n )\\n all_arms_ids = torch.randperm(num_all_arms)\\n self.all_unique_arm_ids = all_arms_ids.reshape(\\n [self.num_unique_batches, self.batch_size, self.num_arms_per_episode]\\n )\\n assert self.all_unique_arm_ids.ndim == 3\\n return\",\n \"def generate_license_plate(self, num):\\n license_plate = []\\n for _ in range(num):\\n license_plate.append(self.fake.license_plate())\\n return license_plate\",\n \"def test_field_id_list(self):\\n field = '5,8'\\n ref_idx = [0,3]\\n self.res=self.run_task(infile=self.rawfile,field=field,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_get_sample_ids(self):\\n obs = self.tester._get_sample_ids(self.conn_handler)\\n self.assertEqual(obs, self.exp_sample_ids)\",\n \"def test_get_sample_ids(self):\\n obs = self.tester._get_sample_ids(self.conn_handler)\\n self.assertEqual(obs, self.exp_sample_ids)\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_15(self):\\n\\t self.assertTrue(prime_generator(15), [2, 3, 5, 7, 11, 13])\",\n \"def create_code():\\n\\n code = [0, 0, 0, 0]\\n\\n for i in range(4):\\n value = random.randint(1, 8) # 8 possible digits\\n while value in code:\\n value = random.randint(1, 8) # 8 possible digits\\n code[i] = value\\n \\n #print(code)\\n return code\",\n \"def test_generate_mine_sequence(self):\\n mine_list = utils.generate_mine_sequence(1)\\n self.assertEqual(len(mine_list), utils.MINE_COUNT)\",\n \"def generate_fake_data(t0, num_array, period=5820, data_range=[0.0, 24.0],\\n cyclic=True):\\n\\n if cyclic:\\n uts_root = np.mod(t0, period)\\n data = (np.mod(uts_root + num_array, period)\\n * (np.diff(data_range)[0] / np.float64(period))) + data_range[0]\\n else:\\n data = ((t0 + num_array) / period).astype(int)\\n\\n return data\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def spinWheel():\\n\\tt = random.randrange(8)\\n\\tif t == 7:\\n\\t\\treturn \\\"00\\\"\\n\\treturn str(t)\",\n \"def NSK129_user_ids():\\n return [\\n707057500045751944,\\n707057500045752170,\\n707057500045752255,\\n707057500045752231,\\n707057500045752217,\\n707057500045752194,\\n707057500045752156,\\n707057500045752132,\\n707057500045752118,\\n707057500045752088,\\n707057500045752064,\\n707057500045752057,\\n707057500045752033,\\n707057500045752002,\\n707057500045751982,\\n707057500045751975,\\n707057500045751937,\\n707057500045751913,\\n707057500045745844,\\n707057500045745851,\\n707057500045745929,\\n707057500045745936,\\n707057500045746001,\\n707057500045746018,\\n707057500045745868,\\n707057500045745875,\\n707057500045745943,\\n707057500045745950,\\n707057500045746025,\\n707057500045746032,\\n707057500045745882,\\n707057500045745837,\\n707057500045745899,\\n707057500045745974,\\n707057500045746049,\\n707057500045746056,\\n707057500045745905,\\n707057500045745981,\\n707057500045745998,\\n707057500045746063,\\n707057500045746070,\\n707057500045745912,\\n707057500045745639,\\n707057500045745707,\\n707057500045745714,\\n707057500045745783,\\n707057500045745790,\\n707057500045745646,\\n707057500045745653,\\n707057500045745738,\\n707057500045745806,\\n707057500045745615,\\n707057500045745776,\\n707057500045745622,\\n707057500045745578,\\n707057500045745585,\\n707057500045745592,\\n707057500045745813,\\n707057500045745660,\\n707057500045745684,\\n707057500045745721,\\n707057500045745769,\\n707057500045745677,\\n707057500045745745,\\n707057500045745752,\\n707057500045745608,\\n707057500045750442,\\n707057500045752613,\\n707057500045752606,\\n707057500045752163,\\n707057500045752200,\\n707057500045752224,\\n707057500045752149,\\n707057500045752187,\\n707057500045752293,\\n707057500045752286,\\n707057500045752071,\\n707057500045752040,\\n707057500045752095,\\n707057500045752125,\\n707057500045752101,\\n707057500045752026,\\n707057500045752279,\\n707057500045752262,\\n707057500045751814,\\n707057500045751807,\\n707057500045751890,\\n707057500045751883,\\n707057500045751876,\\n707057500045751869,\\n707057500045751821,\\n707057500045751838,\\n707057500045751845,\\n707057500045751852,\\n707057500045751999,\\n707057500045751951,\\n707057500045752019,\\n707057500045751920,\\n707057500045751968,\\n707057500045751906,\\n707057500045745691,\\n707057500045745967]\",\n \"def iv_gen():\\r\\n rndiv = os.urandom(16)\\r\\n return rndiv\",\n \"def test_resisc45():\\n if not os.path.isdir(os.path.join(DATASET_DIR, \\\"resisc45_split\\\", \\\"3.0.0\\\")):\\n pytest.skip(\\\"resisc45_split dataset not locally available.\\\")\\n\\n for split, size in [(\\\"train\\\", 22500), (\\\"validation\\\", 4500), (\\\"test\\\", 4500)]:\\n batch_size = 16\\n epochs = 1\\n dataset = datasets.resisc45(\\n split=split, epochs=epochs, batch_size=batch_size, dataset_dir=DATASET_DIR,\\n )\\n assert dataset.size == size\\n assert dataset.batch_size == batch_size\\n assert dataset.batches_per_epoch == (\\n size // batch_size + bool(size % batch_size)\\n )\\n\\n x, y = dataset.get_batch()\\n assert x.shape == (batch_size, 256, 256, 3)\\n assert y.shape == (batch_size,)\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def data(i):\\n m = i*100\\n return [random.randint(0, m) for j in range(i)]\",\n \"def test_id_get(mocker):\\n mocker.patch('serial.Serial.open')\\n mocker.patch('serial.Serial.flushInput')\\n css = mocker.patch('pysds011.driver.SDS011.cmd_set_sleep')\\n css.return_value = True\\n cfv = mocker.patch('pysds011.driver.SDS011.cmd_firmware_ver')\\n cfv.return_value = {'id': b'\\\\x12\\\\x34', 'paperino': 'maciomicio'}\\n runner = CliRunner()\\n result = runner.invoke(main, ['id'])\\n\\n calls = [call(0, id=b'\\\\xff\\\\xff'), call(1, id=b'\\\\xff\\\\xff')]\\n css.assert_has_calls(calls, any_order=False)\\n\\n assert '12' in result.output and '34' in result.output\\n assert result.exit_code == 0\",\n \"def test_generate_factoid():\\n generator = mockdata.generate_factoid()\\n for i in range(100):\\n factoid = next(generator)\\n assert factoid[\\\"@id\\\"] == \\\"Factoid %03d\\\" % (i + 1)\\n assert \\\"Person\\\" in factoid[\\\"person\\\"][\\\"@id\\\"]\\n assert \\\"Source\\\" in factoid[\\\"source\\\"][\\\"@id\\\"]\\n assert \\\"statement\\\" in factoid\\n assert factoid[\\\"statement\\\"][\\\"@id\\\"] == \\\"F%dS1\\\" % (i + 1)\",\n \"def generate_run_id(self):\\n r_id_len = 4\\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\\n while r_id in self.cache:\\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\\n return r_id\",\n \"def test_get_sample_ids(self):\\r\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\r\\n parse_metadata_state_descriptions('Study:Twin')), [])\\r\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\r\\n parse_metadata_state_descriptions('Study:Dog')), ['a', 'b'])\\r\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\r\\n parse_metadata_state_descriptions('Study:*,!Dog')), ['c', 'd', 'e'])\\r\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\r\\n parse_metadata_state_descriptions('Study:*,!Dog;BodySite:Stool')), ['e'])\\r\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\r\\n parse_metadata_state_descriptions('BodySite:Stool')), ['a', 'b', 'e'])\",\n \"def test_id(self):\\n b1 = Base()\\n self.assertEqual(b1.id, 1)\\n b2 = Base()\\n self.assertEqual(b2.id, 2)\\n b3 = Base(98)\\n self.assertEqual(b3.id, 98)\\n b4 = Base(256)\\n self.assertEqual(b4.id, 256)\\n b5 = Base()\\n self.assertEqual(b5.id, 3)\\n b6 = Base(-98)\\n self.assertEqual(b6.id, -98)\\n b7 = Base(None)\\n self.assertEqual(b7.id, 4)\\n b8 = Base(4.4)\\n self.assertEqual(b8.id, 4.4)\",\n \"def test_get_sample_ids(self):\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\\\\n parse_metadata_state_descriptions('Study:Twin')), [])\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\\\\n parse_metadata_state_descriptions('Study:Dog')), ['a','b'])\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\\\\n parse_metadata_state_descriptions('Study:*,!Dog')), ['c','d','e'])\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\\\\n parse_metadata_state_descriptions('Study:*,!Dog;BodySite:Stool')), ['e'])\\n self.assertEqual(get_sample_ids(self.map_data, self.map_headers,\\\\\\n parse_metadata_state_descriptions('BodySite:Stool')), ['a','b','e'])\",\n \"def test_main(data, tmp_path):\\n\\n main(data, tmp_path)\\n\\n FILES = (\\n \\\"gd32f888x(0-1)xx-pinctrl.h\\\",\\n \\\"gd32f888x(2-3)xx-pinctrl.h\\\",\\n \\\"gd32f888y(0-1)xx-pinctrl.h\\\",\\n \\\"gd32f999x(0-1)xx-pinctrl.h\\\",\\n \\\"gd32f999x(2-3)xx-pinctrl.h\\\",\\n \\\"gd32f999y(0-1)xx-pinctrl.h\\\",\\n )\\n\\n for file in FILES:\\n ref_file = data / file\\n gen_file = tmp_path / file\\n\\n assert gen_file.exists()\\n\\n with open(ref_file) as ref, open(gen_file) as gen:\\n assert ref.read() == gen.read()\",\n \"def get_ids(data, N_max):\\n\\n id_data = data[['molecule_name', 'id']].copy()\\n\\n # write molecules into one line\\n id_data = id_data.groupby('molecule_name').apply(lambda x:\\n x.values.reshape(-1))\\n\\n # pad with nans\\n id_list = []\\n for i in range(len(id_data)):\\n n = N_max*2 - len(id_data[i])\\n id_list.append(np.pad(id_data[i], (0, n), 'constant',\\n constant_values=(0, np.nan)))\\n\\n # build np array and remove molecule names\\n id_data = np.vstack(id_list)\\n del id_list\\n id_data = np.delete(id_data, [2*i for i in range(N_max)], 1)\\n\\n return id_data\",\n \"def test1():\\n for test in pkl.load(open(TEST_RESOURCES_DIR / \\\"regression_vault.pkl\\\", \\\"rb\\\"))[:5]:\\n init_dict, rslt = test\\n np.testing.assert_array_equal(run_regression_test(init_dict), rslt)\",\n \"def data_gen(size, p):\\n #print(np.random.get_state()[1][0])\\n random_table = np.random.binomial(size = size, p = p, n = 1)\\n test_array = np.zeros((size, 2), dtype = int)\\n for i in range(size):\\n test_array[i,0] = i\\n test_array[i,1] = random_table[i]\\n return test_array\",\n \"def test_assign_resources_to_tmc_subarray_in_low():\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.815962","0.80106467","0.781097","0.7796662","0.77246344","0.6556488","0.5972483","0.596083","0.5889257","0.58199716","0.58112353","0.5503903","0.5457309","0.54131293","0.5382142","0.53779155","0.53478414","0.5337792","0.5311869","0.53046256","0.5285401","0.52599484","0.52502036","0.5233625","0.52207005","0.52123296","0.52112746","0.5202007","0.51958144","0.5193191","0.5180278","0.5178195","0.5175502","0.51631004","0.51556665","0.5151206","0.5131397","0.51259255","0.51256835","0.5117571","0.51022136","0.50823075","0.50714695","0.50714695","0.5068802","0.5063967","0.50500447","0.5042853","0.503737","0.50345826","0.5034424","0.5033376","0.502541","0.5018513","0.50119483","0.5011213","0.5005459","0.50026786","0.49857843","0.49825937","0.49825266","0.49798742","0.49745557","0.49738216","0.4966475","0.4958198","0.49576238","0.49474046","0.4946705","0.4940623","0.4937741","0.4936203","0.4931893","0.49301362","0.49265128","0.4926337","0.4926337","0.49260318","0.492274","0.49193355","0.49142656","0.4908842","0.49062678","0.49038064","0.49032825","0.48955756","0.489028","0.48800418","0.48793417","0.48768046","0.48763105","0.48740423","0.48694378","0.4868947","0.48684672","0.48673344","0.4863496","0.48625824","0.48563123","0.48525748"],"string":"[\n \"0.815962\",\n \"0.80106467\",\n \"0.781097\",\n \"0.7796662\",\n \"0.77246344\",\n \"0.6556488\",\n \"0.5972483\",\n \"0.596083\",\n \"0.5889257\",\n \"0.58199716\",\n \"0.58112353\",\n \"0.5503903\",\n \"0.5457309\",\n \"0.54131293\",\n \"0.5382142\",\n \"0.53779155\",\n \"0.53478414\",\n \"0.5337792\",\n \"0.5311869\",\n \"0.53046256\",\n \"0.5285401\",\n \"0.52599484\",\n \"0.52502036\",\n \"0.5233625\",\n \"0.52207005\",\n \"0.52123296\",\n \"0.52112746\",\n \"0.5202007\",\n \"0.51958144\",\n \"0.5193191\",\n \"0.5180278\",\n \"0.5178195\",\n \"0.5175502\",\n \"0.51631004\",\n \"0.51556665\",\n \"0.5151206\",\n \"0.5131397\",\n \"0.51259255\",\n \"0.51256835\",\n \"0.5117571\",\n \"0.51022136\",\n \"0.50823075\",\n \"0.50714695\",\n \"0.50714695\",\n \"0.5068802\",\n \"0.5063967\",\n \"0.50500447\",\n \"0.5042853\",\n \"0.503737\",\n \"0.50345826\",\n \"0.5034424\",\n \"0.5033376\",\n \"0.502541\",\n \"0.5018513\",\n \"0.50119483\",\n \"0.5011213\",\n \"0.5005459\",\n \"0.50026786\",\n \"0.49857843\",\n \"0.49825937\",\n \"0.49825266\",\n \"0.49798742\",\n \"0.49745557\",\n \"0.49738216\",\n \"0.4966475\",\n \"0.4958198\",\n \"0.49576238\",\n \"0.49474046\",\n \"0.4946705\",\n \"0.4940623\",\n \"0.4937741\",\n \"0.4936203\",\n \"0.4931893\",\n \"0.49301362\",\n \"0.49265128\",\n \"0.4926337\",\n \"0.4926337\",\n \"0.49260318\",\n \"0.492274\",\n \"0.49193355\",\n \"0.49142656\",\n \"0.4908842\",\n \"0.49062678\",\n \"0.49038064\",\n \"0.49032825\",\n \"0.48955756\",\n \"0.489028\",\n \"0.48800418\",\n \"0.48793417\",\n \"0.48768046\",\n \"0.48763105\",\n \"0.48740423\",\n \"0.48694378\",\n \"0.4868947\",\n \"0.48684672\",\n \"0.48673344\",\n \"0.4863496\",\n \"0.48625824\",\n \"0.48563123\",\n \"0.48525748\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.80710626"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":81488,"cells":{"query":{"kind":"string","value":"Sixth test of the spin ID generation function. The function tested is pipe_control.mol_res_spin.generate_spin_id_data_array()."},"document":{"kind":"string","value":"def test_generate_spin_id_data_array6(self):\n\n # The data.\n data = ['1', 'GLY', None, None]\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_generate_spin_id_data_array5(self):\n\n # The data.\n data = ['Ap4Aase', '1', 'GLY', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5)\n\n # Test the string.\n self.assertEqual(id, '#Ap4Aase:1@234')","def test_generate_spin_id_data_array1(self):\n\n # The data.\n data = ['1', 'GLY']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')","def test_generate_spin_id_data_array3(self):\n\n # The data.\n data = ['Ap4Aase', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=None, res_name_col=None, spin_num_col=2, spin_name_col=3)\n\n # Test the string.\n self.assertEqual(id, '#Ap4Aase@234')","def test_generate_spin_id_data_array2(self):\n\n # The data.\n data = ['1', 'GLY', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2, spin_num_col=3, spin_name_col=4)\n\n # Test the string.\n self.assertEqual(id, ':1@234')","def test_generate_spin_id_data_array4(self):\n\n # The data.\n data = ['Ap4Aase', '1', 'GLY']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3)\n\n # Test the string.\n self.assertEqual(id, '#Ap4Aase:1')","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def test_random_id(self):\r\n ids = \\\r\n \"R27DLI_4812 R27DLI_600 R27DLI_727 U1PLI_403 U1PLI_8969\".split(\r\n )\r\n assert random_id(ids, {}) in ids\r\n # just test we got something from the list, don't add stochastic test\r","def test_id_array(self):\n arr = vtk.vtkIdTypeArray()\n arr.SetNumberOfTuples(10)\n for i in range(10):\n arr.SetValue(i, i)\n\n np = array_handler.vtk2array(arr)\n self.assertEqual(numpy.all(np == range(10)), True)","def test_spin_loop(self):\n\n # Spin data.\n select = [1, 0]\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, 'N5')\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 2)","def test_create_template(self):\n m_size = 10\n data = ecn.IDData(m_size)\n self.assertEqual(np.shape(data.ID_MATRIX), (m_size, m_size))\n self.assertEqual(sum(sum(data.ID_MATRIX)), m_size)\n self.assertTrue((sum(data.ID_MATRIX) == np.ones(m_size)).all())\n print('Finished testing template\\n')","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_uuid():\n for _ in range(1000):\n uuid = uuid_generator()\n assert len(uuid) == 36\n assert uuid.count('-') == 4","def test_generate(self):\n cant_interations = int(random()*100)\n for i in range(cant_interations):\n number = self.sudoku.generate() # Generate number\n self.assertGreaterEqual(number, 0) # number >= 0\n self.assertLessEqual(number, 8) # number <= 8","def test_scan_id_list(self):\n scan = '15,17'\n ref_idx = [0,3]\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_run_sim_1():\n rnd = rand.Arrivals(36, 41)\n sim.run_sim(3, 2, 5, 6, 22, rnd)","def test_resisc45():\n if not os.path.isdir(os.path.join(DATASET_DIR, \"resisc45_split\", \"3.0.0\")):\n pytest.skip(\"resisc45_split dataset not locally available.\")\n\n for split, size in [(\"train\", 22500), (\"validation\", 4500), (\"test\", 4500)]:\n batch_size = 16\n epochs = 1\n dataset = datasets.resisc45(\n split=split, epochs=epochs, batch_size=batch_size, dataset_dir=DATASET_DIR,\n )\n assert dataset.size == size\n assert dataset.batch_size == batch_size\n assert dataset.batches_per_epoch == (\n size // batch_size + bool(size % batch_size)\n )\n\n x, y = dataset.get_batch()\n assert x.shape == (batch_size, 256, 256, 3)\n assert y.shape == (batch_size,)","def test_kf_id():\n\n for _ in range(1000):\n prefix = ''.join(random.sample(string.ascii_uppercase, 2))\n kf_id = kf_id_generator(prefix)()\n assert kf_id[:2] == prefix\n assert len(kf_id) == 11\n assert kf_id[2] == '_'\n\n assert 'I' not in kf_id[2:]\n assert 'L' not in kf_id[2:]\n assert 'O' not in kf_id[2:]\n assert 'U' not in kf_id[2:]\n\n assert re.search(r'^'+prefix+r'_[A-HJ-KM-NP-TV-Z0-9]{8}', kf_id)","def test_spin_loop_no_selection(self):\n\n # Spin data.\n select = [0, 1, 0, 0, 1, 1, 0, 1]\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 8)","def test_from_structure_klifs_id(\n self, structure_klifs_ids, klifs_session, n_cores, fingerprints_values_array_sum\n ):\n\n fingerprints = FingerprintGenerator.from_structure_klifs_ids(\n structure_klifs_ids, klifs_session, n_cores\n )\n # Test attributes\n # Attribute: structure_klifs_id\n assert fingerprints.structure_klifs_ids == structure_klifs_ids\n # Attribute: klifs_session\n if klifs_session is not None:\n assert fingerprints.klifs_session == klifs_session\n else:\n # If no session was provided, use set up remote session\n assert fingerprints.klifs_session._client is not None\n # Attribute: data\n assert isinstance(fingerprints.data, dict)\n for key, value in fingerprints.data.items():\n assert isinstance(key, int)\n assert isinstance(value, Fingerprint)\n fingerprints_values_array_sum_calculated = sum(\n [\n np.nansum(fingerprint.values_array(True, True, True))\n for _, fingerprint in fingerprints.data.items()\n ]\n )\n assert (\n pytest.approx(fingerprints_values_array_sum_calculated, abs=1e-4)\n == fingerprints_values_array_sum\n )\n\n # Property: subpocket_centers\n assert isinstance(fingerprints.subpocket_centers, pd.DataFrame)\n assert fingerprints.subpocket_centers.index.to_list() == structure_klifs_ids\n assert (\n fingerprints.subpocket_centers.columns.get_level_values(0).to_list()\n == np.repeat(FEATURE_NAMES_DISTANCES_AND_MOMENTS, 3).tolist()\n )\n assert fingerprints.subpocket_centers.columns.get_level_values(1).to_list() == [\n \"x\",\n \"y\",\n \"z\",\n ] * len(FEATURE_NAMES_DISTANCES_AND_MOMENTS)","def test_run_sim():\n rnd = rand.Arrivals(31, 40)\n sim.run_sim(2, 1, 3, 4, 24, rnd)","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_weyl_specialize_id(self):\n a, b, c = 0.0, 0.0, 0.0\n for da, db, dc in DELTAS:\n for k1l, k1r, k2l, k2r in K1K2SB:\n k1 = np.kron(k1l.data, k1r.data)\n k2 = np.kron(k2l.data, k2r.data)\n self.check_two_qubit_weyl_specialization(\n k1 @ Ud(a + da, b + db, c + dc) @ k2,\n 0.999,\n TwoQubitWeylIdEquiv,\n {\"rz\": 4, \"ry\": 2},\n )","def generate_raiz():\n\treturn os.urandom(12)","def test_scan_id_range(self):\n scan = '16~17'\n ref_idx = [1,2,3]\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def myID() -> np.int:\r\n return 304976335","def myID() -> np.int:\r\n return 304976335","def createArrayFunc(self):\r\n minVal = int(self.spinBoxMin_2.value())\r\n maxVal = int(self.spinBoxMax_2.value())\r\n arrayLength = int(self.spinBoxLength_2.value())\r\n different = maxVal - minVal\r\n if self.checkBoxNoRepeate_2.isChecked():\r\n if different > arrayLength:\r\n def unique_rand(initial, limit, total):\r\n data = []\r\n i = 0\r\n while i < total:\r\n number = numpy.random.randint(initial, limit)\r\n if number not in data:\r\n data.append(number)\r\n i += 1\r\n return data\r\n\r\n self.UnsortedArray_2 = unique_rand(minVal, maxVal, arrayLength)\r\n else:\r\n err = \"Array length must be greater than difference between limits\"\r\n self.labelUnsortedArray_2.setText(str(err))\r\n\r\n else:\r\n self.UnsortedArray_2 = numpy.random.randint(minVal, maxVal, arrayLength)\r\n self.labelUnsortedArray_2.setText(str(self.UnsortedArray_2))\r\n self.SortedArray_2 = Insertion.sorting(self.UnsortedArray_2)\r\n self.labelSortedArray_2.setText(str(self.SortedArray_2))\r\n binaryMax = int(self.spinBoxMax_2.value())\r\n binaryMin = int(self.spinBoxMin_2.value())\r\n self.spinBoxBinary.setMaximum(binaryMax)\r\n self.spinBoxBinary.setMinimum(binaryMin)\r\n self.spinBoxIthSmallest.setMaximum(arrayLength + 1)","def test_num_circs_shots(self):\n backend = FakeValencia()\n generator = Generator(backend)\n max_experiments = 5\n max_shots = 10\n backend._configuration.max_experiments = max_experiments\n backend._configuration.max_shots = max_shots\n sub_tests = [1, 3*max_shots, 3*max_shots+1, 3*max_shots-1,\n 3*max_shots*2, 3*max_shots*2+1, 3*max_shots*max_experiments-1]\n for num_raw_bits in sub_tests:\n with self.subTest(num_raw_bits=num_raw_bits):\n result = generator.sample(num_raw_bits=num_raw_bits).block_until_ready()\n self.assertGreaterEqual(len(result.raw_bits), num_raw_bits)","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_id_rot():\n assert_array_almost_equal(pr.R_id, pr.matrix_from_axis_angle(pr.a_id))\n assert_array_almost_equal(pr.R_id, pr.matrix_from_quaternion(pr.q_id))\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_xyz(pr.e_xyz_id))\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_zyx(pr.e_zyx_id))","def NSK129_user_ids():\n return [\n707057500045751944,\n707057500045752170,\n707057500045752255,\n707057500045752231,\n707057500045752217,\n707057500045752194,\n707057500045752156,\n707057500045752132,\n707057500045752118,\n707057500045752088,\n707057500045752064,\n707057500045752057,\n707057500045752033,\n707057500045752002,\n707057500045751982,\n707057500045751975,\n707057500045751937,\n707057500045751913,\n707057500045745844,\n707057500045745851,\n707057500045745929,\n707057500045745936,\n707057500045746001,\n707057500045746018,\n707057500045745868,\n707057500045745875,\n707057500045745943,\n707057500045745950,\n707057500045746025,\n707057500045746032,\n707057500045745882,\n707057500045745837,\n707057500045745899,\n707057500045745974,\n707057500045746049,\n707057500045746056,\n707057500045745905,\n707057500045745981,\n707057500045745998,\n707057500045746063,\n707057500045746070,\n707057500045745912,\n707057500045745639,\n707057500045745707,\n707057500045745714,\n707057500045745783,\n707057500045745790,\n707057500045745646,\n707057500045745653,\n707057500045745738,\n707057500045745806,\n707057500045745615,\n707057500045745776,\n707057500045745622,\n707057500045745578,\n707057500045745585,\n707057500045745592,\n707057500045745813,\n707057500045745660,\n707057500045745684,\n707057500045745721,\n707057500045745769,\n707057500045745677,\n707057500045745745,\n707057500045745752,\n707057500045745608,\n707057500045750442,\n707057500045752613,\n707057500045752606,\n707057500045752163,\n707057500045752200,\n707057500045752224,\n707057500045752149,\n707057500045752187,\n707057500045752293,\n707057500045752286,\n707057500045752071,\n707057500045752040,\n707057500045752095,\n707057500045752125,\n707057500045752101,\n707057500045752026,\n707057500045752279,\n707057500045752262,\n707057500045751814,\n707057500045751807,\n707057500045751890,\n707057500045751883,\n707057500045751876,\n707057500045751869,\n707057500045751821,\n707057500045751838,\n707057500045751845,\n707057500045751852,\n707057500045751999,\n707057500045751951,\n707057500045752019,\n707057500045751920,\n707057500045751968,\n707057500045751906,\n707057500045745691,\n707057500045745967]","def test_test_ids_request(get_interface_params):\n from sail_on_client.protocol.localinterface import LocalInterface\n\n config_directory, config_name = get_interface_params\n data_dir = f\"{os.path.dirname(__file__)}/data\"\n local_interface = LocalInterface(config_name, config_directory)\n\n assumptions_path = os.path.join(os.path.dirname(__file__), \"assumptions.json\")\n filename = local_interface.test_ids_request(\n \"OND\", \"image_classification\", \"5678\", assumptions_path\n )\n expected = os.path.join(data_dir, \"OND\", \"image_classification\", \"test_ids.csv\")\n assert os.stat(expected).st_size > 5\n assert expected == filename","def test_split_id_otp(self):\n public_id, otp, = pyhsm.yubikey.split_id_otp(\"ft\" * 16)\n self.assertEqual(public_id, '')\n self.assertEqual(otp, \"ft\" * 16)\n\n public_id, otp, = pyhsm.yubikey.split_id_otp(\"cc\" + \"ft\" * 16)\n self.assertEqual(public_id, 'cc')\n self.assertEqual(otp, \"ft\" * 16)","def exercise9():\n#seed here is 8\n np.random.seed(seed=8)\n#Generate random numbers from 2 dice for 1000o trials. ranges from [0,5]\n#diceThrows = np.random.randint(6, size=(1000,2))\n #print(diceThrows.shape)\n for i in range(1,11):\n count=0\n diceThrows = np.random.randint(6, size=(1000, 2))\n for x,y in diceThrows:\n if x == 5 and y == 5: #double sixes\n count = count + 1\n\n print(\"Trial \", i, \"= \", count/1000)","def test_random_integers(self):\r\n # Check over two calls to see if the random state is correctly updated.\r\n random = RandomStreams(utt.fetch_seed())\r\n fn = function([], random.random_integers((20, 20), -5, 5))\r\n fn_val0 = fn()\r\n fn_val1 = fn()\r\n\r\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\r\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\r\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\r\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\r\n\r\n assert numpy.all(fn_val0 == numpy_val0)\r\n assert numpy.all(fn_val1 == numpy_val1)","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def generate_T(number_obeservations):\n T = np.random.randint(0, 2, (number_obeservations,1))\n return T","def generate_synth_data(n):","def test_15(self):\n\t self.assertTrue(prime_generator(15), [2, 3, 5, 7, 11, 13])","def test_if_array_is_good(self):\n testing_param = random.randint(1, 100)\n self.assertEqual(self.exercice.main(testing_param),\n list(range(2, testing_param+1, 2)))","def generate_new_ids(ids: np.array, n_required: int) -> np.array:\n\n current_max_id = ids.max()\n new_ids = np.arange(n_required) + current_max_id + 1\n\n return new_ids","def test_get_ids(civic, main_data, updated_data):\n assert len(civic._get_ids(main_data['assertions'])) == 0\n assert len(civic._get_ids(main_data['variants'])) == 1\n assert len(civic._get_ids(main_data['genes'])) == 2\n assert len(civic._get_ids(main_data['evidence'])) == 1\n\n assert len(civic._get_ids(updated_data['assertions'])) == 1\n assert len(civic._get_ids(updated_data['variants'])) == 1\n assert len(civic._get_ids(updated_data['genes'])) == 1\n assert len(civic._get_ids(updated_data['evidence'])) == 1","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def generaterandomindices(dataSize, percentTest):\n\n TrainIndices = np.array([])\n while TrainIndices.__len__() < int(percentTest * dataSize):\n # Randomly select an index value and store it. If it has already been chosen, pick again.\n index = int(random.random() * dataSize)\n if not TrainIndices.__contains__(index):\n TrainIndices = np.append(TrainIndices, [index])\n\n # For aesthetic purposes:\n TrainIndices = np.sort(TrainIndices)\n\n return TrainIndices","def test_task559_eratosthenes(number, expected_value):\r\n assert algo.Task559.eratosthenes(number) == expected_value","def tubeid():\n return binascii.hexlify(os.urandom(12))","def test_random_integers(self):\r\n # Check over two calls to see if the random state is correctly updated.\r\n m = Module()\r\n m.random = RandomStreams(utt.fetch_seed())\r\n m.fn = Method([], m.random.random_integers((20,20), -5, 5))\r\n\r\n made = m.make()\r\n made.random.initialize()\r\n fn_val0 = made.fn()\r\n fn_val1 = made.fn()\r\n\r\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\r\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\r\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\r\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\r\n\r\n assert numpy.all(fn_val0 == numpy_val0)\r\n assert numpy.all(fn_val1 == numpy_val1)","def genNumID(size):\n\tid = \"\"\n\tfor i in range(size):\n\t\tid = id + selectRandomFromList(numTokens)\n\treturn id","def generate_subsegment_id():\n return uuid.uuid4().hex[:16]","def generate_run_id(self):\n r_id_len = 4\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\n while r_id in self.cache:\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\n return r_id","def test_generateuuids(self):\n ret1 = {\"message\": \"No Random.org api key or api version found.\", \"res\": False}\n self.assertDictEqual(random_org.generateUUIDs(), ret1)\n\n ret2 = {\"message\": \"Required argument, number is missing.\", \"res\": False}\n self.assertDictEqual(\n random_org.generateUUIDs(api_key=\"peW\", api_version=\"1\"), ret2\n )\n\n ret3 = {\"message\": \"Number of UUIDs must be between 1 and 1000\", \"res\": False}\n self.assertDictEqual(\n random_org.generateUUIDs(api_key=\"peW\", api_version=\"1\", number=\"5\"), ret3\n )\n\n ret3 = {\"message\": \"Parameter 'apiKey' is malformed\", \"res\": False}\n self.assertDictEqual(\n random_org.generateUUIDs(api_key=\"peW\", api_version=\"1\", number=5), ret3\n )","def test_spin_loop_wildcard(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N*'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_generate_factoid():\n generator = mockdata.generate_factoid()\n for i in range(100):\n factoid = next(generator)\n assert factoid[\"@id\"] == \"Factoid %03d\" % (i + 1)\n assert \"Person\" in factoid[\"person\"][\"@id\"]\n assert \"Source\" in factoid[\"source\"][\"@id\"]\n assert \"statement\" in factoid\n assert factoid[\"statement\"][\"@id\"] == \"F%dS1\" % (i + 1)","def spinWheel():\n\tt = random.randrange(8)\n\tif t == 7:\n\t\treturn \"00\"\n\treturn str(t)","def test_apply_ridit(self):\n x, x_rand, s = self.create_testdata()\n task = mmRDTR()\n s = task.check_sparse(s)\n\n for data in [x, x_rand, s]:\n #get ecdf for data\n Fn=task.make_ECDF(data)\n out=task.apply_ridit( data, Fn )\n # check same dimension\n self.assertEqual(np.all(data.shape==out.shape),True)\n # check mean almost equal to 0\n for i in range(data.shape[1]):\n self.assertEqual(round(out[:,i].mean(),8),0)\n # check if works with newdata\n newdata=data[:2]\n out=task.apply_ridit( newdata, Fn )\n # check same dimension\n self.assertEqual(np.all(newdata.shape==out.shape),True)","def genSCID():\n scid_hex = getRandomBytes(8)\n scid_hex = getSHA256Hex(scid_hex)\n scid_hex = scid_hex[0:8]\n return scid_hex","def _apply_array_spin123(self,\n h1e: 'Nparray',\n h2e: 'Nparray',\n h3e: 'Nparray',\n dvec: Optional[Tuple['Nparray', 'Nparray']] = None,\n evec: Optional[Tuple['Nparray', 'Nparray', 'Nparray', 'Nparray']] \\\n = None) -> 'Nparray':\n norb = self.norb()\n assert h3e.shape == (norb * 2,) * 6\n assert not (dvec is None) ^ (evec is None)\n\n from1234 = (dvec is not None) and (evec is not None)\n\n nh1e = numpy.copy(h1e)\n nh2e = numpy.copy(h2e)\n\n for i in range(norb * 2):\n for j in range(norb * 2):\n for k in range(norb * 2):\n nh2e[j, k, :, :] += (-h3e[k, j, i, i, :, :] -\n h3e[j, i, k, i, :, :] -\n h3e[j, k, i, :, i, :])\n\n nh1e[:, :] += h3e[:, i, j, i, j, :]\n\n out = self._apply_array_spin12_halffilling(nh1e, nh2e)\n\n n = norb # This is just shorter\n if not from1234:\n symfac = 2.0\n axes = ((1, 3), (0, 1))\n (odveca, odvecb) = self.calculate_dvec_spin()\n dveca = numpy.zeros_like(odveca)\n dvecb = numpy.zeros_like(odvecb)\n\n for i in range(norb):\n for j in range(norb):\n evecaa, _ = self._calculate_dvec_spin_with_coeff(\n odveca[i, j, :, :])\n evecab, evecbb = self._calculate_dvec_spin_with_coeff(\n odvecb[i, j, :, :])\n\n dveca += numpy.tensordot(h3e[:n, :n, i, :n, :n, j],\n evecaa,\n axes=axes)\n dveca += numpy.tensordot(h3e[:n, :n, n + i, :n, :n, n + j],\n evecab,\n axes=axes) * symfac\n dveca += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\n evecbb,\n axes=axes)\n\n dvecb += numpy.tensordot(h3e[n:, :n, i, n:, :n, j],\n evecaa,\n axes=axes)\n dvecb += numpy.tensordot(h3e[n:, :n, n + i, n:, :n, n + j],\n evecab,\n axes=axes) * symfac\n dvecb += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\n evecbb,\n axes=axes)\n else:\n symfac = 1.0\n axes = ((1, 4, 2, 5), (0, 1, 2, 3)) # type: ignore\n dveca, dvecb = dvec # type: ignore\n evecaa, evecab, evecba, evecbb = evec # type: ignore\n\n dveca = numpy.tensordot(h3e[:n, :n, :n, :n, :n, :n],\n evecaa, axes=axes) \\\n + numpy.tensordot(h3e[:n, :n, n:, :n, :n, n:],\n evecab, axes=axes) * symfac \\\n + numpy.tensordot(h3e[:n, n:, n:, :n, n:, n:],\n evecbb, axes=axes) + \\\n + numpy.tensordot(h3e[:n, n:, :n, :n, n:, :n],\n evecba, axes=axes)\n\n dvecb = numpy.tensordot(h3e[n:, :n, :n, n:, :n, :n],\n evecaa, axes=axes) \\\n + numpy.tensordot(h3e[n:, :n, n:, n:, :n, n:],\n evecab, axes=axes) * symfac \\\n + numpy.tensordot(h3e[n:, n:, n:, n:, n:, n:],\n evecbb, axes=axes) + \\\n + numpy.tensordot(h3e[n:, n:, :n, n:, n:, :n],\n evecba, axes=axes)\n\n out -= self._calculate_coeff_spin_with_dvec((dveca, dvecb))\n return out","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_arbitrary_rotation(self):\n \n # This test is run a bunch of times on various intervals, ranging from 50% to 1/6\n\t\t# (16.667%).\n for i in range(2, 7):\n \n interval = 1 / i # The amount to increase each qubit's probability by, relative to the previous qubit\n step_string = \"{:.4f}\".format(100 / i) # The decimal representation of the interval, as a percent\n target_probabilities = [0] * (i + 1) # This will store the desired probabilities of each qubit\n for j in range(0, i + 1):\n target_probability = j * interval\n target_probabilities[j] = target_probability\n\n # Run the test\n self.run_test(self.arbitrary_rotation_function, f\"Rotation with steps of 1/{i} ({step_string}%)\", 2000, target_probabilities, 0.05)","def _generate_id() -> str:\n return \"\".join(sample(\"abcdefghjkmopqrstuvqxyz\", 16))","def test_api_random_id(api_client, single_brew_number):\n response = api_client.get(path='/breweries' + '/' + str(single_brew_number))\n assert response.json()['id'] == single_brew_number","def test_WINNF_FT_S_REG_17(self):\n\n # Register device\n device_a = json.load(\n open(os.path.join('testcases', 'testdata', 'device_a.json')))\n self._sas_admin.InjectFccId({'fccId': device_a['fccId']})\n # Register the device\n request = {'registrationRequest': [device_a]}\n response = self._sas.Registration(request)['registrationResponse'][0]\n # Check registration response\n self.assertTrue('cbsdId' in response)\n self.assertEqual(response['response']['responseCode'], 0)\n cbsd_id = response['cbsdId']\n del request, response\n\n # Blacklist the device\n self._sas_admin.BlacklistByFccId({'fccId':device_a['fccId']})\n\n # Re-register the device\n request = {'registrationRequest': [device_a]}\n response = self._sas.Registration(request)['registrationResponse'][0]\n\n # Check registration response\n self.assertFalse('cbsdId' in response)\n self.assertEqual(response['response']['responseCode'], 101)","def get_refresh_ids(self):\n ids = []\n for bucket in self.router.lonely_buckets():\n rid = random.randint(*bucket.range).to_bytes(20, byteorder='big')\n ids.append(rid)\n return ids","def test_spin_type(get_pdos_generator_inputs):\n with pytest.raises(NotImplementedError):\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=spin_type)\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=SpinType.COLLINEAR)\n for namespace in [builder.scf, builder.nscf]:\n parameters = namespace['pw']['parameters'].get_dict()\n assert parameters['SYSTEM']['nspin'] == 2\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}","def cifar_iid(dataset, num_users):\n print(\"Sampling dataset: CIFAR-10 IID\")\n num_items = int(len(dataset)/num_users)\n dict_users, all_idxs = {}, [i for i in range(len(dataset))]\n for i in range(num_users):\n dict_users[i] = set(np.random.choice(all_idxs, num_items, replace=False))\n all_idxs = list(set(all_idxs) - dict_users[i])\n return dict_users","def test_start_ids_10(self):\n\n\t\texpected_num_layers = 11\n\t\texpected_ids = np.arange(10,21)\n\t\t# test describe\n\t\tdetails = self.watcher.describe(start_ids=10)\n\t\tprint(\"start id = 10\", details)\n\t\tactual_ids = details.layer_id.to_numpy().tolist()\n\t\tself.assertTrue(np.array_equal(actual_ids, expected_ids))\n\t\tself.assertEqual(len(expected_ids), expected_num_layers)\n\t\t\t\t\n\t\treturn","def _get_rand_array(self):\n pass","def iv_gen():\r\n rndiv = os.urandom(16)\r\n return rndiv","def create_code():\n\n code = [0, 0, 0, 0]\n\n for i in range(4):\n value = random.randint(1, 8) # 8 possible digits\n while value in code:\n value = random.randint(1, 8) # 8 possible digits\n code[i] = value\n \n #print(code)\n return code","def test_generation_index_zero(self):\n generator = math_helpers.triangle_number_generator()\n first_eleven_triangle_numbers = [next(generator) for _ in range(11)]\n canonical_values = [0, 1, 3, 6, 10, 15, 21, 28, 36, 45, 55]\n self.assertEqual(canonical_values, first_eleven_triangle_numbers)","def test_scan_id_gt(self):\n scan = '>16'\n ref_idx = [3]\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_scan_id_lt(self):\n scan = '<16'\n ref_idx = [0]\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_stickers(self):\n rotation, _ = list(self.cube.scramble_cube(15))\n\n unique, counts = np.unique(rotation, return_counts=True)\n dictionary = dict(zip(unique, counts))\n\n self.assertEqual(all(value == 4 for value in dictionary.values()), True)","def test_scan_id_exprlist(self):\n scan = '15,>16'\n ref_idx = [0,3]\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_brains_id_get(self):\n pass","def test_spin_loop_multiatom(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_run_a_scan_on_sdp_subarray_in_low():","def get_test_split(self, fraction=0.1):\n rng = np.random.default_rng(42)\n test_size = int(round(len(self.all_asset_ids) * fraction))\n test_ids = rng.choice(self.all_asset_ids, size=test_size, replace=False)\n train_ids = [i for i in self.all_asset_ids if i not in test_ids]\n return train_ids, test_ids","def test_run_a_scan_on_sdp_subarray_in_mid():","def test_residue_loop(self):\n\n # Loop over the residues.\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\n # Test the selection.\n self.assertEqual(res.num, 2)\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)","def test_returned_num_in_random_nums(self):\n self._setup_random_gen([1.], [42])\n self.assertEqual(self._random_gen.next_num(), 42)","def test_arr2vtkIdList(self):\n a = [1, 2, 3, 4, 5]\n p = array_handler.array2vtkIdList(a)\n for i, j in enumerate(a): \n self.assertEqual(p.GetId(i), j)\n p = vtk.vtkIdList()\n ident = id(p)\n p = array_handler.array2vtkIdList(numpy.array(a), p)\n for i, j in enumerate(a): \n self.assertEqual(p.GetId(i), j)\n self.assertEqual(id(p), ident)\n \n self.assertRaises(AssertionError, array_handler.array2vtkIdList,\n [[1,2,3]])","def test_get_new_otu_id_large(self):\r\n tree = DndParser(\"(A:0.1,B:0.2,(C:0.3,D:0.4):0.5);\")\r\n results = []\r\n for i in range(1000):\r\n results.append(qiime.simsam.get_new_otu_id(old_otu_id='D',\r\n tree=tree, dissim=.6))\r\n self.assertTrue('C' in results)\r\n self.assertTrue('D' in results)\r\n self.assertTrue('A' not in results)\r\n self.assertTrue('B' not in results)","def test_ids(self):\n # AdapterID inherited from IOAdapter\n self.assertEqual('553713696', self.sriovs[0].id)\n self.assertEqual(1, self.sriovs[0].sriov_adap_id)\n\n self.assertEqual('553713680', self.sriovs[2].id)\n self.assertIsNone(self.sriovs[2].sriov_adap_id)","def gen_data(min_coord, max_coord, size):\r\n data = np.random.randint(min_coord, max_coord, size)\r\n return data","def data_gen(size, p):\n #print(np.random.get_state()[1][0])\n random_table = np.random.binomial(size = size, p = p, n = 1)\n test_array = np.zeros((size, 2), dtype = int)\n for i in range(size):\n test_array[i,0] = i\n test_array[i,1] = random_table[i]\n return test_array","def test1():\n for test in pkl.load(open(TEST_RESOURCES_DIR / \"regression_vault.pkl\", \"rb\"))[:5]:\n init_dict, rslt = test\n np.testing.assert_array_equal(run_regression_test(init_dict), rslt)","def generateRegistrationId():\n regId = KeyHelper.getRandomSequence()\n return regId","def test_id_get(mocker):\n mocker.patch('serial.Serial.open')\n mocker.patch('serial.Serial.flushInput')\n css = mocker.patch('pysds011.driver.SDS011.cmd_set_sleep')\n css.return_value = True\n cfv = mocker.patch('pysds011.driver.SDS011.cmd_firmware_ver')\n cfv.return_value = {'id': b'\\x12\\x34', 'paperino': 'maciomicio'}\n runner = CliRunner()\n result = runner.invoke(main, ['id'])\n\n calls = [call(0, id=b'\\xff\\xff'), call(1, id=b'\\xff\\xff')]\n css.assert_has_calls(calls, any_order=False)\n\n assert '12' in result.output and '34' in result.output\n assert result.exit_code == 0","def test_generation_index_one(self):\n generator = math_helpers.triangle_number_generator(1)\n first_ten_triangle_numbers = [next(generator) for _ in range(10)]\n canonical_values = [1, 3, 6, 10, 15, 21, 28, 36, 45, 55]\n self.assertEqual(canonical_values, first_ten_triangle_numbers)","def test_pol_id_list(self):\n pol = '0,1'\n ref_idx = []\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_random_generator(self):\n gen = random_data()\n data = [next(gen) for _ in range(100)]\n self.assertEqual(len(data), 100)","def test_rand_func2(self):\n for i in range(0, 100000):\n num = random.randint(0, 32535143990)\n func2_comp(num)","def test_get_tid():\n tids = []\n def _foo():\n mytid = yield GetTid()\n tids.append(mytid)\n for i in range(5):\n yield i\n\n scheduler = Scheduler()\n scheduler.new(_foo())\n scheduler.new(_foo())\n scheduler.mainloop()\n\n # can we do better than hard code?\n assert tids == [4, 5]","def test_generation(self):\n generator = math_helpers.hexagonal_number_generator()\n first_ten_hex_numbers = [next(generator) for _ in range(10)]\n canonical_values = [1, 6, 15, 28, 45, 66, 91, 120, 153, 190]\n self.assertEqual(canonical_values, first_ten_hex_numbers)","def test_generate_mine_sequence(self):\n mine_list = utils.generate_mine_sequence(1)\n self.assertEqual(len(mine_list), utils.MINE_COUNT)","def test_spin_type(fixture_code, generate_structure):\n code = fixture_code('quantumespresso.pw')\n structure = generate_structure()\n\n with pytest.raises(NotImplementedError):\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\n PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=spin_type)\n\n builder = PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=SpinType.COLLINEAR)\n\n for namespace in [builder.relax['base'], builder.scf, builder.bands]:\n parameters = namespace['pw']['parameters'].get_dict()\n assert parameters['SYSTEM']['nspin'] == 2\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}","def generate_mixture_indicator(number_obeservations):\n mixture_indicator = np.random.randint(0, 2, (number_obeservations,1))\n return mixture_indicator","def random_lottery():\n\treturn 0","def test_main(data, tmp_path):\n\n main(data, tmp_path)\n\n FILES = (\n \"gd32f888x(0-1)xx-pinctrl.h\",\n \"gd32f888x(2-3)xx-pinctrl.h\",\n \"gd32f888y(0-1)xx-pinctrl.h\",\n \"gd32f999x(0-1)xx-pinctrl.h\",\n \"gd32f999x(2-3)xx-pinctrl.h\",\n \"gd32f999y(0-1)xx-pinctrl.h\",\n )\n\n for file in FILES:\n ref_file = data / file\n gen_file = tmp_path / file\n\n assert gen_file.exists()\n\n with open(ref_file) as ref, open(gen_file) as gen:\n assert ref.read() == gen.read()"],"string":"[\n \"def test_generate_spin_id_data_array5(self):\\n\\n # The data.\\n data = ['Ap4Aase', '1', 'GLY', '234', 'NH']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5)\\n\\n # Test the string.\\n self.assertEqual(id, '#Ap4Aase:1@234')\",\n \"def test_generate_spin_id_data_array1(self):\\n\\n # The data.\\n data = ['1', 'GLY']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\\n\\n # Test the string.\\n self.assertEqual(id, ':1')\",\n \"def test_generate_spin_id_data_array3(self):\\n\\n # The data.\\n data = ['Ap4Aase', '234', 'NH']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=None, res_name_col=None, spin_num_col=2, spin_name_col=3)\\n\\n # Test the string.\\n self.assertEqual(id, '#Ap4Aase@234')\",\n \"def test_generate_spin_id_data_array2(self):\\n\\n # The data.\\n data = ['1', 'GLY', '234', 'NH']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2, spin_num_col=3, spin_name_col=4)\\n\\n # Test the string.\\n self.assertEqual(id, ':1@234')\",\n \"def test_generate_spin_id_data_array4(self):\\n\\n # The data.\\n data = ['Ap4Aase', '1', 'GLY']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3)\\n\\n # Test the string.\\n self.assertEqual(id, '#Ap4Aase:1')\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def test_random_id(self):\\r\\n ids = \\\\\\r\\n \\\"R27DLI_4812 R27DLI_600 R27DLI_727 U1PLI_403 U1PLI_8969\\\".split(\\r\\n )\\r\\n assert random_id(ids, {}) in ids\\r\\n # just test we got something from the list, don't add stochastic test\\r\",\n \"def test_id_array(self):\\n arr = vtk.vtkIdTypeArray()\\n arr.SetNumberOfTuples(10)\\n for i in range(10):\\n arr.SetValue(i, i)\\n\\n np = array_handler.vtk2array(arr)\\n self.assertEqual(numpy.all(np == range(10)), True)\",\n \"def test_spin_loop(self):\\n\\n # Spin data.\\n select = [1, 0]\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, 'N5')\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 2)\",\n \"def test_create_template(self):\\n m_size = 10\\n data = ecn.IDData(m_size)\\n self.assertEqual(np.shape(data.ID_MATRIX), (m_size, m_size))\\n self.assertEqual(sum(sum(data.ID_MATRIX)), m_size)\\n self.assertTrue((sum(data.ID_MATRIX) == np.ones(m_size)).all())\\n print('Finished testing template\\\\n')\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_uuid():\\n for _ in range(1000):\\n uuid = uuid_generator()\\n assert len(uuid) == 36\\n assert uuid.count('-') == 4\",\n \"def test_generate(self):\\n cant_interations = int(random()*100)\\n for i in range(cant_interations):\\n number = self.sudoku.generate() # Generate number\\n self.assertGreaterEqual(number, 0) # number >= 0\\n self.assertLessEqual(number, 8) # number <= 8\",\n \"def test_scan_id_list(self):\\n scan = '15,17'\\n ref_idx = [0,3]\\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_run_sim_1():\\n rnd = rand.Arrivals(36, 41)\\n sim.run_sim(3, 2, 5, 6, 22, rnd)\",\n \"def test_resisc45():\\n if not os.path.isdir(os.path.join(DATASET_DIR, \\\"resisc45_split\\\", \\\"3.0.0\\\")):\\n pytest.skip(\\\"resisc45_split dataset not locally available.\\\")\\n\\n for split, size in [(\\\"train\\\", 22500), (\\\"validation\\\", 4500), (\\\"test\\\", 4500)]:\\n batch_size = 16\\n epochs = 1\\n dataset = datasets.resisc45(\\n split=split, epochs=epochs, batch_size=batch_size, dataset_dir=DATASET_DIR,\\n )\\n assert dataset.size == size\\n assert dataset.batch_size == batch_size\\n assert dataset.batches_per_epoch == (\\n size // batch_size + bool(size % batch_size)\\n )\\n\\n x, y = dataset.get_batch()\\n assert x.shape == (batch_size, 256, 256, 3)\\n assert y.shape == (batch_size,)\",\n \"def test_kf_id():\\n\\n for _ in range(1000):\\n prefix = ''.join(random.sample(string.ascii_uppercase, 2))\\n kf_id = kf_id_generator(prefix)()\\n assert kf_id[:2] == prefix\\n assert len(kf_id) == 11\\n assert kf_id[2] == '_'\\n\\n assert 'I' not in kf_id[2:]\\n assert 'L' not in kf_id[2:]\\n assert 'O' not in kf_id[2:]\\n assert 'U' not in kf_id[2:]\\n\\n assert re.search(r'^'+prefix+r'_[A-HJ-KM-NP-TV-Z0-9]{8}', kf_id)\",\n \"def test_spin_loop_no_selection(self):\\n\\n # Spin data.\\n select = [0, 1, 0, 0, 1, 1, 0, 1]\\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 8)\",\n \"def test_from_structure_klifs_id(\\n self, structure_klifs_ids, klifs_session, n_cores, fingerprints_values_array_sum\\n ):\\n\\n fingerprints = FingerprintGenerator.from_structure_klifs_ids(\\n structure_klifs_ids, klifs_session, n_cores\\n )\\n # Test attributes\\n # Attribute: structure_klifs_id\\n assert fingerprints.structure_klifs_ids == structure_klifs_ids\\n # Attribute: klifs_session\\n if klifs_session is not None:\\n assert fingerprints.klifs_session == klifs_session\\n else:\\n # If no session was provided, use set up remote session\\n assert fingerprints.klifs_session._client is not None\\n # Attribute: data\\n assert isinstance(fingerprints.data, dict)\\n for key, value in fingerprints.data.items():\\n assert isinstance(key, int)\\n assert isinstance(value, Fingerprint)\\n fingerprints_values_array_sum_calculated = sum(\\n [\\n np.nansum(fingerprint.values_array(True, True, True))\\n for _, fingerprint in fingerprints.data.items()\\n ]\\n )\\n assert (\\n pytest.approx(fingerprints_values_array_sum_calculated, abs=1e-4)\\n == fingerprints_values_array_sum\\n )\\n\\n # Property: subpocket_centers\\n assert isinstance(fingerprints.subpocket_centers, pd.DataFrame)\\n assert fingerprints.subpocket_centers.index.to_list() == structure_klifs_ids\\n assert (\\n fingerprints.subpocket_centers.columns.get_level_values(0).to_list()\\n == np.repeat(FEATURE_NAMES_DISTANCES_AND_MOMENTS, 3).tolist()\\n )\\n assert fingerprints.subpocket_centers.columns.get_level_values(1).to_list() == [\\n \\\"x\\\",\\n \\\"y\\\",\\n \\\"z\\\",\\n ] * len(FEATURE_NAMES_DISTANCES_AND_MOMENTS)\",\n \"def test_run_sim():\\n rnd = rand.Arrivals(31, 40)\\n sim.run_sim(2, 1, 3, 4, 24, rnd)\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_weyl_specialize_id(self):\\n a, b, c = 0.0, 0.0, 0.0\\n for da, db, dc in DELTAS:\\n for k1l, k1r, k2l, k2r in K1K2SB:\\n k1 = np.kron(k1l.data, k1r.data)\\n k2 = np.kron(k2l.data, k2r.data)\\n self.check_two_qubit_weyl_specialization(\\n k1 @ Ud(a + da, b + db, c + dc) @ k2,\\n 0.999,\\n TwoQubitWeylIdEquiv,\\n {\\\"rz\\\": 4, \\\"ry\\\": 2},\\n )\",\n \"def generate_raiz():\\n\\treturn os.urandom(12)\",\n \"def test_scan_id_range(self):\\n scan = '16~17'\\n ref_idx = [1,2,3]\\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def myID() -> np.int:\\r\\n return 304976335\",\n \"def myID() -> np.int:\\r\\n return 304976335\",\n \"def createArrayFunc(self):\\r\\n minVal = int(self.spinBoxMin_2.value())\\r\\n maxVal = int(self.spinBoxMax_2.value())\\r\\n arrayLength = int(self.spinBoxLength_2.value())\\r\\n different = maxVal - minVal\\r\\n if self.checkBoxNoRepeate_2.isChecked():\\r\\n if different > arrayLength:\\r\\n def unique_rand(initial, limit, total):\\r\\n data = []\\r\\n i = 0\\r\\n while i < total:\\r\\n number = numpy.random.randint(initial, limit)\\r\\n if number not in data:\\r\\n data.append(number)\\r\\n i += 1\\r\\n return data\\r\\n\\r\\n self.UnsortedArray_2 = unique_rand(minVal, maxVal, arrayLength)\\r\\n else:\\r\\n err = \\\"Array length must be greater than difference between limits\\\"\\r\\n self.labelUnsortedArray_2.setText(str(err))\\r\\n\\r\\n else:\\r\\n self.UnsortedArray_2 = numpy.random.randint(minVal, maxVal, arrayLength)\\r\\n self.labelUnsortedArray_2.setText(str(self.UnsortedArray_2))\\r\\n self.SortedArray_2 = Insertion.sorting(self.UnsortedArray_2)\\r\\n self.labelSortedArray_2.setText(str(self.SortedArray_2))\\r\\n binaryMax = int(self.spinBoxMax_2.value())\\r\\n binaryMin = int(self.spinBoxMin_2.value())\\r\\n self.spinBoxBinary.setMaximum(binaryMax)\\r\\n self.spinBoxBinary.setMinimum(binaryMin)\\r\\n self.spinBoxIthSmallest.setMaximum(arrayLength + 1)\",\n \"def test_num_circs_shots(self):\\n backend = FakeValencia()\\n generator = Generator(backend)\\n max_experiments = 5\\n max_shots = 10\\n backend._configuration.max_experiments = max_experiments\\n backend._configuration.max_shots = max_shots\\n sub_tests = [1, 3*max_shots, 3*max_shots+1, 3*max_shots-1,\\n 3*max_shots*2, 3*max_shots*2+1, 3*max_shots*max_experiments-1]\\n for num_raw_bits in sub_tests:\\n with self.subTest(num_raw_bits=num_raw_bits):\\n result = generator.sample(num_raw_bits=num_raw_bits).block_until_ready()\\n self.assertGreaterEqual(len(result.raw_bits), num_raw_bits)\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_id_rot():\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_axis_angle(pr.a_id))\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_quaternion(pr.q_id))\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_xyz(pr.e_xyz_id))\\n assert_array_almost_equal(pr.R_id, pr.matrix_from_euler_zyx(pr.e_zyx_id))\",\n \"def NSK129_user_ids():\\n return [\\n707057500045751944,\\n707057500045752170,\\n707057500045752255,\\n707057500045752231,\\n707057500045752217,\\n707057500045752194,\\n707057500045752156,\\n707057500045752132,\\n707057500045752118,\\n707057500045752088,\\n707057500045752064,\\n707057500045752057,\\n707057500045752033,\\n707057500045752002,\\n707057500045751982,\\n707057500045751975,\\n707057500045751937,\\n707057500045751913,\\n707057500045745844,\\n707057500045745851,\\n707057500045745929,\\n707057500045745936,\\n707057500045746001,\\n707057500045746018,\\n707057500045745868,\\n707057500045745875,\\n707057500045745943,\\n707057500045745950,\\n707057500045746025,\\n707057500045746032,\\n707057500045745882,\\n707057500045745837,\\n707057500045745899,\\n707057500045745974,\\n707057500045746049,\\n707057500045746056,\\n707057500045745905,\\n707057500045745981,\\n707057500045745998,\\n707057500045746063,\\n707057500045746070,\\n707057500045745912,\\n707057500045745639,\\n707057500045745707,\\n707057500045745714,\\n707057500045745783,\\n707057500045745790,\\n707057500045745646,\\n707057500045745653,\\n707057500045745738,\\n707057500045745806,\\n707057500045745615,\\n707057500045745776,\\n707057500045745622,\\n707057500045745578,\\n707057500045745585,\\n707057500045745592,\\n707057500045745813,\\n707057500045745660,\\n707057500045745684,\\n707057500045745721,\\n707057500045745769,\\n707057500045745677,\\n707057500045745745,\\n707057500045745752,\\n707057500045745608,\\n707057500045750442,\\n707057500045752613,\\n707057500045752606,\\n707057500045752163,\\n707057500045752200,\\n707057500045752224,\\n707057500045752149,\\n707057500045752187,\\n707057500045752293,\\n707057500045752286,\\n707057500045752071,\\n707057500045752040,\\n707057500045752095,\\n707057500045752125,\\n707057500045752101,\\n707057500045752026,\\n707057500045752279,\\n707057500045752262,\\n707057500045751814,\\n707057500045751807,\\n707057500045751890,\\n707057500045751883,\\n707057500045751876,\\n707057500045751869,\\n707057500045751821,\\n707057500045751838,\\n707057500045751845,\\n707057500045751852,\\n707057500045751999,\\n707057500045751951,\\n707057500045752019,\\n707057500045751920,\\n707057500045751968,\\n707057500045751906,\\n707057500045745691,\\n707057500045745967]\",\n \"def test_test_ids_request(get_interface_params):\\n from sail_on_client.protocol.localinterface import LocalInterface\\n\\n config_directory, config_name = get_interface_params\\n data_dir = f\\\"{os.path.dirname(__file__)}/data\\\"\\n local_interface = LocalInterface(config_name, config_directory)\\n\\n assumptions_path = os.path.join(os.path.dirname(__file__), \\\"assumptions.json\\\")\\n filename = local_interface.test_ids_request(\\n \\\"OND\\\", \\\"image_classification\\\", \\\"5678\\\", assumptions_path\\n )\\n expected = os.path.join(data_dir, \\\"OND\\\", \\\"image_classification\\\", \\\"test_ids.csv\\\")\\n assert os.stat(expected).st_size > 5\\n assert expected == filename\",\n \"def test_split_id_otp(self):\\n public_id, otp, = pyhsm.yubikey.split_id_otp(\\\"ft\\\" * 16)\\n self.assertEqual(public_id, '')\\n self.assertEqual(otp, \\\"ft\\\" * 16)\\n\\n public_id, otp, = pyhsm.yubikey.split_id_otp(\\\"cc\\\" + \\\"ft\\\" * 16)\\n self.assertEqual(public_id, 'cc')\\n self.assertEqual(otp, \\\"ft\\\" * 16)\",\n \"def exercise9():\\n#seed here is 8\\n np.random.seed(seed=8)\\n#Generate random numbers from 2 dice for 1000o trials. ranges from [0,5]\\n#diceThrows = np.random.randint(6, size=(1000,2))\\n #print(diceThrows.shape)\\n for i in range(1,11):\\n count=0\\n diceThrows = np.random.randint(6, size=(1000, 2))\\n for x,y in diceThrows:\\n if x == 5 and y == 5: #double sixes\\n count = count + 1\\n\\n print(\\\"Trial \\\", i, \\\"= \\\", count/1000)\",\n \"def test_random_integers(self):\\r\\n # Check over two calls to see if the random state is correctly updated.\\r\\n random = RandomStreams(utt.fetch_seed())\\r\\n fn = function([], random.random_integers((20, 20), -5, 5))\\r\\n fn_val0 = fn()\\r\\n fn_val1 = fn()\\r\\n\\r\\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\\r\\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\\r\\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\\r\\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\\r\\n\\r\\n assert numpy.all(fn_val0 == numpy_val0)\\r\\n assert numpy.all(fn_val1 == numpy_val1)\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def generate_T(number_obeservations):\\n T = np.random.randint(0, 2, (number_obeservations,1))\\n return T\",\n \"def generate_synth_data(n):\",\n \"def test_15(self):\\n\\t self.assertTrue(prime_generator(15), [2, 3, 5, 7, 11, 13])\",\n \"def test_if_array_is_good(self):\\n testing_param = random.randint(1, 100)\\n self.assertEqual(self.exercice.main(testing_param),\\n list(range(2, testing_param+1, 2)))\",\n \"def generate_new_ids(ids: np.array, n_required: int) -> np.array:\\n\\n current_max_id = ids.max()\\n new_ids = np.arange(n_required) + current_max_id + 1\\n\\n return new_ids\",\n \"def test_get_ids(civic, main_data, updated_data):\\n assert len(civic._get_ids(main_data['assertions'])) == 0\\n assert len(civic._get_ids(main_data['variants'])) == 1\\n assert len(civic._get_ids(main_data['genes'])) == 2\\n assert len(civic._get_ids(main_data['evidence'])) == 1\\n\\n assert len(civic._get_ids(updated_data['assertions'])) == 1\\n assert len(civic._get_ids(updated_data['variants'])) == 1\\n assert len(civic._get_ids(updated_data['genes'])) == 1\\n assert len(civic._get_ids(updated_data['evidence'])) == 1\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def generaterandomindices(dataSize, percentTest):\\n\\n TrainIndices = np.array([])\\n while TrainIndices.__len__() < int(percentTest * dataSize):\\n # Randomly select an index value and store it. If it has already been chosen, pick again.\\n index = int(random.random() * dataSize)\\n if not TrainIndices.__contains__(index):\\n TrainIndices = np.append(TrainIndices, [index])\\n\\n # For aesthetic purposes:\\n TrainIndices = np.sort(TrainIndices)\\n\\n return TrainIndices\",\n \"def test_task559_eratosthenes(number, expected_value):\\r\\n assert algo.Task559.eratosthenes(number) == expected_value\",\n \"def tubeid():\\n return binascii.hexlify(os.urandom(12))\",\n \"def test_random_integers(self):\\r\\n # Check over two calls to see if the random state is correctly updated.\\r\\n m = Module()\\r\\n m.random = RandomStreams(utt.fetch_seed())\\r\\n m.fn = Method([], m.random.random_integers((20,20), -5, 5))\\r\\n\\r\\n made = m.make()\\r\\n made.random.initialize()\\r\\n fn_val0 = made.fn()\\r\\n fn_val1 = made.fn()\\r\\n\\r\\n rng_seed = numpy.random.RandomState(utt.fetch_seed()).randint(2**30)\\r\\n rng = numpy.random.RandomState(int(rng_seed)) #int() is for 32bit\\r\\n numpy_val0 = rng.random_integers(-5, 5, size=(20,20))\\r\\n numpy_val1 = rng.random_integers(-5, 5, size=(20,20))\\r\\n\\r\\n assert numpy.all(fn_val0 == numpy_val0)\\r\\n assert numpy.all(fn_val1 == numpy_val1)\",\n \"def genNumID(size):\\n\\tid = \\\"\\\"\\n\\tfor i in range(size):\\n\\t\\tid = id + selectRandomFromList(numTokens)\\n\\treturn id\",\n \"def generate_subsegment_id():\\n return uuid.uuid4().hex[:16]\",\n \"def generate_run_id(self):\\n r_id_len = 4\\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\\n while r_id in self.cache:\\n r_id = 'r'+''.join([str(random.randint(0,9)) for i in range(r_id_len)])\\n return r_id\",\n \"def test_generateuuids(self):\\n ret1 = {\\\"message\\\": \\\"No Random.org api key or api version found.\\\", \\\"res\\\": False}\\n self.assertDictEqual(random_org.generateUUIDs(), ret1)\\n\\n ret2 = {\\\"message\\\": \\\"Required argument, number is missing.\\\", \\\"res\\\": False}\\n self.assertDictEqual(\\n random_org.generateUUIDs(api_key=\\\"peW\\\", api_version=\\\"1\\\"), ret2\\n )\\n\\n ret3 = {\\\"message\\\": \\\"Number of UUIDs must be between 1 and 1000\\\", \\\"res\\\": False}\\n self.assertDictEqual(\\n random_org.generateUUIDs(api_key=\\\"peW\\\", api_version=\\\"1\\\", number=\\\"5\\\"), ret3\\n )\\n\\n ret3 = {\\\"message\\\": \\\"Parameter 'apiKey' is malformed\\\", \\\"res\\\": False}\\n self.assertDictEqual(\\n random_org.generateUUIDs(api_key=\\\"peW\\\", api_version=\\\"1\\\", number=5), ret3\\n )\",\n \"def test_spin_loop_wildcard(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N*'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_generate_factoid():\\n generator = mockdata.generate_factoid()\\n for i in range(100):\\n factoid = next(generator)\\n assert factoid[\\\"@id\\\"] == \\\"Factoid %03d\\\" % (i + 1)\\n assert \\\"Person\\\" in factoid[\\\"person\\\"][\\\"@id\\\"]\\n assert \\\"Source\\\" in factoid[\\\"source\\\"][\\\"@id\\\"]\\n assert \\\"statement\\\" in factoid\\n assert factoid[\\\"statement\\\"][\\\"@id\\\"] == \\\"F%dS1\\\" % (i + 1)\",\n \"def spinWheel():\\n\\tt = random.randrange(8)\\n\\tif t == 7:\\n\\t\\treturn \\\"00\\\"\\n\\treturn str(t)\",\n \"def test_apply_ridit(self):\\n x, x_rand, s = self.create_testdata()\\n task = mmRDTR()\\n s = task.check_sparse(s)\\n\\n for data in [x, x_rand, s]:\\n #get ecdf for data\\n Fn=task.make_ECDF(data)\\n out=task.apply_ridit( data, Fn )\\n # check same dimension\\n self.assertEqual(np.all(data.shape==out.shape),True)\\n # check mean almost equal to 0\\n for i in range(data.shape[1]):\\n self.assertEqual(round(out[:,i].mean(),8),0)\\n # check if works with newdata\\n newdata=data[:2]\\n out=task.apply_ridit( newdata, Fn )\\n # check same dimension\\n self.assertEqual(np.all(newdata.shape==out.shape),True)\",\n \"def genSCID():\\n scid_hex = getRandomBytes(8)\\n scid_hex = getSHA256Hex(scid_hex)\\n scid_hex = scid_hex[0:8]\\n return scid_hex\",\n \"def _apply_array_spin123(self,\\n h1e: 'Nparray',\\n h2e: 'Nparray',\\n h3e: 'Nparray',\\n dvec: Optional[Tuple['Nparray', 'Nparray']] = None,\\n evec: Optional[Tuple['Nparray', 'Nparray', 'Nparray', 'Nparray']] \\\\\\n = None) -> 'Nparray':\\n norb = self.norb()\\n assert h3e.shape == (norb * 2,) * 6\\n assert not (dvec is None) ^ (evec is None)\\n\\n from1234 = (dvec is not None) and (evec is not None)\\n\\n nh1e = numpy.copy(h1e)\\n nh2e = numpy.copy(h2e)\\n\\n for i in range(norb * 2):\\n for j in range(norb * 2):\\n for k in range(norb * 2):\\n nh2e[j, k, :, :] += (-h3e[k, j, i, i, :, :] -\\n h3e[j, i, k, i, :, :] -\\n h3e[j, k, i, :, i, :])\\n\\n nh1e[:, :] += h3e[:, i, j, i, j, :]\\n\\n out = self._apply_array_spin12_halffilling(nh1e, nh2e)\\n\\n n = norb # This is just shorter\\n if not from1234:\\n symfac = 2.0\\n axes = ((1, 3), (0, 1))\\n (odveca, odvecb) = self.calculate_dvec_spin()\\n dveca = numpy.zeros_like(odveca)\\n dvecb = numpy.zeros_like(odvecb)\\n\\n for i in range(norb):\\n for j in range(norb):\\n evecaa, _ = self._calculate_dvec_spin_with_coeff(\\n odveca[i, j, :, :])\\n evecab, evecbb = self._calculate_dvec_spin_with_coeff(\\n odvecb[i, j, :, :])\\n\\n dveca += numpy.tensordot(h3e[:n, :n, i, :n, :n, j],\\n evecaa,\\n axes=axes)\\n dveca += numpy.tensordot(h3e[:n, :n, n + i, :n, :n, n + j],\\n evecab,\\n axes=axes) * symfac\\n dveca += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\\n evecbb,\\n axes=axes)\\n\\n dvecb += numpy.tensordot(h3e[n:, :n, i, n:, :n, j],\\n evecaa,\\n axes=axes)\\n dvecb += numpy.tensordot(h3e[n:, :n, n + i, n:, :n, n + j],\\n evecab,\\n axes=axes) * symfac\\n dvecb += numpy.tensordot(h3e[:n, n:, n + i, :n, n:, n + j],\\n evecbb,\\n axes=axes)\\n else:\\n symfac = 1.0\\n axes = ((1, 4, 2, 5), (0, 1, 2, 3)) # type: ignore\\n dveca, dvecb = dvec # type: ignore\\n evecaa, evecab, evecba, evecbb = evec # type: ignore\\n\\n dveca = numpy.tensordot(h3e[:n, :n, :n, :n, :n, :n],\\n evecaa, axes=axes) \\\\\\n + numpy.tensordot(h3e[:n, :n, n:, :n, :n, n:],\\n evecab, axes=axes) * symfac \\\\\\n + numpy.tensordot(h3e[:n, n:, n:, :n, n:, n:],\\n evecbb, axes=axes) + \\\\\\n + numpy.tensordot(h3e[:n, n:, :n, :n, n:, :n],\\n evecba, axes=axes)\\n\\n dvecb = numpy.tensordot(h3e[n:, :n, :n, n:, :n, :n],\\n evecaa, axes=axes) \\\\\\n + numpy.tensordot(h3e[n:, :n, n:, n:, :n, n:],\\n evecab, axes=axes) * symfac \\\\\\n + numpy.tensordot(h3e[n:, n:, n:, n:, n:, n:],\\n evecbb, axes=axes) + \\\\\\n + numpy.tensordot(h3e[n:, n:, :n, n:, n:, :n],\\n evecba, axes=axes)\\n\\n out -= self._calculate_coeff_spin_with_dvec((dveca, dvecb))\\n return out\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_arbitrary_rotation(self):\\n \\n # This test is run a bunch of times on various intervals, ranging from 50% to 1/6\\n\\t\\t# (16.667%).\\n for i in range(2, 7):\\n \\n interval = 1 / i # The amount to increase each qubit's probability by, relative to the previous qubit\\n step_string = \\\"{:.4f}\\\".format(100 / i) # The decimal representation of the interval, as a percent\\n target_probabilities = [0] * (i + 1) # This will store the desired probabilities of each qubit\\n for j in range(0, i + 1):\\n target_probability = j * interval\\n target_probabilities[j] = target_probability\\n\\n # Run the test\\n self.run_test(self.arbitrary_rotation_function, f\\\"Rotation with steps of 1/{i} ({step_string}%)\\\", 2000, target_probabilities, 0.05)\",\n \"def _generate_id() -> str:\\n return \\\"\\\".join(sample(\\\"abcdefghjkmopqrstuvqxyz\\\", 16))\",\n \"def test_api_random_id(api_client, single_brew_number):\\n response = api_client.get(path='/breweries' + '/' + str(single_brew_number))\\n assert response.json()['id'] == single_brew_number\",\n \"def test_WINNF_FT_S_REG_17(self):\\n\\n # Register device\\n device_a = json.load(\\n open(os.path.join('testcases', 'testdata', 'device_a.json')))\\n self._sas_admin.InjectFccId({'fccId': device_a['fccId']})\\n # Register the device\\n request = {'registrationRequest': [device_a]}\\n response = self._sas.Registration(request)['registrationResponse'][0]\\n # Check registration response\\n self.assertTrue('cbsdId' in response)\\n self.assertEqual(response['response']['responseCode'], 0)\\n cbsd_id = response['cbsdId']\\n del request, response\\n\\n # Blacklist the device\\n self._sas_admin.BlacklistByFccId({'fccId':device_a['fccId']})\\n\\n # Re-register the device\\n request = {'registrationRequest': [device_a]}\\n response = self._sas.Registration(request)['registrationResponse'][0]\\n\\n # Check registration response\\n self.assertFalse('cbsdId' in response)\\n self.assertEqual(response['response']['responseCode'], 101)\",\n \"def get_refresh_ids(self):\\n ids = []\\n for bucket in self.router.lonely_buckets():\\n rid = random.randint(*bucket.range).to_bytes(20, byteorder='big')\\n ids.append(rid)\\n return ids\",\n \"def test_spin_type(get_pdos_generator_inputs):\\n with pytest.raises(NotImplementedError):\\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=spin_type)\\n builder = PdosWorkChain.get_builder_from_protocol(**get_pdos_generator_inputs, spin_type=SpinType.COLLINEAR)\\n for namespace in [builder.scf, builder.nscf]:\\n parameters = namespace['pw']['parameters'].get_dict()\\n assert parameters['SYSTEM']['nspin'] == 2\\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}\",\n \"def cifar_iid(dataset, num_users):\\n print(\\\"Sampling dataset: CIFAR-10 IID\\\")\\n num_items = int(len(dataset)/num_users)\\n dict_users, all_idxs = {}, [i for i in range(len(dataset))]\\n for i in range(num_users):\\n dict_users[i] = set(np.random.choice(all_idxs, num_items, replace=False))\\n all_idxs = list(set(all_idxs) - dict_users[i])\\n return dict_users\",\n \"def test_start_ids_10(self):\\n\\n\\t\\texpected_num_layers = 11\\n\\t\\texpected_ids = np.arange(10,21)\\n\\t\\t# test describe\\n\\t\\tdetails = self.watcher.describe(start_ids=10)\\n\\t\\tprint(\\\"start id = 10\\\", details)\\n\\t\\tactual_ids = details.layer_id.to_numpy().tolist()\\n\\t\\tself.assertTrue(np.array_equal(actual_ids, expected_ids))\\n\\t\\tself.assertEqual(len(expected_ids), expected_num_layers)\\n\\t\\t\\t\\t\\n\\t\\treturn\",\n \"def _get_rand_array(self):\\n pass\",\n \"def iv_gen():\\r\\n rndiv = os.urandom(16)\\r\\n return rndiv\",\n \"def create_code():\\n\\n code = [0, 0, 0, 0]\\n\\n for i in range(4):\\n value = random.randint(1, 8) # 8 possible digits\\n while value in code:\\n value = random.randint(1, 8) # 8 possible digits\\n code[i] = value\\n \\n #print(code)\\n return code\",\n \"def test_generation_index_zero(self):\\n generator = math_helpers.triangle_number_generator()\\n first_eleven_triangle_numbers = [next(generator) for _ in range(11)]\\n canonical_values = [0, 1, 3, 6, 10, 15, 21, 28, 36, 45, 55]\\n self.assertEqual(canonical_values, first_eleven_triangle_numbers)\",\n \"def test_scan_id_gt(self):\\n scan = '>16'\\n ref_idx = [3]\\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_scan_id_lt(self):\\n scan = '<16'\\n ref_idx = [0]\\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_stickers(self):\\n rotation, _ = list(self.cube.scramble_cube(15))\\n\\n unique, counts = np.unique(rotation, return_counts=True)\\n dictionary = dict(zip(unique, counts))\\n\\n self.assertEqual(all(value == 4 for value in dictionary.values()), True)\",\n \"def test_scan_id_exprlist(self):\\n scan = '15,>16'\\n ref_idx = [0,3]\\n self.res=self.run_task(infile=self.rawfile,scan=scan,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_brains_id_get(self):\\n pass\",\n \"def test_spin_loop_multiatom(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_run_a_scan_on_sdp_subarray_in_low():\",\n \"def get_test_split(self, fraction=0.1):\\n rng = np.random.default_rng(42)\\n test_size = int(round(len(self.all_asset_ids) * fraction))\\n test_ids = rng.choice(self.all_asset_ids, size=test_size, replace=False)\\n train_ids = [i for i in self.all_asset_ids if i not in test_ids]\\n return train_ids, test_ids\",\n \"def test_run_a_scan_on_sdp_subarray_in_mid():\",\n \"def test_residue_loop(self):\\n\\n # Loop over the residues.\\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\\n # Test the selection.\\n self.assertEqual(res.num, 2)\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)\",\n \"def test_returned_num_in_random_nums(self):\\n self._setup_random_gen([1.], [42])\\n self.assertEqual(self._random_gen.next_num(), 42)\",\n \"def test_arr2vtkIdList(self):\\n a = [1, 2, 3, 4, 5]\\n p = array_handler.array2vtkIdList(a)\\n for i, j in enumerate(a): \\n self.assertEqual(p.GetId(i), j)\\n p = vtk.vtkIdList()\\n ident = id(p)\\n p = array_handler.array2vtkIdList(numpy.array(a), p)\\n for i, j in enumerate(a): \\n self.assertEqual(p.GetId(i), j)\\n self.assertEqual(id(p), ident)\\n \\n self.assertRaises(AssertionError, array_handler.array2vtkIdList,\\n [[1,2,3]])\",\n \"def test_get_new_otu_id_large(self):\\r\\n tree = DndParser(\\\"(A:0.1,B:0.2,(C:0.3,D:0.4):0.5);\\\")\\r\\n results = []\\r\\n for i in range(1000):\\r\\n results.append(qiime.simsam.get_new_otu_id(old_otu_id='D',\\r\\n tree=tree, dissim=.6))\\r\\n self.assertTrue('C' in results)\\r\\n self.assertTrue('D' in results)\\r\\n self.assertTrue('A' not in results)\\r\\n self.assertTrue('B' not in results)\",\n \"def test_ids(self):\\n # AdapterID inherited from IOAdapter\\n self.assertEqual('553713696', self.sriovs[0].id)\\n self.assertEqual(1, self.sriovs[0].sriov_adap_id)\\n\\n self.assertEqual('553713680', self.sriovs[2].id)\\n self.assertIsNone(self.sriovs[2].sriov_adap_id)\",\n \"def gen_data(min_coord, max_coord, size):\\r\\n data = np.random.randint(min_coord, max_coord, size)\\r\\n return data\",\n \"def data_gen(size, p):\\n #print(np.random.get_state()[1][0])\\n random_table = np.random.binomial(size = size, p = p, n = 1)\\n test_array = np.zeros((size, 2), dtype = int)\\n for i in range(size):\\n test_array[i,0] = i\\n test_array[i,1] = random_table[i]\\n return test_array\",\n \"def test1():\\n for test in pkl.load(open(TEST_RESOURCES_DIR / \\\"regression_vault.pkl\\\", \\\"rb\\\"))[:5]:\\n init_dict, rslt = test\\n np.testing.assert_array_equal(run_regression_test(init_dict), rslt)\",\n \"def generateRegistrationId():\\n regId = KeyHelper.getRandomSequence()\\n return regId\",\n \"def test_id_get(mocker):\\n mocker.patch('serial.Serial.open')\\n mocker.patch('serial.Serial.flushInput')\\n css = mocker.patch('pysds011.driver.SDS011.cmd_set_sleep')\\n css.return_value = True\\n cfv = mocker.patch('pysds011.driver.SDS011.cmd_firmware_ver')\\n cfv.return_value = {'id': b'\\\\x12\\\\x34', 'paperino': 'maciomicio'}\\n runner = CliRunner()\\n result = runner.invoke(main, ['id'])\\n\\n calls = [call(0, id=b'\\\\xff\\\\xff'), call(1, id=b'\\\\xff\\\\xff')]\\n css.assert_has_calls(calls, any_order=False)\\n\\n assert '12' in result.output and '34' in result.output\\n assert result.exit_code == 0\",\n \"def test_generation_index_one(self):\\n generator = math_helpers.triangle_number_generator(1)\\n first_ten_triangle_numbers = [next(generator) for _ in range(10)]\\n canonical_values = [1, 3, 6, 10, 15, 21, 28, 36, 45, 55]\\n self.assertEqual(canonical_values, first_ten_triangle_numbers)\",\n \"def test_pol_id_list(self):\\n pol = '0,1'\\n ref_idx = []\\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_random_generator(self):\\n gen = random_data()\\n data = [next(gen) for _ in range(100)]\\n self.assertEqual(len(data), 100)\",\n \"def test_rand_func2(self):\\n for i in range(0, 100000):\\n num = random.randint(0, 32535143990)\\n func2_comp(num)\",\n \"def test_get_tid():\\n tids = []\\n def _foo():\\n mytid = yield GetTid()\\n tids.append(mytid)\\n for i in range(5):\\n yield i\\n\\n scheduler = Scheduler()\\n scheduler.new(_foo())\\n scheduler.new(_foo())\\n scheduler.mainloop()\\n\\n # can we do better than hard code?\\n assert tids == [4, 5]\",\n \"def test_generation(self):\\n generator = math_helpers.hexagonal_number_generator()\\n first_ten_hex_numbers = [next(generator) for _ in range(10)]\\n canonical_values = [1, 6, 15, 28, 45, 66, 91, 120, 153, 190]\\n self.assertEqual(canonical_values, first_ten_hex_numbers)\",\n \"def test_generate_mine_sequence(self):\\n mine_list = utils.generate_mine_sequence(1)\\n self.assertEqual(len(mine_list), utils.MINE_COUNT)\",\n \"def test_spin_type(fixture_code, generate_structure):\\n code = fixture_code('quantumespresso.pw')\\n structure = generate_structure()\\n\\n with pytest.raises(NotImplementedError):\\n for spin_type in [SpinType.NON_COLLINEAR, SpinType.SPIN_ORBIT]:\\n PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=spin_type)\\n\\n builder = PwBandsWorkChain.get_builder_from_protocol(code, structure, spin_type=SpinType.COLLINEAR)\\n\\n for namespace in [builder.relax['base'], builder.scf, builder.bands]:\\n parameters = namespace['pw']['parameters'].get_dict()\\n assert parameters['SYSTEM']['nspin'] == 2\\n assert parameters['SYSTEM']['starting_magnetization'] == {'Si': 0.1}\",\n \"def generate_mixture_indicator(number_obeservations):\\n mixture_indicator = np.random.randint(0, 2, (number_obeservations,1))\\n return mixture_indicator\",\n \"def random_lottery():\\n\\treturn 0\",\n \"def test_main(data, tmp_path):\\n\\n main(data, tmp_path)\\n\\n FILES = (\\n \\\"gd32f888x(0-1)xx-pinctrl.h\\\",\\n \\\"gd32f888x(2-3)xx-pinctrl.h\\\",\\n \\\"gd32f888y(0-1)xx-pinctrl.h\\\",\\n \\\"gd32f999x(0-1)xx-pinctrl.h\\\",\\n \\\"gd32f999x(2-3)xx-pinctrl.h\\\",\\n \\\"gd32f999y(0-1)xx-pinctrl.h\\\",\\n )\\n\\n for file in FILES:\\n ref_file = data / file\\n gen_file = tmp_path / file\\n\\n assert gen_file.exists()\\n\\n with open(ref_file) as ref, open(gen_file) as gen:\\n assert ref.read() == gen.read()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.784438","0.7714932","0.7577586","0.757559","0.7561462","0.6163308","0.5690773","0.56745136","0.56711537","0.5610869","0.56024593","0.5324083","0.527502","0.5271551","0.5269606","0.52232736","0.52200073","0.5196732","0.5193356","0.5152407","0.5141934","0.5140214","0.5136551","0.5094677","0.50934577","0.50934577","0.5092785","0.5089717","0.507889","0.5056581","0.50549257","0.5052593","0.5033704","0.5031883","0.5031547","0.50310254","0.502694","0.50098413","0.5006745","0.4991137","0.49900505","0.49846685","0.49810216","0.49761346","0.4971696","0.49526995","0.4931449","0.4928985","0.492406","0.49143815","0.4907066","0.49067634","0.49036613","0.4894906","0.48922542","0.48867777","0.48768303","0.48751643","0.48712257","0.48706675","0.4870333","0.48702115","0.48657534","0.4865439","0.48616904","0.48606256","0.48595908","0.4857318","0.48553398","0.48368663","0.48209593","0.48207068","0.48204175","0.48156765","0.48081642","0.48028138","0.4799075","0.47976008","0.47962347","0.47932363","0.47918278","0.47874272","0.4784194","0.47806886","0.47767565","0.47763178","0.47746474","0.47719654","0.47714636","0.47701824","0.47688967","0.47683558","0.4766466","0.4763582","0.47515628","0.4750009","0.47460416","0.4745053","0.47385716","0.47345847"],"string":"[\n \"0.784438\",\n \"0.7714932\",\n \"0.7577586\",\n \"0.757559\",\n \"0.7561462\",\n \"0.6163308\",\n \"0.5690773\",\n \"0.56745136\",\n \"0.56711537\",\n \"0.5610869\",\n \"0.56024593\",\n \"0.5324083\",\n \"0.527502\",\n \"0.5271551\",\n \"0.5269606\",\n \"0.52232736\",\n \"0.52200073\",\n \"0.5196732\",\n \"0.5193356\",\n \"0.5152407\",\n \"0.5141934\",\n \"0.5140214\",\n \"0.5136551\",\n \"0.5094677\",\n \"0.50934577\",\n \"0.50934577\",\n \"0.5092785\",\n \"0.5089717\",\n \"0.507889\",\n \"0.5056581\",\n \"0.50549257\",\n \"0.5052593\",\n \"0.5033704\",\n \"0.5031883\",\n \"0.5031547\",\n \"0.50310254\",\n \"0.502694\",\n \"0.50098413\",\n \"0.5006745\",\n \"0.4991137\",\n \"0.49900505\",\n \"0.49846685\",\n \"0.49810216\",\n \"0.49761346\",\n \"0.4971696\",\n \"0.49526995\",\n \"0.4931449\",\n \"0.4928985\",\n \"0.492406\",\n \"0.49143815\",\n \"0.4907066\",\n \"0.49067634\",\n \"0.49036613\",\n \"0.4894906\",\n \"0.48922542\",\n \"0.48867777\",\n \"0.48768303\",\n \"0.48751643\",\n \"0.48712257\",\n \"0.48706675\",\n \"0.4870333\",\n \"0.48702115\",\n \"0.48657534\",\n \"0.4865439\",\n \"0.48616904\",\n \"0.48606256\",\n \"0.48595908\",\n \"0.4857318\",\n \"0.48553398\",\n \"0.48368663\",\n \"0.48209593\",\n \"0.48207068\",\n \"0.48204175\",\n \"0.48156765\",\n \"0.48081642\",\n \"0.48028138\",\n \"0.4799075\",\n \"0.47976008\",\n \"0.47962347\",\n \"0.47932363\",\n \"0.47918278\",\n \"0.47874272\",\n \"0.4784194\",\n \"0.47806886\",\n \"0.47767565\",\n \"0.47763178\",\n \"0.47746474\",\n \"0.47719654\",\n \"0.47714636\",\n \"0.47701824\",\n \"0.47688967\",\n \"0.47683558\",\n \"0.4766466\",\n \"0.4763582\",\n \"0.47515628\",\n \"0.4750009\",\n \"0.47460416\",\n \"0.4745053\",\n \"0.47385716\",\n \"0.47345847\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8226237"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81489,"cells":{"query":{"kind":"string","value":"Test the proper operation of the molecule loop with molecule selection. The function tested is pipe_control.mol_res_spin.molecule_loop()."},"document":{"kind":"string","value":"def test_molecule_loop(self):\n\n # Loop over the molecules.\n for mol in mol_res_spin.molecule_loop('#RNA'):\n # Test the molecule name.\n self.assertEqual(mol.name, 'RNA')\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_molecule_loop_no_selection(self):\n\n # Molecule data.\n name = ['Ap4Aase', 'RNA']\n\n # Loop over the molecules.\n i = 0\n for mol in mol_res_spin.molecule_loop():\n # Test the molecule names.\n self.assertEqual(mol.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)","def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_spin_loop(self):\n\n # Spin data.\n select = [1, 0]\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, 'N5')\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 2)","def test_molecule_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for molecule in mol_res_spin.molecule_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_spin_loop_multiatom(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_spin_loop_no_selection(self):\n\n # Spin data.\n select = [0, 1, 0, 0, 1, 1, 0, 1]\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 8)","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def test_residue_loop(self):\n\n # Loop over the residues.\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\n # Test the selection.\n self.assertEqual(res.num, 2)\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)","def test_spin_loop_wildcard(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N*'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_multi_molecules_cycle(self, multi_mol_system_regular, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n expected = expected * 3\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_regular)\n found = self.sequence_from_system(multi_mol_system_regular, \"test\")\n assert found == expected","def test_multi_molecules_cycle_one(self, multi_mol_system_irregular):\n sequence = \"A\"\n expected = [sequence] * (15 * 3)\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_irregular)\n found = self.sequence_from_system(multi_mol_system_irregular, \"test\")\n assert found == expected","def test_return_molecule(self):\n\n # Ask for a few molecules.\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\n\n # Test the data of molecule 1.\n self.assertEqual(mol1.name, 'Ap4Aase')\n\n # Test the data of molecule 2.\n self.assertEqual(mol2.name, 'RNA')","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_run_molecule(self, single_mol_system):\n sequence = \"ABCDE\"\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_run_molecule_not_selected(self, single_mol_system):\n sequence = \"ABCDE\"\n processor = dssp.AnnotateResidues(\n \"test\", sequence, molecule_selector=lambda mol: False\n )\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert vermouth.utils.are_all_equal(found)\n assert found[0] is None","def test_residue_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for residue in mol_res_spin.residue_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_single_molecules_cycle_one(self, single_mol_system):\n sequence = \"A\"\n expected = [sequence] * (5 * 3)\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def test_spin_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for spin in mol_res_spin.spin_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_run_loop_success(self):\n found = False\n pyint = Interpreter(limit=15)\n try:\n pyint.run(code=BF_CODE_LOOP_TWICE)\n except SystemExit: \n found = True\n self.assertFalse(found)","def test_single_molecule(self, single_mol_system, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def run_test(dut):\n tb = MyTB(dut,int(os.environ['SIM_LEN']))\n cocotb.fork(Clock(dut.clk, 10).start())\n stim_thread = cocotb.fork(tb.stim_mux())\n read_thread = cocotb.fork(tb.read_mux())\n yield stim_thread.join()\n yield read_thread.join()\n if tb.sim_mux_sel != tb.py_sel_input:\n raise TestFailure(\"Mux selection failed.\")\n else:\n raise TestSuccess(\"Mux sel successful\")","def test_return_molecule_pipe_fail(self):\n\n # Try to get a molecule from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')","def test_simulationRun(self):\n self.opt = { 'temperature' : 300.0, 'friction' : 1, 'dt' : 0.00002,\n 'nIter' : 2, 'nstepsNC' : 2, 'nstepsMD' : 1, 'nprop' : 1,\n 'nonbondedMethod' : 'NoCutoff', 'constraints': 'HBonds',\n 'trajectory_interval' : 1, 'reporter_interval' : 1,\n 'outfname' : 'mc-test',\n 'platform' : None,\n 'constraints' : 'HBonds',\n 'mc_per_iter' : 2 }\n\n structure = self.full_struct\n class SetRotationMove(RandomLigandRotationMove):\n def __init__(self, structure, resname='LIG'):\n super(SetRotationMove, self).__init__(structure, resname)\n\n def move(self, context):\n \"\"\"Function that performs a random rotation about the\n center of mass of the ligand.\n \"\"\"\n #TODO: check if we need to deepcopy\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\n\n self.positions = positions[self.atom_indices]\n self.center_of_mass = self.getCenterOfMass(self.positions, self.masses)\n reduced_pos = self.positions - self.center_of_mass\n\n # Define random rotational move on the ligand\n #set rotation so that test is reproducible\n set_rotation_matrix = np.array([[-0.62297988, -0.17349253, 0.7627558 ],\n [ 0.55082352, -0.78964857, 0.27027502],\n [ 0.55541834, 0.58851973, 0.58749893]])\n\n\n #set_rotation_matrix = np.array([[1, 0, 0],\n # [0, 1, 0],\n # [0, 0, 1]])\n\n #multiply lig coordinates by rot matrix and add back COM translation from origin\n rot_move = np.dot(reduced_pos, set_rotation_matrix) * positions.unit + self.center_of_mass\n\n # Update ligand positions in nc_sim\n for index, atomidx in enumerate(self.atom_indices):\n positions[atomidx] = rot_move[index]\n context.setPositions(positions)\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\n self.positions = positions[self.atom_indices]\n return context\n\n\n self.model = SetRotationMove(structure, resname='ALA')\n #self.model = RandomLigandRotationMove(structure, resname='ALA')\n\n self.model.atom_indices = range(22)\n self.model.topology = structure[self.model.atom_indices].topology\n self.model.positions = structure[self.model.atom_indices].positions\n self.model.calculateProperties()\n\n self.mover = MoveEngine(self.model)\n #Initialize the SimulationFactory object\n sims = SimulationFactory(structure, self.mover, **self.opt)\n #print(sims)\n system = sims.generateSystem(structure, **self.opt)\n simdict = sims.createSimulationSet()\n alch_system = sims.generateAlchSystem(system, self.model.atom_indices)\n self.nc_sim = sims.generateSimFromStruct(structure, self.mover, alch_system, ncmc=True, **self.opt)\n self.model.calculateProperties()\n self.initial_positions = self.nc_sim.context.getState(getPositions=True).getPositions(asNumpy=True)\n mc_sim = Simulation(sims, self.mover, **self.opt)\n #monkeypatch to access acceptance value\n def nacceptRejectMC(self, temperature=300, **opt):\n \"\"\"Function that chooses to accept or reject the proposed move.\n \"\"\"\n md_state0 = self.current_state['md']['state0']\n md_state1 = self.current_state['md']['state1']\n log_mc = (md_state1['potential_energy'] - md_state0['potential_energy']) * (-1.0/self.nc_sim.context._integrator.kT)\n randnum = math.log(np.random.random())\n\n if log_mc > randnum:\n self.accept += 1\n print('MC MOVE ACCEPTED: log_mc {} > randnum {}'.format(log_mc, randnum) )\n self.md_sim.context.setPositions(md_state1['positions'])\n else:\n self.reject += 1\n print('MC MOVE REJECTED: log_mc {} < {}'.format(log_mc, randnum) )\n self.md_sim.context.setPositions(md_state0['positions'])\n self.log_mc = log_mc\n self.md_sim.context.setVelocitiesToTemperature(self.opt['temperature'])\n mc_sim.acceptRejectMC = nacceptRejectMC\n nacceptRejectMC.__get__(mc_sim)\n mc_sim.acceptRejectMC = types.MethodType(nacceptRejectMC, mc_sim)\n mc_sim.runMC(self.opt['nIter'])\n #get log acceptance\n print(mc_sim.log_mc)\n #if mc is working, should be around -24.1\n assert mc_sim.log_mc <= -23.8 and mc_sim.log_mc >= -24.3","def test_for_loop(self, modes, parse_input_mocked_metadata):\n bb = parse_input_mocked_metadata(\n \"for int m in {}\\n\\tMeasureFock() | m\".format(modes)\n )\n assert np.all(\n bb._forvar[\"m\"] == np.array(modes)\n )\n assert bb.operations == [\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[0]]},\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[1]]},\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[2]]}\n ]","def test_select_pdb_conformation(self):\n with mmtools.utils.temporary_directory() as tmp_dir:\n yaml_content = \"\"\"\n ---\n options:\n output_dir: {}\n setup_dir: .\n molecules:\n selected:\n filepath: {}\n leap: {{parameters: oldff/leaprc.ff14SB}}\n select: 1\n \"\"\".format(tmp_dir, self.pdb_path)\n yaml_content = textwrap.dedent(yaml_content)\n exp_builder = ExperimentBuilder(yaml_content)\n\n # The molecule now is neither set up nor processed\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\n assert is_setup is False\n assert is_processed is False\n\n # The setup of the molecule must isolate the frame in a single-frame PDB\n exp_builder._db._setup_molecules('selected')\n selected_pdb_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\n 'selected', 'selected.pdb')\n assert os.path.exists(os.path.join(selected_pdb_path))\n assert os.path.getsize(os.path.join(selected_pdb_path)) > 0\n\n # The positions must be the ones of the second frame\n selected_pdb = PDBFile(selected_pdb_path)\n selected_pos = selected_pdb.getPositions(asNumpy=True)\n second_pos = PDBFile(self.pdb_path).getPositions(asNumpy=True, frame=1)\n assert selected_pdb.getNumFrames() == 1\n assert (selected_pos == second_pos).all()\n\n # The description of the molecule is now updated\n assert os.path.normpath(exp_builder._db.molecules['selected']['filepath']) == selected_pdb_path\n\n # The molecule now both set up and processed\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\n assert is_setup is True\n assert is_processed is True\n\n # A new instance of ExperimentBuilder is able to resume with correct molecule\n exp_builder = ExperimentBuilder(yaml_content)\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\n assert is_setup is True\n assert is_processed is True","def test_boolean_and_selection(self):\n\n # The selection loop:\n sel = list(mol_res_spin.residue_loop(\"#Ap4Aase:4 & :Pro\"))\n\n # Test:\n self.assertEqual(len(sel), 1)\n for res in sel:\n self.assert_(res.name == \"Pro\" and res.num == 4)","def ROOMSELECTION_LOOP():\n pass","def loop(self):\n raise NotImplementedError()","def MULTIPLAYER_LOOP():\n pass","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_boolean_complex_selection(self):\n\n # The residue selection loop.\n sel = list(mol_res_spin.residue_loop(\"#Ap4Aase:4 & :Pro | #RNA\"))\n\n # Residue names and numbers.\n names = ['Pro', None, None]\n numbers = [4, -5, -4]\n\n # The residues.\n self.assertEqual(len(sel), 3)\n for i in range(3):\n self.assertEqual(sel[i].name, names[i])\n self.assertEqual(sel[i].num, numbers[i])","def test_control_loop_example():\n example.control.print_error_measurement()\n matplotlib.use('agg')\n example.control.visualise_error_measurement(fig_file='cs_compare.pdf')\n assert path.isfile('cs_compare.pdf')\n example.control.sil_comparison()","def loop(self):\n pass","def test_set_molecule(self):\n mol = Molecule.from_smiles(\"CCO\")\n atom = Atom(6, 0, False)\n atom.molecule = mol","def test_select_sdf_mol2(self):\n with mmtools.utils.temporary_directory() as tmp_dir:\n yaml_content = \"\"\"\n ---\n options:\n output_dir: {}\n setup_dir: .\n molecules:\n sdf_0:\n filepath: {}\n antechamber: {{charge_method: bcc}}\n leap: {{parameters: leaprc.gaff}}\n select: 0\n sdf_1:\n filepath: {}\n antechamber: {{charge_method: bcc}}\n leap: {{parameters: leaprc.gaff}}\n select: 1\n mol2_0:\n filepath: {}\n antechamber: {{charge_method: bcc}}\n leap: {{parameters: leaprc.gaff}}\n select: 0\n mol2_1:\n filepath: {}\n antechamber: {{charge_method: bcc}}\n leap: {{parameters: leaprc.gaff}}\n select: 1\n \"\"\".format(tmp_dir, self.sdf_path, self.sdf_path, self.mol2_path, self.mol2_path)\n yaml_content = textwrap.dedent(yaml_content)\n exp_builder = ExperimentBuilder(yaml_content)\n\n for extension in ['sdf', 'mol2']:\n multi_path = getattr(self, extension + '_path')\n for model_idx in [0, 1]:\n mol_id = extension + '_' + str(model_idx)\n\n # The molecule now is neither set up nor processed\n is_setup, is_processed = exp_builder._db.is_molecule_setup(mol_id)\n assert is_setup is False\n assert is_processed is False\n\n exp_builder._db._setup_molecules(mol_id)\n\n # The setup of the molecule must isolate the frame in a single-frame PDB\n single_mol_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\n mol_id, mol_id + '.' + extension)\n assert os.path.exists(os.path.join(single_mol_path))\n assert os.path.getsize(os.path.join(single_mol_path)) > 0\n if extension == 'mol2':\n # OpenEye loses the resname when writing a mol2 file.\n mol2_file = utils.Mol2File(single_mol_path)\n assert len(list(mol2_file.resnames)) == 1\n assert mol2_file.resname != '<0>'\n\n # sdf files must be converted to mol2 to be fed to antechamber\n if extension == 'sdf':\n single_mol_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\n mol_id, mol_id + '.mol2')\n assert os.path.exists(os.path.join(single_mol_path))\n assert os.path.getsize(os.path.join(single_mol_path)) > 0\n\n # Check antechamber parametrization\n single_mol_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\n mol_id, mol_id + '.gaff.mol2')\n assert os.path.exists(os.path.join(single_mol_path))\n assert os.path.getsize(os.path.join(single_mol_path)) > 0\n\n # The positions must be approximately correct (antechamber move the molecule)\n selected_oe_mol = utils.load_oe_molecules(single_mol_path, molecule_idx=0)\n selected_pos = utils.get_oe_mol_positions(selected_oe_mol)\n second_oe_mol = utils.load_oe_molecules(multi_path, molecule_idx=model_idx)\n second_pos = utils.get_oe_mol_positions(second_oe_mol)\n assert selected_oe_mol.NumConfs() == 1\n assert np.allclose(selected_pos, second_pos, atol=1e-1)\n\n # The molecule now both set up and processed\n is_setup, is_processed = exp_builder._db.is_molecule_setup(mol_id)\n assert is_setup is True\n assert is_processed is True\n\n # A new instance of ExperimentBuilder is able to resume with correct molecule\n exp_builder = ExperimentBuilder(yaml_content)\n is_setup, is_processed = exp_builder._db.is_molecule_setup(mol_id)\n assert is_setup is True\n assert is_processed is True","def test_compute_partial_charges(self):\n # TODO: Test only one molecule for speed?\n # TODO: Do we need to deepcopy each molecule, or is setUp called separately for each test method?\n import numpy as np\n from simtk import unit\n\n # Do not modify original molecules.\n molecules = copy.deepcopy(mini_drug_bank())\n\n # Test a single toolkit at a time\n # Removed ['amber', 'amberff94'] from OE list, as those won't find the residue types they're expecting\n toolkit_to_charge_method = {\n OpenEyeToolkitWrapper: [\n \"mmff\",\n \"mmff94\",\n \"am1bcc\",\n \"am1bccnosymspt\",\n \"am1bccelf10\",\n ],\n AmberToolsToolkitWrapper: [\"bcc\", \"gas\", \"mul\"],\n }\n\n manual_skips = []\n\n manual_skips.append(\n \"ZINC1564378\"\n ) # Warning: OEMMFF94Charges: assigning OEMMFFAtomTypes failed on mol .\n manual_skips.append(\n \"ZINC00265517\"\n ) # Warning: OEMMFF94Charges: assigning OEMMFFAtomTypes failed on mol .\n\n for toolkit in list(toolkit_to_charge_method.keys()):\n toolkit_registry = ToolkitRegistry(toolkit_precedence=[toolkit])\n for charge_model in toolkit_to_charge_method[toolkit]:\n c = 0\n for molecule in molecules[:1]: # Just test first molecule to save time\n c += 1\n if molecule.name in manual_skips: # Manual skips, hopefully rare\n continue\n molecule.compute_partial_charges(\n charge_model=charge_model, toolkit_registry=toolkit_registry\n )\n charges1 = molecule._partial_charges\n # Make sure everything isn't 0s\n assert (abs(charges1 / unit.elementary_charge) > 0.01).any()\n # Check total charge\n charges_sum_unitless = charges1.sum() / unit.elementary_charge\n # if abs(charges_sum_unitless - float(molecule.total_charge)) > 0.0001:\n # print('c {} molecule {} charge_sum {} molecule.total_charge {}'.format(c, molecule.name,\n # charges_sum_unitless,\n # molecule.total_charge))\n # assert_almost_equal(charges_sum_unitless, molecule.total_charge, decimal=4)\n\n # Call should be faster second time due to caching\n # TODO: Implement caching\n molecule.compute_partial_charges(\n charge_model=charge_model, toolkit_registry=toolkit_registry\n )\n charges2 = molecule._partial_charges\n assert np.allclose(charges1, charges2, atol=0.002)","def test_run_loop_exc(self):\n with self.assertRaises(ExecutionException):\n pyint = Interpreter(limit=1)\n pyint.run(code=BF_CODE_LOOP_TWICE)","def test_circularloop(self):\n cmd = f\"{SRC_LISTER} -i {PWD}/main\"\n with subprocess.Popen(\n shlex.split(cmd), stdout=subprocess.PIPE, stderr=subprocess.PIPE\n ) as proc:\n try:\n out, err = proc.communicate(timeout=5)\n assert len(err.strip()) > 0, \"Expected a circular reference error\"\n except subprocess.TimeoutExpired as te:\n print(\"Unexpected parser timeout during infinite loop test\")","def runSingleTest(cube, instructions, interval):\n root = Tk()\n interface = Interface(root, cube)\n root.after(0, interface.runInstructions, instructions, interval)\n root.mainloop()","def loop_run(self, loops):\n self.loop_seek(self.num_loops + loops)","def test_multi_molecules_diff_sizes(self, multi_mol_system_irregular, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_irregular)\n found = self.sequence_from_system(multi_mol_system_irregular, \"test\")\n assert found == expected","def run_one_test_cycle(self):\n logging.info(\n \"{0} operations remaining: {1}\".format(\n self.args.pm_operation, self.args.repetitions\n )\n )\n\n self.check_last_cycle_duration()\n if self.args.repetitions > 0:\n self.run_pm_command()\n else:\n self.summary()","def algorithm_loop(self):","def _run_cycle(self):\n pass","def do_simulation_loop(self) -> tuple[bool, bool]:\n running, reset = True, False\n for event in pygame.event.get():\n if check_for_quit(event):\n running = False\n elif check_for_reset(event):\n running = False\n reset = True\n self.simulation.do_step()\n self.update_visualization()\n self.simple_pygame.loop()\n return running, reset","def runMasking(self,roiNode,inputVolumes,inPlace):\n\n self.delayDisplay('Running the algorithm')\n\n for vol in inputVolumes:\n self.maskVolume(vol, roiNode, inPlace)\n\n return True\n\n self.delayDisplay('Running the aglorithm')","async def test_routine(self):\n print('Running test routine...')\n print('Waiting for axes to initialize...')\n await self.robot.wait_until_initialized()\n print('Synchronizing robot state with peripheral...')\n await self.robot.synchronize_values()\n print('Loading calibration data...')\n await self.robot.load_calibrations()\n await self.robot.go_to_alignment_hole()\n\n print('Starting 96-well plate test...')\n await self.robot.go_to_96_well_plate(1, 'a')\n await self.robot.dispense('96-well plate', 'far above')\n for height in ['bottom', 'low', 'mid', 'high', 'top', 'above', 'far above']:\n print('Testing with height {}...'.format(height))\n for (row, volume) in [('a', 20), ('b', 30), ('c', 40), ('d', 50), ('e', 100)]:\n print(\n ' Testing precise with row {} and volume {} mL...'\n .format(row, volume)\n )\n await self.test_individual_precise(row, height, volume / 1000)\n await self.robot.dispense('96-well plate', height)\n for (row, volume) in [\n ('f', 100), ('g', 150), ('h', 200), ('a', 300), ('b', 400),\n ('c', 500), ('d', 600), ('e', 700), ('g', 800), ('h', 900)\n ]:\n print(\n ' Testing rough with row {} and volume {} mL...'\n .format(row, volume / 1000)\n )\n await self.test_individual_rough(row, height, volume / 1000)\n await self.robot.z.go_to_high_end_position()\n await self.robot.y.go_to_low_end_position()\n\n print(batch.OUTPUT_FOOTER)\n print('Quitting...')","def test_omp(self):\n ex = self.ex\n j = self.j\n\n nreps = random.randint(1, 10)\n ncalls = random.randint(1, 10)\n ex.calls = ncalls * [ex.call]\n ex.nreps = nreps\n ex.calls_parallel = True\n\n cmds = ex.generate_cmds()\n\n self.assertEqual(cmds.count([\"{omp\"]), nreps)\n self.assertEqual(cmds.count([\"}\"]), nreps)\n\n lensumrange = random.randint(1, 10)\n ex.sumrange = [j, range(lensumrange)]\n ex.sumrange_parallel = True\n\n cmds = ex.generate_cmds()\n\n self.assertEqual(cmds.count([\"{omp\"]), nreps)\n self.assertEqual(cmds.count([\"}\"]), nreps)","def runtest(self):\n folder = self.path.parent\n folders = folder.parts\n cwd = os.path.abspath(os.path.join(folder, \"../..\"))\n scenario = folders[-1]\n # role = folders[-3] # noqa\n\n cmd = [sys.executable, \"-m\", \"molecule\"]\n if self.config.option.molecule_base_config:\n cmd.extend((\"--base-config\", self.config.option.molecule_base_config))\n if self.config.option.skip_no_git_change:\n try:\n with subprocess.Popen(\n [\"git\", \"diff\", self.config.option.skip_no_git_change, \"--\", \"./\"],\n cwd=cwd,\n stdout=subprocess.PIPE,\n stderr=subprocess.STDOUT,\n universal_newlines=True,\n ) as proc:\n proc.wait()\n if len(proc.stdout.readlines()) == 0:\n pytest.skip(\"No change in role\")\n except Exception as exc: # pylint: disable=broad-except\n pytest.fail(\"Error checking git diff. Error was:\" + str(exc))\n\n cmd.extend((self.name, \"-s\", scenario))\n # We append the additional options to molecule call, allowing user to\n # control how molecule is called by pytest-molecule\n opts = os.environ.get(\"MOLECULE_OPTS\")\n if opts:\n cmd.extend(shlex.split(opts))\n\n print(f\"running: {' '.join(quote(arg) for arg in cmd)} (from {cwd})\")\n try:\n # Workaround for STDOUT/STDERR line ordering issue:\n # https://github.com/pytest-dev/pytest/issues/5449\n\n with subprocess.Popen(\n cmd,\n cwd=cwd,\n stdout=subprocess.PIPE,\n stderr=subprocess.STDOUT,\n universal_newlines=True,\n ) as proc:\n for line in proc.stdout:\n print(line, end=\"\")\n proc.wait()\n if proc.returncode != 0:\n pytest.fail(\n f\"Error code {proc.returncode} returned by: {' '.join(cmd)}\",\n pytrace=False,\n )\n except Exception as exc: # pylint: disable=broad-except\n pytest.fail(f\"Exception {exc} returned by: {' '.join(cmd)}\", pytrace=False)","def _run(self):\n while(self._loop):\n pass","async def main(dut):\n # Create a 10us period clock on port clk\n clock = Clock(dut.clk_i, 10, units=\"us\")\n cocotb.fork(clock.start())\n\n # Reset system\n await FallingEdge(dut.clk_i)\n dut.rst_n_i <= 0\n dut.en_i <= 0\n dut.data_i <= 0\n dut.valid_i <= 0\n\n # reset\n await FallingEdge(dut.clk_i)\n dut.rst_n_i <= 1\n\n # test 1\n dut.en_i <= 1\n x, y = get_test_vector()\n cocotb.fork(write_input(dut, x))\n await check_output(dut, y)\n\n # test 2\n dut.en_i <= 0\n await check_output_no_en(dut)\n\n # test 3\n dut.en_i <= 1\n x, y = get_test_vector()\n cocotb.fork(write_input(dut, x))\n await check_output(dut, y)","def correct(self):\n stop_flag = False\n self.orbit_class.online_calc = False\n # read orbit devs\n for elem in self.orbit.corrs:\n try:\n elem.kick_mrad = elem.mi.get_value()\n except Exception as e:\n stop_flag = True\n logger.warning(elem.id + \" reading error: \" + str(e))\n return stop_flag\n \n elem.angle_read = elem.kick_mrad*1e-3\n elem.i_kick = elem.kick_mrad\n elem.ui.set_init_value(elem.kick_mrad)\n elem.ui.set_value(elem.kick_mrad)\n elem.transfer_map = self.parent.lat.method.create_tm(elem)\n if elem.ui.alarm:\n stop_flag = True\n logger.warning(\"correct - STOP: corrector shows alarm: \" + elem.id)\n\n\n #self.parent.lat.update_transfer_maps()\n\n for elem in self.orbit.bpms:\n if elem.id not in self.new_ref_orbit.keys():\n logger.warning(\"correct - STOP: BPM is not in new ref orbit: \" + elem.id)\n stop_flag = True\n return stop_flag\n elem.x = self.new_ref_orbit[elem.id][0]\n elem.y = self.new_ref_orbit[elem.id][1]\n elem.ui.set_value((elem.x*1000., elem.y*1000.))\n if elem.ui.alarm:\n logger.warning(\"correct - STOP: BPM shows alarm: \" + elem.id)\n stop_flag = True\n if stop_flag:\n return stop_flag\n self.orbit_class.online_calc = True\n\n\n if not self.orbit_class.is_rm_ok(self.orbit):\n logger.error(\" correct: Calculate Response Matrix\")\n self.parent.error_box(\"Calculate Response Matrix\")\n return 0\n\n self.orbit_class.golden_orbit.dict2golden_orbit()\n\n if self.orbit_class.ui.cb_close_orbit.isChecked():\n self.orbit_class.close_orbit()\n\n self.calc_correction = {}\n for cor in self.orbit.corrs:\n cor.angle = 0.\n self.calc_correction[cor.id] = cor.angle\n\n alpha = 0.\n\n self.orbit.correction(alpha=alpha, p_init=None, beta=0, print_log=False)\n for cor in self.orbit.corrs:\n self.calc_correction[cor.id] = cor.angle\n\n self.set_values2correctors()\n return stop_flag","def test_validation_correct_molecules():\n paths = examples_paths()\n molecules = [\n {'name': 'toluene', 'leap': {'parameters': 'leaprc.gaff'}},\n {'name': 'toluene', 'leap': {'parameters': ['leaprc.gaff', 'toluene.frcmod']}},\n {'name': 'p-xylene', 'antechamber': {'charge_method': 'bcc'}},\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'},\n 'antechamber': {'charge_method': None}},\n {'name': 'p-xylene', 'antechamber': {'charge_method': 'bcc'},\n 'epik': {'ph': 7.6, 'ph_tolerance': 0.7, 'tautomerize': False, 'select': 0}},\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'},\n 'antechamber': {'charge_method': None}, 'epik': {'select': 1}},\n\n {'filepath': paths['abl']},\n {'filepath': paths['abl'], 'leap': {'parameters': 'leaprc.ff99SBildn'}},\n {'filepath': paths['abl'], 'leap': {'parameters': 'leaprc.ff99SBildn'}, 'select': 1},\n {'filepath': paths['abl'], 'select': 'all'},\n {'filepath': paths['abl'], 'select': 'all', 'strip_protons': True},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {}},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'add_missing_residues': True}},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'add_missing_atoms': 'all', 'ph': '8.0'}},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'remove_heterogens': 'all'}},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'replace_nonstandard_residues': True}},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'apply_mutations': {'chain_id': 'A', 'mutations': 'T85I'}}},\n {'filepath': paths['abl'], 'select': 'all', 'modeller': {'apply_mutations': {'chain_id': 'A', 'mutations': 'T85I'}}},\n {'filepath': paths['abl'], 'select': 'all', 'modeller': {'apply_mutations': {'chain_id': 'A', 'mutations': 'WT'}}},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'apply_mutations': {'chain_id': 'A', 'mutations': 'I8A/T9A'}}},\n {'filepath': paths['toluene'], 'leap': {'parameters': 'leaprc.gaff'}},\n {'filepath': paths['benzene'], 'epik': {'select': 1, 'tautomerize': False}},\n # Regions tests, make sure all other combos still work\n {'name': 'toluene', 'regions': {'a_region': 4}},\n {'name': 'toluene', 'regions': {'a_region': 'dsl string'}},\n {'name': 'toluene', 'regions': {'a_region': [0, 2, 3]}},\n {'name': 'toluene', 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}},\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': 4}},\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': 'dsl string'}},\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': [0, 2, 3]}},\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}},\n {'filepath': paths['abl'], 'regions': {'a_region': 4}},\n {'filepath': paths['abl'], 'regions': {'a_region': 'dsl string'}},\n {'filepath': paths['abl'], 'regions': {'a_region': [0, 2, 3]}},\n {'filepath': paths['abl'], 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}},\n {'filepath': paths['toluene'], 'regions': {'a_region': 4}},\n {'filepath': paths['toluene'], 'regions': {'a_region': 'dsl string'}},\n {'filepath': paths['toluene'], 'regions': {'a_region': [0, 2, 3]}},\n {'filepath': paths['toluene'], 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}}\n ]\n for molecule in molecules:\n yield ExperimentBuilder._validate_molecules, {'mol': molecule}","def loop(self, loop: bool=None):\n self._select_interface(self._rc_loop, self._http_loop, loop)","def main():\n moons = initialize_moons()\n\n # Do it again, to get a stable initial set of values to compare against.\n initial_state = initialize_moons()\n needed_cycles = [0] * 3\n\n # Because in the mechanics of this fake universe gravity and velocity in\n # one dimension do not affect anything in the other two dimensions, we\n # can loop altering one dimension at a time until\n for dimension in (Position3d.X, Position3d.Y, Position3d.Z):\n Position3d.set_dimension(dimension)\n cycled = False\n cycle_count = 0\n while not cycled:\n if cycle_count > 30000000000:\n print(\"bailing!\")\n break\n cycle_count += 1\n for moon in moons:\n for other_moon in moons:\n if moon is other_moon:\n continue\n moon.apply_gravity(other_moon)\n for moon in moons:\n moon.apply_velocity()\n match = True\n for idx, moon in enumerate(moons):\n if moon != initial_state[idx]:\n # Didn't complete a cycle back to original state for this\n # dimension. Try again.\n match = False\n break\n if match:\n # Yea! Done with this dimension\n needed_cycles[dimension] = cycle_count\n cycled = True\n\n print(lcm(needed_cycles[2], lcm(needed_cycles[0], needed_cycles[1])),\n \"cycles needed to loop.\")\n print(\"Hawking would be proud.\")","def setUp(self):\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Name the first molecule.\n cdp.mol[0].name = 'Ap4Aase'\n\n # Add a second molecule to the system.\n cdp.mol.add_item(mol_name='RNA')\n\n # Add two more residues to the first molecule (and set the residue number of the first).\n cdp.mol[0].res[0].num = 1\n cdp.mol[0].res.add_item(res_num=2, res_name='Glu')\n cdp.mol[0].res.add_item(res_num=4, res_name='Pro')\n\n # Add some spin info to this molecule.\n cdp.mol[0].res[0].spin[0].name = 'NH'\n cdp.mol[0].res[0].spin[0].num = 60\n cdp.mol[0].res[1].spin[0].name = 'NH'\n cdp.mol[0].res[1].spin[0].num = 63\n\n # Add one more residue to the second molecule (and set the residue number of the first).\n cdp.mol[1].res[0].num = -5\n cdp.mol[1].res.add_item(res_num=-4)\n\n # Add a second set of spins to the second molecule (naming the first set first).\n cdp.mol[1].res[0].spin[0].name = 'C8'\n cdp.mol[1].res[1].spin[0].name = 'C8'\n cdp.mol[1].res[0].spin.add_item(spin_name='N5')\n cdp.mol[1].res[1].spin.add_item(spin_name='N5')\n cdp.mol[1].res[1].spin.add_item(spin_name='2H', spin_num=132)\n\n # Deselect a number of spins.\n cdp.mol[0].res[0].spin[0].select = 0\n cdp.mol[0].res[2].spin[0].select = 0\n cdp.mol[1].res[0].spin[0].select = 0\n cdp.mol[1].res[1].spin[1].select = 0\n\n # Update the metadata.\n mol_res_spin.metadata_update()","def test_simulate(self, scml_system):\n\n # Reset the system and take a random action\n scml_system.reset()\n action = scml_system.action_space.sample()\n # Set a defined intitial state\n ode_state = np.array([3, 4, 5, 6])\n scml_system._ode_solver.set_initial_value(ode_state)\n # Perform the action on the system\n next_state = scml_system.simulate(action)\n solver_state_me = scml_system._ode_solver.y[:len(DummyLoad.state_names)]\n solver_state_el = scml_system._ode_solver.y[len(DummyLoad.state_names):]\n torque = [scml_system.electrical_motor.torque(solver_state_el)]\n u_sup = [scml_system.supply.u_nominal]\n u_in = [u * u_sup[0] for u in scml_system.converter.u_in]\n # Calculate the next state\n desired_next_state = (\n np.concatenate((solver_state_me, torque, solver_state_el, u_in, u_sup))\n ) / scml_system.limits\n\n # Assertions for correct simulation\n assert all(desired_next_state == next_state), 'The calculated next state differs from the expected one'\n assert scml_system.converter.action == action, 'The action was not passed correctly to the converter'\n assert scml_system.converter.action_set_time == 0, 'The action start time was passed incorrect to the converter'\n assert scml_system.converter.last_i_out == scml_system.electrical_motor.i_in(scml_system._ode_solver.last_y[2:])","def run(self):\n while True:\n if self.job_q.empty():\n self.message_q.put(False)\n return\n try:\n smolecule = self.job_q.get()\n self.data_pointer[smolecule].get_adp(self.Temp)\n except IndexError:\n self.message_q.put((smolecule, None))\n try:\n self.message_q.put((smolecule, [j.adp['cart_int'] for j in self.data_pointer[smolecule].atoms]))\n except KeyError:\n # =======================================================\n # self.message_q.put((molecule,[0 for i in self.data_pointer[molecule].atoms]))\n #=======================================================\n pass","def test_analog_in_out_loop(self):\n for v in range(0, 6, 1):\n self.l.output(ao0=v, ao1=v)\n r = self.l.input(channels=(8,8,9,9), gains=(1,4,1,4))[0]\n for i in r:\n self.assertTrue(abs(v-i) < .1,\n \"measured %g for %g\" % (i, v))","def test_shared_wires(self):\n wires = range(2)\n estimation_wires = range(1, 3)\n\n with pytest.raises(ValueError, match=\"No wires can be shared between the wires\"):\n quantum_monte_carlo(\n lambda: None, wires=wires, target_wire=0, estimation_wires=estimation_wires\n )","def test_epik_enumeration():\n with mmtools.utils.temporary_directory() as tmp_dir:\n yaml_content = get_template_script(tmp_dir, keep_schrodinger=True)\n exp_builder = ExperimentBuilder(yaml_content)\n mol_ids = ['benzene-epik0', 'benzene-epikcustom']\n exp_builder._db._setup_molecules(*mol_ids)\n\n for mol_id in mol_ids:\n output_dir = exp_builder._db.get_molecule_dir(mol_id)\n output_basename = os.path.join(output_dir, mol_id + '-epik.')\n assert os.path.exists(output_basename + 'mol2')\n assert os.path.getsize(output_basename + 'mol2') > 0\n assert os.path.exists(output_basename + 'sdf')\n assert os.path.getsize(output_basename + 'sdf') > 0","def run(self):\n while True:\n try:\n self.check_value()\n except Exception as e:\n print(f\"[ERROR]: Error running the continuous run loop on sample_module: {e}\")\n continue","def run( self, cycles=-1 ):","def test_selection():\n pdb_inp = iotbx.pdb.input(source_info=None, lines=pdb_answer_0)\n ncs_obj_phil = ncs.input(\n hierarchy=pdb_inp.construct_hierarchy())\n nrg = ncs_obj_phil.get_ncs_restraints_group_list()\n\n m1 = list(nrg[0].master_iselection)\n c1 = list(nrg[0].copies[0].iselection)\n c2 = list(nrg[0].copies[1].iselection)\n\n assert len(m1) == len(c1) # renumbering\n assert m1 == [0, 1, 2, 3, 4, 5, 6] # 0, 1, X, 3, X, 5, X | 0, 1, 3\n assert c1 == [7, 8, 9, 10, 11, 12, 13] # 7, 8, 9, X, X, 12, X | 4, 5, 7\n assert c2 == [14, 15, 16, 17, 18, 19, 20] # 14, 15, X, 17, X, 19, X | 8, 9, 11\n\n selection1 = flex.size_t([0,1,5,3,100,101])\n selection2 = flex.size_t([0,1,5,3,7,8,9,12,100,101])\n selection3 = flex.size_t([0,1,5,3,7,8,9,12,14,15,19,17,100,101])\n # gone iseqs for selection3: 2,4,6,10,11,13,16,18,20-99\n\n new_nrg = nrg.select(flex.bool(102, selection1))\n # only atoms in master are selected\n mt = list(new_nrg[0].master_iselection)\n c1t = list(new_nrg[0].copies[0].iselection)\n\n assert mt == []\n assert c1t == []\n\n # atoms selected in both master and copies\n new_nrg = nrg.select(flex.bool(102, selection2))\n # only atoms in master are selected\n mt = list(new_nrg[0].master_iselection)\n c1t = list(new_nrg[0].copies[0].iselection)\n\n assert mt == []\n assert c1t == []\n\n new_nrg = nrg.select(flex.bool(102, selection3))\n # only atoms in master are selected\n mt = list(new_nrg[0].master_iselection)\n c1t = list(new_nrg[0].copies[0].iselection)\n c2t = list(new_nrg[0].copies[1].iselection)\n\n assert mt == [0, 1, 3], list(mt)\n assert c1t == [4, 5, 7], list(c1t)\n assert c2t == [8, 9, 11], list(c2t)","async def loop():\n # ArmDevice.storage.joints_pos = await get_positions() # Use this if encoders are wired up.\n # ArmDevice.storage.joints_pos = simulate_positions() # Use this for testing without position feedback.\n log.debug(\"command: {}\".format(ArmDevice.storage.command))\n ArmDevice.storage.controller.user_command(ArmDevice.storage.mode, *ArmDevice.storage.command)\n ArmDevice.storage.speeds = ArmDevice.storage.controller.update_duties(ArmDevice.storage.joints_pos)\n\n # publish speeds/duty cycles here\n log.debug(\"joints_pos: {}\".format(ArmDevice.storage.joints_pos))\n log.debug(\"speeds: {}\".format(ArmDevice.storage.speeds))\n await send_duties()","def test_for_restart(self):\n #print(\"entering test_for_restart()\")\n self._compile_result(\"UserName: \" + self.user_name)\n #if self.first_song == True:\n # msg = \"Welcome_str\"\n # self.first_song = False\n if self._feedback_plat == \"RIVA\":\n self._RIVA_message_num += 1\n text_to_RIVA(\"Welcome_str\")\n else:# self._feedback_plat == \"Text\":\n self._RIVA_message_num += 1\n #to_no_voice_log(\"NewData:{};TTS:{}\".format(self._RIVA_message_num, msg))\n ###else:\n ### text_to_ispeech(ispeech_formatter(msg))\n while True:\n self._check_completion()\n if self._song_over is False:\n print(\"Song Started\")\n if self._feedback_plat == \"RIVA\":\n reset_RIVA_log()\n self._RIVA_message_num += 1\n #text_to_RIVA(self.response_welcome())\n elif self._feedback_plat == \"Text\":\n to_no_voice_log((emo_less_feedback(0, 0, 0)))\n self.execute_song()\n print(\"Re-entered Test_for_restart()\")\n if self._song_over is True:\n interface_info = gather_info(\n parse_csv(read_csv(CSV_functions.MUSICGLOVE)))\n #print(interface_info)\n #print(\"Song_over min/max = \", min_max)\n self.user_stats.set_grips(interface_info)\n self._compile_result(grip_avg_summary_str(interface_info))\n evaluated_info = [evaluate_worst_grip(interface_info, self._last_worst_grip),\n evaluate_best_grip(interface_info)]\n summary = summary_generator(evaluated_info[0], evaluated_info[1])\n if self._feedback_plat == \"RIVA\":\n self._RIVA_message_num += 1\n #print(\"message_num={} summary={}\".format(self._message_num, summary))\n text_to_RIVA(summary)\n else:# self._feedback_plat == \"Text\":\n to_no_voice_log(emo_less_feedback(self._RIVA_message_num, evaluated_info[0], evaluated_info[1]))\n ###else:\n ### text_to_ispeech(ispeech_formatter(summary))\n self._last_30_sec = []\n self._compile_result(summary)\n self._csv_result.extend(read_csv(CSV_functions.MUSICGLOVE))\n make_csv(self._csv_result, CSV_functions.M_GLOVE_SUMMARIES, what_song(self._grip_count))\n self.__init__(self.user_name, restart=True)\n self._RIVA_message_num = 1\n else:\n pass\n return","def ml_loop(side: str):\n\n # === Here is the execution order of the loop === #\n # 1. Put the initialization code here\n ball_served = False\n blocker_last_x = 0\n\n class Pred:\n pred = 100\n blocker_pred_x = 0\n last_command = 0\n blocker_vx = 0\n\n \n def move_to(player, pred) : #move platform to predicted position to catch ball \n if player == '1P':\n if scene_info[\"platform_1P\"][0]+20 > (pred-10) and scene_info[\"platform_1P\"][0]+20 < (pred+10): return 0 # NONE\n elif scene_info[\"platform_1P\"][0]+20 <= (pred-10) : return 1 # goes right\n else : return 2 # goes left\n else :\n if scene_info[\"platform_2P\"][0]+20 > (pred-10) and scene_info[\"platform_2P\"][0]+20 < (pred+10): return 0 # NONE\n elif scene_info[\"platform_2P\"][0]+20 <= (pred-10) : return 1 # goes right\n else : return 2 # goes left\n\n def ml_loop_for_1P(): \n # ball slicing\n if scene_info[\"ball_speed\"][1] > 0 and (scene_info[\"ball\"][1]+scene_info[\"ball_speed\"][1]) >= 415 and Pred.last_command == 0:\n print(\"------\")\n ball_x = scene_info[\"ball\"][0]\n ball_y = scene_info[\"ball\"][1]\n ball_vx = scene_info[\"ball_speed\"][0]\n ball_slice_vx = scene_info[\"ball_speed\"][0]+np.sign(scene_info[\"ball_speed\"][0])*3\n ball_vy = scene_info[\"ball_speed\"][1] \n blocker_x = scene_info['blocker'][0] + Pred.blocker_vx\n \n y = abs((415 - ball_y) // ball_vy)\n pred_ball_1P = ball_x + ball_vx * y\n\n y = abs((415 - 260) // ball_vy)\n pred_ball_blocker = pred_ball_1P + ball_slice_vx * y\n bound = pred_ball_blocker // 200 # Determine if it is beyond the boundary\n if (bound > 0): # pred > 200 # fix landing position\n if (bound%2 == 0) : \n pred_ball_blocker = pred_ball_blocker - bound*200 \n else :\n pred_ball_blocker = 200 - (pred_ball_blocker - 200*bound)\n elif (bound < 0) : # pred < 0\n if (bound%2 ==1) :\n pred_ball_blocker = abs(pred_ball_blocker - (bound+1) *200)\n else :\n pred_ball_blocker = pred_ball_blocker + (abs(bound)*200)\n \n y = abs((415 - 260) // ball_vy)\n Pred.blocker_pred_x = blocker_x + Pred.blocker_vx * y \n if Pred.blocker_pred_x < 0: Pred.blocker_pred_x = abs(Pred.blocker_pred_x)\n elif Pred.blocker_pred_x > 170: Pred.blocker_pred_x = 170 - (Pred.blocker_pred_x - 170)\n \n if pred_ball_blocker >= Pred.blocker_pred_x-10 and pred_ball_blocker < Pred.blocker_pred_x+40:\n print(\"slice will hit blicker\")\n # don't slice \n # use origin ball vx to predict will hit blocker or not\n # if will hit blicker let ball go reverse direction\n y = abs((415 - 260) // ball_vy)\n pred_ball_blocker = pred_ball_1P + ball_vx * y\n bound = pred_ball_blocker // 200 # Determine if it is beyond the boundary\n if (bound > 0): # pred > 200 # fix landing position\n if (bound%2 == 0) : \n pred_ball_blocker = pred_ball_blocker - bound*200 \n else :\n pred_ball_blocker = 200 - (pred_ball_blocker - 200*bound)\n elif (bound < 0) : # pred < 0\n if (bound%2 ==1) :\n pred_ball_blocker = abs(pred_ball_blocker - (bound+1) *200)\n else :\n pred_ball_blocker = pred_ball_blocker + (abs(bound)*200)\n\n if pred_ball_blocker >= Pred.blocker_pred_x-10 and pred_ball_blocker < Pred.blocker_pred_x+40:\n print(\"will hit blocker, hit reversed direction\")\n if scene_info[\"ball_speed\"][0] > 0: return 2\n else: return 1\n else: \n print(\"will not hit blicker, do nothing\")\n return 0\n else:\n # slice\n print(\"slice will not hit blocker\")\n if scene_info[\"ball_speed\"][0] > 0: return 1\n else: return 2\n\n elif scene_info[\"ball_speed\"][1] > 0 : # 球正在向下 # ball goes down\n x = ( scene_info[\"platform_1P\"][1]-scene_info[\"ball\"][1] ) // scene_info[\"ball_speed\"][1] # 幾個frame以後會需要接 # x means how many frames before catch the ball\n Pred.pred = scene_info[\"ball\"][0]+(scene_info[\"ball_speed\"][0]*x) # 預測最終位置 # pred means predict ball landing site \n bound = Pred.pred // 200 # Determine if it is beyond the boundary\n if (bound > 0): # pred > 200 # fix landing position\n if (bound%2 == 0) : \n Pred.pred = Pred.pred - bound*200 \n else :\n Pred.pred = 200 - (Pred.pred - 200*bound)\n elif (bound < 0) : # pred < 0\n if (bound%2 ==1) :\n Pred.pred = abs(Pred.pred - (bound+1) *200)\n else :\n Pred.pred = Pred.pred + (abs(bound)*200)\n return move_to(player = '1P',pred = Pred.pred)\n \n else : # 球正在向上 # ball goes up\n return move_to(player = '1P',pred = 100)\n\n\n\n def ml_loop_for_2P(): # as same as 1P\n if scene_info[\"ball_speed\"][1] > 0 : \n return move_to(player = '2P',pred = 100)\n else : \n x = ( scene_info[\"platform_2P\"][1]+30-scene_info[\"ball\"][1] ) // scene_info[\"ball_speed\"][1] \n pred = scene_info[\"ball\"][0]+(scene_info[\"ball_speed\"][0]*x) \n bound = pred // 200 \n if (bound > 0):\n if (bound%2 == 0):\n pred = pred - bound*200 \n else :\n pred = 200 - (pred - 200*bound)\n elif (bound < 0) :\n if bound%2 ==1:\n pred = abs(pred - (bound+1) *200)\n else :\n pred = pred + (abs(bound)*200)\n return move_to(player = '2P',pred = pred)\n\n # 2. Inform the game process that ml process is ready\n comm.ml_ready()\n\n # 3. Start an endless loop\n while True:\n # 3.1. Receive the scene information sent from the game process\n scene_info = comm.recv_from_game()\n\n # 3.2. If either of two sides wins the game, do the updating or\n # resetting stuff and inform the game process when the ml process\n # is ready.\n if scene_info[\"status\"] != \"GAME_ALIVE\":\n # Do some updating or resetting stuff\n ball_served = False\n\n # 3.2.1 Inform the game process that\n # the ml process is ready for the next round\n comm.ml_ready()\n continue\n\n # 3.3 Put the code here to handle the scene information\n\n # 3.4 Send the instruction for this frame to the game process\n if not ball_served:\n comm.send_to_game({\"frame\": scene_info[\"frame\"], \"command\": \"SERVE_TO_LEFT\"})\n blocker_last_x = scene_info[\"blocker\"][0]\n Pred.last_command = 0\n ball_served = True\n else:\n if side == \"1P\":\n Pred.blocker_vx = scene_info[\"blocker\"][0] - blocker_last_x\n if scene_info[\"blocker\"][0] == 0: Pred.blocker_vx = 5\n elif scene_info[\"blocker\"][0] == 170: Pred.blocker_vx = -5\n command = ml_loop_for_1P()\n blocker_last_x = scene_info[\"blocker\"][0]\n Pred.last_command = command\n else:\n command = ml_loop_for_2P()\n\n if command == 0:\n comm.send_to_game({\"frame\": scene_info[\"frame\"], \"command\": \"NONE\"})\n elif command == 1:\n comm.send_to_game({\"frame\": scene_info[\"frame\"], \"command\": \"MOVE_RIGHT\"})\n else :\n comm.send_to_game({\"frame\": scene_info[\"frame\"], \"command\": \"MOVE_LEFT\"})","async def checkNewLoop(self):\n pass","def test_using_mirror_output_type():\n\n def check_correct_type(index):\n # Force a race condition\n if index == 0:\n sleep(0.1)\n if index % 2 == 0:\n with _using_mirror_output_type():\n sleep(0.5)\n return cuml.global_settings.output_type == \"mirror\"\n else:\n output_type = test_output_types_str[index]\n with using_output_type(output_type):\n sleep(0.5)\n return cuml.global_settings.output_type == output_type\n\n results = [\n delayed(check_correct_type)(index)\n for index in range(len(test_output_types_str))\n ]\n\n assert (delayed(all)(results)).compute()","def check_calcs_v2(list_mols, data_file=\"\", max_restart=False, depth='medium', frc=False):\n import warnings\n from gausspy.gaussian_job_manager import server_data_unequal\n from gausspy.data_extract_utils import latest_restarts, import_moldata, load_from_server\n from gausspy.data_extract_utils import oniom_components_on_server, export_moldata, clean_local_files\n from gausspy import oniom_utils\n\n if max_restart:\n list_mols = latest_restarts(list_mols)\n\n #if we are forcing we ignore previously saved data\n if not frc:\n current_data = import_moldata(data_file)\n else:\n current_data = []\n\n #check saved data against current list of molecules\n current_labels = [m.calc.label for m in current_data]\n mol_labels = [m.calc.label for m in list_mols]\n mismatched_labels = [label for label in current_labels if label not in mol_labels]\n\n if mismatched_labels:\n warnings.warn(\n RuntimeWarning(\n \"Calculations: {m} in data_file do not match molecules passed to check_calcs\".format(\n m=\" \".join(mismatched_labels))\n )\n )\n\n #extract calculation data from the datafile (note at the moment we are not extracting the non calculation part\n # which means that if the calculation modifies the original ase object those changes will be lost\n for saved_mol in current_data:\n try:\n ind = mol_labels.index(saved_mol.calc.label)\n #loading the entire object = list_mols[ind] = saved_mod\n #but because of python's reference passing behaviour this would mean check_calcs_v2 would not act like check_calcs (think restarted incomplete calculations)\n list_mols[ind].calc = saved_mol.calc\n except ValueError:\n pass\n\n if frc:\n update_mask = [True for i in range(len(list_mols))]\n else:\n update_mask =server_data_unequal(list_mols)\n\n mols_to_update = [list_mols[i] for i in range(len(list_mols)) if update_mask[i]]\n for mol in mols_to_update:\n #if log files on home directory and server are different we copy those files to the home directory\n mol = load_from_server(mol, depth)\n\n #if we have an oniom calculation we check to see if the components of the calculation have been run and if so we retrieve them and attach them to the calculation object\n if 'oniom' in mol.calc.method and oniom_components_on_server(mol):\n init_mol = copy.deepcopy(mol)\n init_mol.calc.label += '_init'\n init_mol = load_from_server(init_mol, depth)\n mol.calc.components = oniom_utils.oniom_comp_calcs(init_mol)\n mol.calc.components = check_calcs_v2(mol.calc.components, depth=depth, max_restart=True, frc=frc)\n\n if data_file and any(update_mask):\n export_moldata(data_file, list_mols)\n clean_local_files(mols_to_update)\n\n return list_mols","def test_run_concurrency(microvm_factory, network_config, guest_kernel, rootfs):\n\n for i in range(NO_OF_MICROVMS):\n microvm = microvm_factory.build(guest_kernel, rootfs)\n microvm.spawn()\n microvm.basic_config(vcpu_count=1, mem_size_mib=128)\n microvm.ssh_network_config(network_config, str(i))\n microvm.start()\n\n # We check that the vm is running by testing that the ssh does\n # not time out.\n microvm.ssh.run(\"true\")","def test_modul1(self):\n\n self.delayDisplay(\"Starting the test\")\n #\n # first, get some data\n #\n import urllib\n downloads = (\n ('http://slicer.kitware.com/midas3/download?items=5767', 'FA.nrrd', slicer.util.loadVolume),\n )\n\n for url,name,loader in downloads:\n filePath = slicer.app.temporaryPath + '/' + name\n if not os.path.exists(filePath) or os.stat(filePath).st_size == 0:\n logging.info('Requesting download %s from %s...\\n' % (name, url))\n urllib.urlretrieve(url, filePath)\n if loader:\n logging.info('Loading %s...' % (name,))\n loader(filePath)\n self.delayDisplay('Finished with download and loading')\n\n volumeNode = slicer.util.getNode(pattern=\"FA\")\n logic = modulLogic()\n self.assertTrue( logic.hasImageData(volumeNode) )\n self.delayDisplay('Test passed!')","def test_clashing_atoms():\n benzene_path = examples_paths()['benzene']\n toluene_path = examples_paths()['toluene']\n with mmtools.utils.temporary_directory() as tmp_dir:\n yaml_content = get_template_script(tmp_dir, keep_openeye=True)\n system_id = 'explicit-system'\n system_description = yaml_content['systems'][system_id]\n system_description['pack'] = True\n system_description['solvent'] = utils.CombinatorialLeaf(['vacuum', 'PME'])\n\n # Sanity check: at the beginning molecules clash\n toluene_pos = utils.get_oe_mol_positions(utils.load_oe_molecules(toluene_path, molecule_idx=0))\n benzene_pos = utils.get_oe_mol_positions(utils.load_oe_molecules(benzene_path, molecule_idx=0))\n assert pipeline.compute_min_dist(toluene_pos, benzene_pos) < pipeline.SetupDatabase.CLASH_THRESHOLD\n\n exp_builder = ExperimentBuilder(yaml_content)\n\n for sys_id in [system_id + '_vacuum', system_id + '_PME']:\n system_dir = os.path.dirname(\n exp_builder._db.get_system(sys_id)[0].position_path)\n\n # Get positions of molecules in the final system\n prmtop = openmm.app.AmberPrmtopFile(os.path.join(system_dir, 'complex.prmtop'))\n inpcrd = openmm.app.AmberInpcrdFile(os.path.join(system_dir, 'complex.inpcrd'))\n positions = inpcrd.getPositions(asNumpy=True).value_in_unit(unit.angstrom)\n topography = Topography(prmtop.topology, ligand_atoms='resname TOL')\n benzene_pos2 = positions.take(topography.receptor_atoms, axis=0)\n toluene_pos2 = positions.take(topography.ligand_atoms, axis=0)\n # atom_indices = pipeline.find_components(prmtop.createSystem(), prmtop.topology, 'resname TOL')\n # benzene_pos2 = positions.take(atom_indices['receptor'], axis=0)\n # toluene_pos2 = positions.take(atom_indices['ligand'], axis=0)\n\n # Test that clashes are resolved in the system\n min_dist, max_dist = pipeline.compute_min_max_dist(toluene_pos2, benzene_pos2)\n assert min_dist >= pipeline.SetupDatabase.CLASH_THRESHOLD\n\n # For solvent we check that molecule is within the box\n if sys_id == system_id + '_PME':\n assert max_dist <= exp_builder._db.solvents['PME']['clearance'].value_in_unit(unit.angstrom)","def testMCShiftedLumiSplit(self):\n singleMCSubscription = self.generateFakeMCFile(firstLumi=345,\n lastLumi=345)\n splitter = SplitterFactory()\n jobFactory = splitter(singleMCSubscription)\n\n jobGroups = jobFactory(events_per_job=100,\n performance=self.performanceParams)\n self.assertEqual(len(jobGroups), 1,\n \"Error: JobFactory did not return one JobGroup\")\n self.assertEqual(len(jobGroups[0].jobs), 1,\n \"Error: JobFactory created %s jobs not one\"\n % len(jobGroups[0].jobs))\n job = jobGroups[0].jobs.pop()\n self.assertEqual(job[\"mask\"].getMaxEvents(), 100,\n \"Error: Job's max events is incorrect.\")\n self.assertEqual(job[\"mask\"][\"FirstEvent\"], 1,\n \"Error: Job's first event is incorrect.\")\n self.assertEqual(job[\"mask\"][\"FirstLumi\"], 345,\n \"Error: Job's first lumi is incorrect.\")\n\n singleMCSubscription = self.generateFakeMCFile(firstLumi=345,\n lastLumi=345)\n splitter = SplitterFactory()\n jobFactory = splitter(singleMCSubscription)\n jobGroups = jobFactory(events_per_job=1000,\n performance=self.performanceParams)\n self.assertEqual(len(jobGroups), 1,\n \"Error: JobFactory did not return one JobGroup\")\n self.assertEqual(len(jobGroups[0].jobs), 1,\n \"Error: JobFactory created %s jobs not one\"\n % len(jobGroups[0].jobs))\n job = jobGroups[0].jobs.pop()\n self.assertEqual(job[\"mask\"].getMaxEvents(), 100,\n \"Error: Job's max events is incorrect.\")\n self.assertEqual(job[\"mask\"][\"FirstEvent\"], 1,\n \"Error: Job's first event is incorrect.\")\n self.assertEqual(job[\"mask\"][\"FirstLumi\"], 345,\n \"Error: Job's first lumi is incorrect.\")\n\n singleMCSubscription = self.generateFakeMCFile(firstLumi=345,\n lastLumi=345)\n splitter = SplitterFactory()\n jobFactory = splitter(singleMCSubscription)\n jobGroups = jobFactory(events_per_job=99,\n performance=self.performanceParams)\n self.assertEqual(len(jobGroups), 1,\n \"Error: JobFactory did not return one JobGroup\")\n self.assertEqual(len(jobGroups[0].jobs), 2,\n \"Error: JobFactory created %s jobs not two\"\n % len(jobGroups[0].jobs))\n for job in jobGroups[0].jobs:\n firstJobCondition = (job[\"mask\"].getMaxEvents() == 99 and\n job[\"mask\"][\"FirstLumi\"] == 345 and\n job[\"mask\"][\"FirstEvent\"] == 1)\n secondJobCondition = (job[\"mask\"].getMaxEvents() == 1 and\n job[\"mask\"][\"FirstLumi\"] == 346 and\n job[\"mask\"][\"FirstEvent\"] == 100)\n self.assertTrue(firstJobCondition or secondJobCondition,\n \"Job mask: %s didn't pass neither of the conditions\"\n % job[\"mask\"])\n\n singleMCSubscription = self.generateFakeMCFile(firstLumi=345,\n lastLumi=345)\n splitter = SplitterFactory()\n jobFactory = splitter(singleMCSubscription)\n jobGroups = jobFactory(events_per_job=50,\n performance=self.performanceParams)\n self.assertEqual(len(jobGroups), 1,\n \"Error: JobFactory did not return one JobGroup\")\n self.assertEqual(len(jobGroups[0].jobs), 2,\n \"Error: JobFactory created %s jobs not two\"\n % len(jobGroups[0].jobs))\n for job in jobGroups[0].jobs:\n firstJobCondition = (job[\"mask\"].getMaxEvents() == 50 and\n job[\"mask\"][\"FirstLumi\"] == 345 and\n job[\"mask\"][\"FirstEvent\"] == 1)\n secondJobCondition = (job[\"mask\"].getMaxEvents() == 50 and\n job[\"mask\"][\"FirstLumi\"] == 346 and\n job[\"mask\"][\"FirstEvent\"] == 51)\n self.assertTrue(firstJobCondition or secondJobCondition,\n \"Job mask: %s didn't pass neither of the conditions\"\n % job[\"mask\"])","def run_multiple_test_cycles(self):\n # Perform as many cycles as required\n while self.args.repetitions >= 0:\n self.run_one_test_cycle()\n self.args.repetitions -= 1","def test_is_in_ring(self):\n molecule = Molecule.from_smiles(\"c1ccccc1\")\n\n for atom in molecule.atoms:\n if atom.atomic_number == 6:\n assert atom.is_in_ring()\n\n for bond in molecule.bonds:\n if 1 in (bond.atom1.atomic_number, bond.atom2.atomic_number):\n continue\n assert bond.is_in_ring()","def set_test_loop(self , _iter):\n\t\tself.__test=_iter","def test_stream_loop(self):\n chans, gains, scans, rate = (10,10,10,10), (1,2,4,5), 1024, 500\n v = [v[0] for v in self.l.stream_sync(\n channels=chans, gains=gains,\n num_scans=scans, rate=rate)]\n for vi in v:\n for r in vi:\n self.assertTrue(abs(r-2.5) < .1,\n \"%s should be cal, 2.5v\" % vi[0])","def PLAYERSELECTION_LOOP():\n pass","def run(self):\n self.cmdloop()","def run1():\n #Reseting motors\n ResetRobot.reset_wheel_motors()\n ResetRobot.reset_attachment_motors()\n CalibrateRobot.calibrate_gyro()\n\n #mission M01 and M02 - space travel and solar panel\n M01_M02()\n \n #Mission M05- Extraction \n M05_M14()\n\n #Back to base before Gerhard (Remove comment if necessary)\n return_to_base1()\n\n # Must delete for competition.. This is to set up forklift to repeat run.\n Robot.attachment_left.on_for_rotations(-100, 8) #Raises Forklift ","def test_set_molecule_error(self):\n mol = Molecule.from_smiles(\"CCO\")\n atom = Atom(6, 0, False)\n atom.molecule = mol\n with pytest.raises(AssertionError, match=\"already has an associated molecule\"):\n atom.molecule = mol","def test_react_parallel(self):\n import rmgpy.rmg.main\n rmgpy.rmg.main.maxproc = 2\n procnum = 2\n\n spc_a = Species().from_smiles('[OH]')\n spcs = [Species().from_smiles('CC'), Species().from_smiles('[CH3]')]\n spc_tuples = [((spc_a, spc), ['H_Abstraction']) for spc in spcs]\n\n reaction_list = list(itertools.chain.from_iterable(react(spc_tuples, procnum)))\n self.assertIsNotNone(reaction_list)\n self.assertEqual(len(reaction_list), 3)\n self.assertTrue(all([isinstance(rxn, TemplateReaction) for rxn in reaction_list]))\n\n # Reset module level maxproc back to default\n rmgpy.rmg.main.maxproc = 1","def test_is_multiplexed(self):\n run_dir = 'data/nanopore_data/run4/done_demuxing/20200104_1412_MN19414_AAU644_68125dc2'\n multiplexed_sample_sheet = 'data/nanopore_data/run4/done_demuxing/20200104_1412_MN19414_AAU644_68125dc2/SQK-LSK109_sample_sheet.csv'\n non_multiplexed_sample_sheet = 'data/nanopore_data/run3/demultiplexing/20200103_1412_MN19414_AAU643_68125dc2/SQK-LSK109_AAU643_sample_sheet.csv'\n multiplexed_run = MinIONqc(run_dir, multiplexed_sample_sheet, None)\n non_multiplexed_run = MinIONqc(run_dir, non_multiplexed_sample_sheet, None)\n self.assertTrue(multiplexed_run._is_multiplexed())\n self.assertFalse(non_multiplexed_run._is_multiplexed())","def temp_mainloop(self, cycles_to_respond=1000):\n\n if self.com_port_select.count() > 0:\n report = \"Begin measuring\"\n self.go_button.setEnabled(False) # don't allow to create new threads\n self.state_temp_loop(True)\n self.append_msg_box(report)\n\n while self.temp_loop_actiator:\n for num in range(self.com_port_select.count()):\n # self.MainWindow_exec_thread(lambda: self.sample_devices(cycles_to_respond, num))\n self.sample_devices(cycles_to_respond, num)\n self.temp_repr.plot_tc_temp(self.temp_log)\n timeo = float(self.timeout.text()) # timeout\n sleep(timeo)\n # -------- record data once in msg box --------\n\n self.go_button.setEnabled(True)\n self.led_light.setPixmap(QtGui.QPixmap(img[\"red_led\"]))\n else:\n self.append_msg_box(\"No device is connected\")","def test_validation_wrong_molecules():\n paths = examples_paths()\n paths['wrongformat'] = utils.get_data_filename(os.path.join('tests', 'data', 'README.md'))\n molecules = [\n {'antechamber': {'charge_method': 'bcc'}},\n {'filepath': paths['wrongformat']},\n {'name': 'p-xylene', 'antechamber': {'charge_method': 'bcc'}, 'unknown': 4},\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'}},\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'invalid'},\n 'antechamber': {'charge_method': None}},\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'},\n 'antechamber': {'charge_method': 'bcc'}},\n {'filepath': 'nonexistentfile.pdb', 'leap': {'parameters': 'leaprc.ff14SB'}},\n {'filepath': paths['toluene'], 'smiles': 'Cc1ccccc1'},\n {'filepath': paths['toluene'], 'strip_protons': True},\n {'filepath': paths['abl'], 'leap': {'parameters': 'oldff/leaprc.ff14SB'}, 'epik': {'select': 0}},\n {'name': 'toluene', 'epik': 0},\n {'name': 'toluene', 'epik': {'tautomerize': 6}},\n {'name': 'toluene', 'epik': {'extract_range': 1}},\n {'name': 'toluene', 'smiles': 'Cc1ccccc1'},\n {'name': 3},\n {'smiles': 'Cc1ccccc1', 'select': 1},\n {'name': 'Cc1ccccc1', 'select': 1},\n {'filepath': paths['abl'], 'leap': {'parameters': 'oldff/leaprc.ff14SB'}, 'select': 'notanoption'},\n {'filepath': paths['abl'], 'regions': 5},\n {'filepath': paths['abl'], 'regions': {'a_region': [-56, 5.23]}},\n {'filepath': paths['toluene'], 'leap': {'parameters': 'leaprc.gaff'}, 'strip_protons': True},\n ]\n for molecule in molecules:\n yield assert_raises, YamlParseError, ExperimentBuilder._validate_molecules, {'mol': molecule}","def exe_tests(self):\n self.rank = mpicom.rank()\n self.size = mpicom.size()\n if mpicom.parallel():\n self.test(\"libname\",os.path.split(mpicom.__file__)[1],\"mpicom.so\")\n else:\n self.test(\"libname\",os.path.split(mpicom.__file__)[1],\"mpistub.pyc\")\n self.test_broadcast()\n self.test_reduce()\n self.test_p2p()\n self.test_gather()\n self.test_scatter()\n #self.test_alltoall()","def add_control_loop(ui):\n\n loop = {}\n content_1 = content_fk_jac_loops(ui, \"loops_1\")\n content_2 = content_fk_jac_loops(ui, \"loops_2\")\n\n # Effector\n if ui.radioButton_loops_effector.isChecked():\n loop[\"type\"] = \"effector\"\n\n # Getting the current item\n ind_o = ui.comboBox_loops_origin.currentIndex()\n ind_d = ui.comboBox_loops_destination.currentIndex()\n if ind_o == ind_d:\n return\n names = [0, 0]\n ids = [0, 0]\n # Finding the corresponding object\n i = 0\n for _, _, node in robot_obj.tree:\n for od, ind in enumerate([ind_o, ind_d]):\n if i == ind:\n type_, nb = node.name.split('_')\n nb = int(nb)\n\n if type_ == 'joint':\n names[od] = robot_obj.joints[nb].name\n else:\n names[od] = robot_obj.links[nb].name\n\n ids[od] = names[od]\n continue\n i += 1\n if content_1 == \"INVALID\":\n return\n ids.append(content_1)\n loop[\"ids\"] = ids\n\n text = f\"{names[0]} ==> {names[1]} {parse_content(content_1)}\"\n\n # CoM\n else:\n loop[\"type\"] = \"com\"\n loop[\"ids\"] = [None, None, content_1]\n text = f\"Center of Mass {parse_content(content_1)}\"\n\n # Effector 2\n if ui.radioButton_loops_effector_2.isChecked():\n loop[\"type_2\"] = \"effector\"\n\n # Getting the current item\n ind_o = ui.comboBox_loops_origin_2.currentIndex()\n ind_d = ui.comboBox_loops_destination_2.currentIndex()\n if ind_o == ind_d:\n return\n names = [0, 0]\n ids = [0, 0]\n # Finding the corresponding object\n i = 0\n for _, _, node in robot_obj.tree:\n for od, ind in enumerate([ind_o, ind_d]):\n if i == ind:\n type_, nb = node.name.split('_')\n nb = int(nb)\n\n if type_ == 'joint':\n names[od] = robot_obj.joints[nb].name\n else:\n names[od] = robot_obj.links[nb].name\n\n ids[od] = names[od]\n continue\n i += 1\n if content_2 == \"INVALID\":\n return\n ids.append(content_2)\n loop[\"ids_2\"] = ids\n\n text += \" - \"\n text += f\"{names[0]} ==> {names[1]} {parse_content(content_2)}\"\n\n # CoM 2\n elif ui.radioButton_loops_com_2.isChecked():\n loop[\"type_2\"] = \"com\"\n loop[\"ids_2\"] = [None, None, content_2]\n text += f\" - Center of Mass {parse_content(content_2)}\"\n else:\n loop[\"type_2\"] = None\n loop[\"ids_2\"] = [None, None, None]\n\n loop[\"trajectory\"] = str(ui.comboBox_loops_trajectory.currentText())\n if ui.radioButton_loops_geometric.isChecked():\n loop[\"control_type\"] = \"geometric\"\n elif ui.radioButton_loops_positions.isChecked():\n loop[\"control_type\"] = \"positions\"\n else:\n loop[\"control_type\"] = \"velocities\"\n loop[\"coppelia\"] = ui.checkBox_loops_coppelia.isChecked()\n loop[\"constraints\"] = ui.checkBox_loops_constraints.isChecked()\n\n if loop in control_loops_list:\n return\n\n text += (f\" - {loop['trajectory']} - {loop['control_type']}\"\n f\"{' - Coppelia' if loop['coppelia'] else ''}\"\n f\"{' - Constraints' if loop['constraints'] else ''}\")\n\n ui.listWidget_loops.addItem(text)\n control_loops_list.append(loop)\n print(loop)","def test_chunk_pauli(self, method, device):\n opts_no_chunk = {\"fusion_enable\": False}\n opts_chunk = copy.copy(opts_no_chunk)\n opts_chunk[\"blocking_enable\"] = True\n opts_chunk[\"blocking_qubits\"] = 3\n\n backend = self.backend(method=method, device=device, **opts_chunk)\n backend_no_chunk = self.backend(method=method, device=device, **opts_no_chunk)\n\n shots = 100\n\n qr = QuantumRegister(5)\n cr = ClassicalRegister(5)\n regs = (qr, cr)\n circuit = QuantumCircuit(*regs)\n circuit.h(qr[0])\n circuit.h(qr[1])\n circuit.h(qr[2])\n circuit.h(qr[3])\n circuit.h(qr[4])\n circuit.pauli(\"YXZYX\", qr)\n circuit.measure_all()\n\n result = backend.run(circuit, shots=shots, memory=True).result()\n counts = result.get_counts(circuit)\n result_no_chunk = backend_no_chunk.run(circuit, shots=shots, memory=True).result()\n counts_no_chunk = result_no_chunk.get_counts(circuit)\n\n self.assertEqual(counts_no_chunk, counts)","def test_expand_molecules(self):\n yaml_content = \"\"\"\n ---\n molecules:\n rec:\n filepath: !Combinatorial [{}, {}]\n leap: {{parameters: oldff/leaprc.ff14SB}}\n lig:\n name: !Combinatorial [iupac1, iupac2]\n leap: {{parameters: leaprc.gaff}}\n epik:\n select: !Combinatorial [0, 2]\n multi:\n filepath: {}\n leap: {{parameters: oldff/leaprc.ff14SB}}\n select: all\n smiles:\n filepath: {}\n leap: {{parameters: leaprc.gaff}}\n select: all\n sdf:\n filepath: {}\n leap: {{parameters: leaprc.gaff}}\n select: all\n mol2:\n filepath: {}\n leap: {{parameters: leaprc.gaff}}\n select: all\n solvents:\n solv1:\n nonbonded_method: NoCutoff\n solv2:\n nonbonded_method: PME\n nonbonded_cutoff: 1*nanometer\n clearance: 10*angstroms\n protocols:{}\n systems:\n sys:\n receptor: !Combinatorial [rec, multi]\n ligand: lig\n solvent: !Combinatorial [solv1, solv2]\n experiments:\n system: sys\n protocol: absolute-binding\n \"\"\".format(self.sdf_path, self.mol2_path, self.pdb_path,\n self.smiles_path, self.sdf_path, self.mol2_path,\n indent(indent(standard_protocol)))\n yaml_content = textwrap.dedent(yaml_content)\n\n expected_content = \"\"\"\n ---\n molecules:\n rec_multisdf:\n filepath: {}\n leap: {{parameters: oldff/leaprc.ff14SB}}\n rec_multimol2:\n filepath: {}\n leap: {{parameters: oldff/leaprc.ff14SB}}\n lig_0_iupac1:\n name: iupac1\n leap: {{parameters: leaprc.gaff}}\n epik: {{select: 0}}\n lig_2_iupac1:\n name: iupac1\n leap: {{parameters: leaprc.gaff}}\n epik: {{select: 2}}\n lig_0_iupac2:\n name: iupac2\n leap: {{parameters: leaprc.gaff}}\n epik: {{select: 0}}\n lig_2_iupac2:\n name: iupac2\n leap: {{parameters: leaprc.gaff}}\n epik: {{select: 2}}\n multi_0:\n filepath: {}\n leap: {{parameters: oldff/leaprc.ff14SB}}\n select: 0\n multi_1:\n filepath: {}\n leap: {{parameters: oldff/leaprc.ff14SB}}\n select: 1\n smiles_0:\n filepath: {}\n leap: {{parameters: leaprc.gaff}}\n select: 0\n smiles_1:\n filepath: {}\n leap: {{parameters: leaprc.gaff}}\n select: 1\n sdf_0:\n filepath: {}\n leap: {{parameters: leaprc.gaff}}\n select: 0\n sdf_1:\n filepath: {}\n leap: {{parameters: leaprc.gaff}}\n select: 1\n mol2_0:\n filepath: {}\n leap: {{parameters: leaprc.gaff}}\n select: 0\n mol2_1:\n filepath: {}\n leap: {{parameters: leaprc.gaff}}\n select: 1\n solvents:\n solv1:\n nonbonded_method: NoCutoff\n solv2:\n nonbonded_method: PME\n nonbonded_cutoff: 1*nanometer\n clearance: 10*angstroms\n protocols:{}\n systems:\n sys:\n receptor: !Combinatorial [rec_multimol2, rec_multisdf, multi_0, multi_1]\n ligand: !Combinatorial [lig_0_iupac1, lig_0_iupac2, lig_2_iupac1, lig_2_iupac2]\n solvent: !Combinatorial [solv1, solv2]\n experiments:\n system: sys\n protocol: absolute-binding\n \"\"\".format(self.sdf_path, self.mol2_path, self.pdb_path, self.pdb_path,\n self.smiles_path, self.smiles_path, self.sdf_path, self.sdf_path,\n self.mol2_path, self.mol2_path, indent(standard_protocol))\n expected_content = textwrap.dedent(expected_content)\n\n raw = yank_load(yaml_content)\n expanded = ExperimentBuilder(yaml_content)._expand_molecules(raw)\n expected = yank_load(expected_content)\n assert expanded == expected, 'Expected:\\n{}\\n\\nExpanded:\\n{}'.format(\n expected['systems'], expanded['systems'])","def __init__(self, test_group):\n super().__init__(test_group=test_group, name='restart_test')\n\n self.add_step(\n SetupMesh(test_case=self, initial_condition='zero'))\n\n name = 'full_run'\n step = RunModel(test_case=self, name=name, subdir=name, ntasks=4,\n openmp_threads=1)\n # modify the namelist options and streams file\n step.add_namelist_file(\n 'compass.landice.tests.hydro_radial.restart_test',\n 'namelist.full', out_name='namelist.landice')\n step.add_streams_file(\n 'compass.landice.tests.hydro_radial.restart_test',\n 'streams.full', out_name='streams.landice')\n self.add_step(step)\n\n input_dir = name\n name = 'visualize_{}'.format(name)\n step = Visualize(test_case=self, name=name, subdir=name,\n input_dir=input_dir)\n self.add_step(step, run_by_default=False)\n\n name = 'restart_run'\n step = RunModel(test_case=self, name=name, subdir=name, ntasks=4,\n openmp_threads=1,\n suffixes=['landice', 'landice.rst'])\n\n # modify the namelist options and streams file\n step.add_namelist_file(\n 'compass.landice.tests.hydro_radial.restart_test',\n 'namelist.restart', out_name='namelist.landice')\n step.add_streams_file(\n 'compass.landice.tests.hydro_radial.restart_test',\n 'streams.restart', out_name='streams.landice')\n\n step.add_namelist_file(\n 'compass.landice.tests.hydro_radial.restart_test',\n 'namelist.restart.rst', out_name='namelist.landice.rst')\n step.add_streams_file(\n 'compass.landice.tests.hydro_radial.restart_test',\n 'streams.restart.rst', out_name='streams.landice.rst')\n self.add_step(step)\n\n input_dir = name\n name = 'visualize_{}'.format(name)\n step = Visualize(test_case=self, name=name, subdir=name,\n input_dir=input_dir)\n self.add_step(step, run_by_default=False)","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def molecule(\n context, command, scenario=None, driver='docker'\n):\n if driver == \"docker\":\n raise Exception(\n \"Can't run tests under Docker as 'timedatectl status' command will fail\\n\"\n \"(see https://stackoverflow.com/a/46837044 for details)\"\n )\n test_utils.run_molecule(context, command, scenario, driver)","def test_motor_error(self):\n # reproducible arbitrariness\n np.random.seed(12325)\n\n nsteps = 10\n nchan = 3\n tmax = nsteps*self.dt\n sequence = np.random.randn(nsteps, self.N)\n\n target = np.random.randn(nchan, nsteps)\n controller = LinearController(self.G, target, tau=None)\n controller.W = np.random.randn(*controller.W.shape)\n\n self.G.out_fct = lambda i: sequence[i]\n\n class MotorErrorGrabber(object):\n def __init__(self, target):\n self.target = target\n self.order = 10\n \n def prepare(self, tmax, dt):\n nsteps = int_r(tmax/dt)\n self.motor_error = np.zeros((nsteps, self.target.N))\n\n def evolve(self, t, dt):\n i = int_r(t/dt)\n self.motor_error[i, :] = self.target.get_motor_error()\n\n M = MotorErrorGrabber(controller)\n M1 = simulation.StateMonitor(controller, 'out')\n\n sim = simulation.Simulation(self.G, controller, M, M1, dt=self.dt)\n sim.run(tmax)\n\n for i in xrange(int_r(tmax/self.dt)):\n diff = M1.out[:, i] - target[:, i]\n self.assertTrue(np.allclose(M.motor_error[i], diff))","def test_integration(self):\n\n m = 5 # number of wires in A\n M = 2**m\n\n xmax = np.pi # bound to region [-pi, pi]\n xs = np.linspace(-xmax, xmax, M)\n\n probs = np.array([norm().pdf(x) for x in xs])\n probs /= np.sum(probs)\n\n func = lambda i: np.sin(xs[i]) ** 2\n r_rotations = np.array([2 * np.arcsin(np.sqrt(func(i))) for i in range(M)])\n\n A_wires = [0, \"a\", -1.1, -10, \"bbb\"]\n target_wire = \"Ancilla\"\n wires = A_wires + [target_wire]\n estimation_wires = [\"bob\", -3, 42, \"penny\", \"lane\"]\n\n def fn():\n qml.templates.MottonenStatePreparation(np.sqrt(probs), wires=A_wires)\n r_unitary(qml.RY, r_rotations, control_wires=A_wires[::-1], target_wire=target_wire)\n\n qmc_circuit = qml.quantum_monte_carlo(\n fn, wires=wires, target_wire=target_wire, estimation_wires=estimation_wires\n )\n\n with qml.queuing.AnnotatedQueue() as q:\n qmc_circuit()\n qml.probs(estimation_wires)\n\n tape = qml.tape.QuantumScript.from_queue(q)\n tape = tape.expand(depth=2)\n\n assert all(\n not isinstance(op, (qml.MultiControlledX, qml.templates.QFT, qml.tape.QuantumScript))\n for op in tape.operations\n )\n\n dev = qml.device(\"default.qubit\", wires=wires + estimation_wires)\n res = dev.execute(tape)\n\n @qml.qnode(dev)\n def circuit():\n qml.templates.QuantumMonteCarlo(\n probs, func, target_wires=wires, estimation_wires=estimation_wires\n )\n return qml.probs(estimation_wires)\n\n res_expected = circuit()\n assert np.allclose(res, res_expected)","def test_template_forloop(self):\n print \"Running: %s - %s\" % (self.id(), self.shortDescription())\n # compare sequence items\n for i in range(0, 3):\n input_item = g.config['templates']['sequence'][i]\n output_item = self.output_config['out_templates']['sequence'][i]\n\n self.assertEqual(input_item, output_item,\n 'sequence items (%i) do not match' % i)","def test_interaction_on_master(self, admin_remote):\n timeout = 1 # minute\n sleep_between_restart = 1 # minute\n\n # Stop rabbit and check that there are no errors in output\n self.control_rabbit_service(admin_remote, 'stop')\n\n # Wait till rabbitmq-server has \"Status: \"Exited.\"\" string\n self.wait_rabbit_became_exited(admin_remote, timeout)\n sleep(60 * sleep_between_restart)\n\n # Rabbit start-stops with check that there are no errors in output\n for i in range(5):\n self.control_rabbit_service(admin_remote, 'start')\n sleep(60 * sleep_between_restart)\n self.control_rabbit_service(admin_remote, 'stop')\n\n # Wait till rabbitmq-server has \"Active: active (running)\" string\n self.control_rabbit_service(admin_remote, 'start')\n self.wait_rabbit_became_active(admin_remote, timeout)","def loop_context():\n loop = setup_test_loop()\n yield loop\n # teardown_test_loop(loop)","def watch_loop(self):\n # Double threaded function that allows to stop the loop mid execution\n def repeatIt():\n # reset UI and flag before starting loop\n self.resetLabels()\n self.reset_scrollbar()\n # enable stop button\n self.btnStop.config(state=\"normal\")\n # disable button while loop is running\n self.btnStart.config(state=\"disabled\")\n self.txtLoop.config(state=\"disabled\", textvariable=self.loopCounterUI)\n self.labelLoop.config(text=\"Loop Count: \")\n\n while self.loopCount.get() > 0:\n # move scrollbar to bottom\n self.testCanvas.yview_moveto(0)\n # count the loop\n self.loopCounterUI.set(self.loopCounterUI.get() + 1)\n\n # Run the test cases\n self.runThis()\n\n # Below are just to reset the UI\n if not self.stopLoop:\n print(\"loop not stopped so proceed\")\n # let user know script is stopping\n x = Label(\n self.testFrame, text=f'End of Loop',\n background=self.bgChooser(),\n foreground=\"#630984\",\n font=self.boldFont)\n x.pack(fill=X)\n # flag gor BG and labels\n self.bgCounter += 1\n self.LabelLists.append(x)\n # allow window to catch up\n self.tkRoot.update()\n self.update_scrollbar()\n else:\n print(\"loop has been stopped so not gonna print End of Loop\")\n\n # pause before restarting loop\n self.loopCount.set(self.loopCount.get()-1)\n time.sleep(1)\n\n # disable stop button\n self.btnStop.config(state=\"disabled\")\n # re-enable button after loop is done\n self.btnStart.config(state=\"normal\")\n self.txtLoop.config(state=\"normal\", textvariable=self.loopCount)\n self.labelLoop.config(text=\"Enter Loop Count: \")\n # self.testCanvas.yview_moveto(0)\n # Let user know the script is done\n if not self.stopLoop:\n # loop did not stopped\n x = Label(\n self.testFrame, text=f'Test is done!',\n background=self.bgChooser(),\n foreground=\"#057224\",\n font=self.boldFont)\n x.pack(fill=X)\n self.bgCounter += 1\n else:\n x = Label(\n self.testFrame, text=f'Test stopped!',\n background=self.bgChooser(),\n foreground=\"#057224\",\n font=self.boldFont)\n x.pack(fill=X)\n self.bgCounter += 1\n self.btnStart.config(state=\"normal\")\n self.txtLoop.config(state=\"normal\", textvariable=self.loopCount)\n self.labelLoop.config(text=\"Enter Loop count: \")\n self.loopCount.set(50000)\n self.LabelLists.append(x)\n # allow window to catch up\n self.tkRoot.update()\n self.update_scrollbar()\n thread = threading.Thread(target=repeatIt)\n thread.start()"],"string":"[\n \"def test_molecule_loop_no_selection(self):\\n\\n # Molecule data.\\n name = ['Ap4Aase', 'RNA']\\n\\n # Loop over the molecules.\\n i = 0\\n for mol in mol_res_spin.molecule_loop():\\n # Test the molecule names.\\n self.assertEqual(mol.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)\",\n \"def test_molecule_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the molecules.\\n i = 0\\n for molecule in mol_res_spin.molecule_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_spin_loop(self):\\n\\n # Spin data.\\n select = [1, 0]\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, 'N5')\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 2)\",\n \"def test_molecule_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for molecule in mol_res_spin.molecule_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_spin_loop_multiatom(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_spin_loop_no_selection(self):\\n\\n # Spin data.\\n select = [0, 1, 0, 0, 1, 1, 0, 1]\\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 8)\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def test_residue_loop(self):\\n\\n # Loop over the residues.\\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\\n # Test the selection.\\n self.assertEqual(res.num, 2)\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)\",\n \"def test_spin_loop_wildcard(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N*'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_multi_molecules_cycle(self, multi_mol_system_regular, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n expected = expected * 3\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_regular)\\n found = self.sequence_from_system(multi_mol_system_regular, \\\"test\\\")\\n assert found == expected\",\n \"def test_multi_molecules_cycle_one(self, multi_mol_system_irregular):\\n sequence = \\\"A\\\"\\n expected = [sequence] * (15 * 3)\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_irregular)\\n found = self.sequence_from_system(multi_mol_system_irregular, \\\"test\\\")\\n assert found == expected\",\n \"def test_return_molecule(self):\\n\\n # Ask for a few molecules.\\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\\n\\n # Test the data of molecule 1.\\n self.assertEqual(mol1.name, 'Ap4Aase')\\n\\n # Test the data of molecule 2.\\n self.assertEqual(mol2.name, 'RNA')\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_run_molecule(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_run_molecule_not_selected(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\", sequence, molecule_selector=lambda mol: False\\n )\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert vermouth.utils.are_all_equal(found)\\n assert found[0] is None\",\n \"def test_residue_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for residue in mol_res_spin.residue_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_single_molecules_cycle_one(self, single_mol_system):\\n sequence = \\\"A\\\"\\n expected = [sequence] * (5 * 3)\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def test_spin_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for spin in mol_res_spin.spin_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_run_loop_success(self):\\n found = False\\n pyint = Interpreter(limit=15)\\n try:\\n pyint.run(code=BF_CODE_LOOP_TWICE)\\n except SystemExit: \\n found = True\\n self.assertFalse(found)\",\n \"def test_single_molecule(self, single_mol_system, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def run_test(dut):\\n tb = MyTB(dut,int(os.environ['SIM_LEN']))\\n cocotb.fork(Clock(dut.clk, 10).start())\\n stim_thread = cocotb.fork(tb.stim_mux())\\n read_thread = cocotb.fork(tb.read_mux())\\n yield stim_thread.join()\\n yield read_thread.join()\\n if tb.sim_mux_sel != tb.py_sel_input:\\n raise TestFailure(\\\"Mux selection failed.\\\")\\n else:\\n raise TestSuccess(\\\"Mux sel successful\\\")\",\n \"def test_return_molecule_pipe_fail(self):\\n\\n # Try to get a molecule from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')\",\n \"def test_simulationRun(self):\\n self.opt = { 'temperature' : 300.0, 'friction' : 1, 'dt' : 0.00002,\\n 'nIter' : 2, 'nstepsNC' : 2, 'nstepsMD' : 1, 'nprop' : 1,\\n 'nonbondedMethod' : 'NoCutoff', 'constraints': 'HBonds',\\n 'trajectory_interval' : 1, 'reporter_interval' : 1,\\n 'outfname' : 'mc-test',\\n 'platform' : None,\\n 'constraints' : 'HBonds',\\n 'mc_per_iter' : 2 }\\n\\n structure = self.full_struct\\n class SetRotationMove(RandomLigandRotationMove):\\n def __init__(self, structure, resname='LIG'):\\n super(SetRotationMove, self).__init__(structure, resname)\\n\\n def move(self, context):\\n \\\"\\\"\\\"Function that performs a random rotation about the\\n center of mass of the ligand.\\n \\\"\\\"\\\"\\n #TODO: check if we need to deepcopy\\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\\n\\n self.positions = positions[self.atom_indices]\\n self.center_of_mass = self.getCenterOfMass(self.positions, self.masses)\\n reduced_pos = self.positions - self.center_of_mass\\n\\n # Define random rotational move on the ligand\\n #set rotation so that test is reproducible\\n set_rotation_matrix = np.array([[-0.62297988, -0.17349253, 0.7627558 ],\\n [ 0.55082352, -0.78964857, 0.27027502],\\n [ 0.55541834, 0.58851973, 0.58749893]])\\n\\n\\n #set_rotation_matrix = np.array([[1, 0, 0],\\n # [0, 1, 0],\\n # [0, 0, 1]])\\n\\n #multiply lig coordinates by rot matrix and add back COM translation from origin\\n rot_move = np.dot(reduced_pos, set_rotation_matrix) * positions.unit + self.center_of_mass\\n\\n # Update ligand positions in nc_sim\\n for index, atomidx in enumerate(self.atom_indices):\\n positions[atomidx] = rot_move[index]\\n context.setPositions(positions)\\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\\n self.positions = positions[self.atom_indices]\\n return context\\n\\n\\n self.model = SetRotationMove(structure, resname='ALA')\\n #self.model = RandomLigandRotationMove(structure, resname='ALA')\\n\\n self.model.atom_indices = range(22)\\n self.model.topology = structure[self.model.atom_indices].topology\\n self.model.positions = structure[self.model.atom_indices].positions\\n self.model.calculateProperties()\\n\\n self.mover = MoveEngine(self.model)\\n #Initialize the SimulationFactory object\\n sims = SimulationFactory(structure, self.mover, **self.opt)\\n #print(sims)\\n system = sims.generateSystem(structure, **self.opt)\\n simdict = sims.createSimulationSet()\\n alch_system = sims.generateAlchSystem(system, self.model.atom_indices)\\n self.nc_sim = sims.generateSimFromStruct(structure, self.mover, alch_system, ncmc=True, **self.opt)\\n self.model.calculateProperties()\\n self.initial_positions = self.nc_sim.context.getState(getPositions=True).getPositions(asNumpy=True)\\n mc_sim = Simulation(sims, self.mover, **self.opt)\\n #monkeypatch to access acceptance value\\n def nacceptRejectMC(self, temperature=300, **opt):\\n \\\"\\\"\\\"Function that chooses to accept or reject the proposed move.\\n \\\"\\\"\\\"\\n md_state0 = self.current_state['md']['state0']\\n md_state1 = self.current_state['md']['state1']\\n log_mc = (md_state1['potential_energy'] - md_state0['potential_energy']) * (-1.0/self.nc_sim.context._integrator.kT)\\n randnum = math.log(np.random.random())\\n\\n if log_mc > randnum:\\n self.accept += 1\\n print('MC MOVE ACCEPTED: log_mc {} > randnum {}'.format(log_mc, randnum) )\\n self.md_sim.context.setPositions(md_state1['positions'])\\n else:\\n self.reject += 1\\n print('MC MOVE REJECTED: log_mc {} < {}'.format(log_mc, randnum) )\\n self.md_sim.context.setPositions(md_state0['positions'])\\n self.log_mc = log_mc\\n self.md_sim.context.setVelocitiesToTemperature(self.opt['temperature'])\\n mc_sim.acceptRejectMC = nacceptRejectMC\\n nacceptRejectMC.__get__(mc_sim)\\n mc_sim.acceptRejectMC = types.MethodType(nacceptRejectMC, mc_sim)\\n mc_sim.runMC(self.opt['nIter'])\\n #get log acceptance\\n print(mc_sim.log_mc)\\n #if mc is working, should be around -24.1\\n assert mc_sim.log_mc <= -23.8 and mc_sim.log_mc >= -24.3\",\n \"def test_for_loop(self, modes, parse_input_mocked_metadata):\\n bb = parse_input_mocked_metadata(\\n \\\"for int m in {}\\\\n\\\\tMeasureFock() | m\\\".format(modes)\\n )\\n assert np.all(\\n bb._forvar[\\\"m\\\"] == np.array(modes)\\n )\\n assert bb.operations == [\\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[0]]},\\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[1]]},\\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[2]]}\\n ]\",\n \"def test_select_pdb_conformation(self):\\n with mmtools.utils.temporary_directory() as tmp_dir:\\n yaml_content = \\\"\\\"\\\"\\n ---\\n options:\\n output_dir: {}\\n setup_dir: .\\n molecules:\\n selected:\\n filepath: {}\\n leap: {{parameters: oldff/leaprc.ff14SB}}\\n select: 1\\n \\\"\\\"\\\".format(tmp_dir, self.pdb_path)\\n yaml_content = textwrap.dedent(yaml_content)\\n exp_builder = ExperimentBuilder(yaml_content)\\n\\n # The molecule now is neither set up nor processed\\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\\n assert is_setup is False\\n assert is_processed is False\\n\\n # The setup of the molecule must isolate the frame in a single-frame PDB\\n exp_builder._db._setup_molecules('selected')\\n selected_pdb_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\\n 'selected', 'selected.pdb')\\n assert os.path.exists(os.path.join(selected_pdb_path))\\n assert os.path.getsize(os.path.join(selected_pdb_path)) > 0\\n\\n # The positions must be the ones of the second frame\\n selected_pdb = PDBFile(selected_pdb_path)\\n selected_pos = selected_pdb.getPositions(asNumpy=True)\\n second_pos = PDBFile(self.pdb_path).getPositions(asNumpy=True, frame=1)\\n assert selected_pdb.getNumFrames() == 1\\n assert (selected_pos == second_pos).all()\\n\\n # The description of the molecule is now updated\\n assert os.path.normpath(exp_builder._db.molecules['selected']['filepath']) == selected_pdb_path\\n\\n # The molecule now both set up and processed\\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\\n assert is_setup is True\\n assert is_processed is True\\n\\n # A new instance of ExperimentBuilder is able to resume with correct molecule\\n exp_builder = ExperimentBuilder(yaml_content)\\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\\n assert is_setup is True\\n assert is_processed is True\",\n \"def test_boolean_and_selection(self):\\n\\n # The selection loop:\\n sel = list(mol_res_spin.residue_loop(\\\"#Ap4Aase:4 & :Pro\\\"))\\n\\n # Test:\\n self.assertEqual(len(sel), 1)\\n for res in sel:\\n self.assert_(res.name == \\\"Pro\\\" and res.num == 4)\",\n \"def ROOMSELECTION_LOOP():\\n pass\",\n \"def loop(self):\\n raise NotImplementedError()\",\n \"def MULTIPLAYER_LOOP():\\n pass\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_boolean_complex_selection(self):\\n\\n # The residue selection loop.\\n sel = list(mol_res_spin.residue_loop(\\\"#Ap4Aase:4 & :Pro | #RNA\\\"))\\n\\n # Residue names and numbers.\\n names = ['Pro', None, None]\\n numbers = [4, -5, -4]\\n\\n # The residues.\\n self.assertEqual(len(sel), 3)\\n for i in range(3):\\n self.assertEqual(sel[i].name, names[i])\\n self.assertEqual(sel[i].num, numbers[i])\",\n \"def test_control_loop_example():\\n example.control.print_error_measurement()\\n matplotlib.use('agg')\\n example.control.visualise_error_measurement(fig_file='cs_compare.pdf')\\n assert path.isfile('cs_compare.pdf')\\n example.control.sil_comparison()\",\n \"def loop(self):\\n pass\",\n \"def test_set_molecule(self):\\n mol = Molecule.from_smiles(\\\"CCO\\\")\\n atom = Atom(6, 0, False)\\n atom.molecule = mol\",\n \"def test_select_sdf_mol2(self):\\n with mmtools.utils.temporary_directory() as tmp_dir:\\n yaml_content = \\\"\\\"\\\"\\n ---\\n options:\\n output_dir: {}\\n setup_dir: .\\n molecules:\\n sdf_0:\\n filepath: {}\\n antechamber: {{charge_method: bcc}}\\n leap: {{parameters: leaprc.gaff}}\\n select: 0\\n sdf_1:\\n filepath: {}\\n antechamber: {{charge_method: bcc}}\\n leap: {{parameters: leaprc.gaff}}\\n select: 1\\n mol2_0:\\n filepath: {}\\n antechamber: {{charge_method: bcc}}\\n leap: {{parameters: leaprc.gaff}}\\n select: 0\\n mol2_1:\\n filepath: {}\\n antechamber: {{charge_method: bcc}}\\n leap: {{parameters: leaprc.gaff}}\\n select: 1\\n \\\"\\\"\\\".format(tmp_dir, self.sdf_path, self.sdf_path, self.mol2_path, self.mol2_path)\\n yaml_content = textwrap.dedent(yaml_content)\\n exp_builder = ExperimentBuilder(yaml_content)\\n\\n for extension in ['sdf', 'mol2']:\\n multi_path = getattr(self, extension + '_path')\\n for model_idx in [0, 1]:\\n mol_id = extension + '_' + str(model_idx)\\n\\n # The molecule now is neither set up nor processed\\n is_setup, is_processed = exp_builder._db.is_molecule_setup(mol_id)\\n assert is_setup is False\\n assert is_processed is False\\n\\n exp_builder._db._setup_molecules(mol_id)\\n\\n # The setup of the molecule must isolate the frame in a single-frame PDB\\n single_mol_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\\n mol_id, mol_id + '.' + extension)\\n assert os.path.exists(os.path.join(single_mol_path))\\n assert os.path.getsize(os.path.join(single_mol_path)) > 0\\n if extension == 'mol2':\\n # OpenEye loses the resname when writing a mol2 file.\\n mol2_file = utils.Mol2File(single_mol_path)\\n assert len(list(mol2_file.resnames)) == 1\\n assert mol2_file.resname != '<0>'\\n\\n # sdf files must be converted to mol2 to be fed to antechamber\\n if extension == 'sdf':\\n single_mol_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\\n mol_id, mol_id + '.mol2')\\n assert os.path.exists(os.path.join(single_mol_path))\\n assert os.path.getsize(os.path.join(single_mol_path)) > 0\\n\\n # Check antechamber parametrization\\n single_mol_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\\n mol_id, mol_id + '.gaff.mol2')\\n assert os.path.exists(os.path.join(single_mol_path))\\n assert os.path.getsize(os.path.join(single_mol_path)) > 0\\n\\n # The positions must be approximately correct (antechamber move the molecule)\\n selected_oe_mol = utils.load_oe_molecules(single_mol_path, molecule_idx=0)\\n selected_pos = utils.get_oe_mol_positions(selected_oe_mol)\\n second_oe_mol = utils.load_oe_molecules(multi_path, molecule_idx=model_idx)\\n second_pos = utils.get_oe_mol_positions(second_oe_mol)\\n assert selected_oe_mol.NumConfs() == 1\\n assert np.allclose(selected_pos, second_pos, atol=1e-1)\\n\\n # The molecule now both set up and processed\\n is_setup, is_processed = exp_builder._db.is_molecule_setup(mol_id)\\n assert is_setup is True\\n assert is_processed is True\\n\\n # A new instance of ExperimentBuilder is able to resume with correct molecule\\n exp_builder = ExperimentBuilder(yaml_content)\\n is_setup, is_processed = exp_builder._db.is_molecule_setup(mol_id)\\n assert is_setup is True\\n assert is_processed is True\",\n \"def test_compute_partial_charges(self):\\n # TODO: Test only one molecule for speed?\\n # TODO: Do we need to deepcopy each molecule, or is setUp called separately for each test method?\\n import numpy as np\\n from simtk import unit\\n\\n # Do not modify original molecules.\\n molecules = copy.deepcopy(mini_drug_bank())\\n\\n # Test a single toolkit at a time\\n # Removed ['amber', 'amberff94'] from OE list, as those won't find the residue types they're expecting\\n toolkit_to_charge_method = {\\n OpenEyeToolkitWrapper: [\\n \\\"mmff\\\",\\n \\\"mmff94\\\",\\n \\\"am1bcc\\\",\\n \\\"am1bccnosymspt\\\",\\n \\\"am1bccelf10\\\",\\n ],\\n AmberToolsToolkitWrapper: [\\\"bcc\\\", \\\"gas\\\", \\\"mul\\\"],\\n }\\n\\n manual_skips = []\\n\\n manual_skips.append(\\n \\\"ZINC1564378\\\"\\n ) # Warning: OEMMFF94Charges: assigning OEMMFFAtomTypes failed on mol .\\n manual_skips.append(\\n \\\"ZINC00265517\\\"\\n ) # Warning: OEMMFF94Charges: assigning OEMMFFAtomTypes failed on mol .\\n\\n for toolkit in list(toolkit_to_charge_method.keys()):\\n toolkit_registry = ToolkitRegistry(toolkit_precedence=[toolkit])\\n for charge_model in toolkit_to_charge_method[toolkit]:\\n c = 0\\n for molecule in molecules[:1]: # Just test first molecule to save time\\n c += 1\\n if molecule.name in manual_skips: # Manual skips, hopefully rare\\n continue\\n molecule.compute_partial_charges(\\n charge_model=charge_model, toolkit_registry=toolkit_registry\\n )\\n charges1 = molecule._partial_charges\\n # Make sure everything isn't 0s\\n assert (abs(charges1 / unit.elementary_charge) > 0.01).any()\\n # Check total charge\\n charges_sum_unitless = charges1.sum() / unit.elementary_charge\\n # if abs(charges_sum_unitless - float(molecule.total_charge)) > 0.0001:\\n # print('c {} molecule {} charge_sum {} molecule.total_charge {}'.format(c, molecule.name,\\n # charges_sum_unitless,\\n # molecule.total_charge))\\n # assert_almost_equal(charges_sum_unitless, molecule.total_charge, decimal=4)\\n\\n # Call should be faster second time due to caching\\n # TODO: Implement caching\\n molecule.compute_partial_charges(\\n charge_model=charge_model, toolkit_registry=toolkit_registry\\n )\\n charges2 = molecule._partial_charges\\n assert np.allclose(charges1, charges2, atol=0.002)\",\n \"def test_run_loop_exc(self):\\n with self.assertRaises(ExecutionException):\\n pyint = Interpreter(limit=1)\\n pyint.run(code=BF_CODE_LOOP_TWICE)\",\n \"def test_circularloop(self):\\n cmd = f\\\"{SRC_LISTER} -i {PWD}/main\\\"\\n with subprocess.Popen(\\n shlex.split(cmd), stdout=subprocess.PIPE, stderr=subprocess.PIPE\\n ) as proc:\\n try:\\n out, err = proc.communicate(timeout=5)\\n assert len(err.strip()) > 0, \\\"Expected a circular reference error\\\"\\n except subprocess.TimeoutExpired as te:\\n print(\\\"Unexpected parser timeout during infinite loop test\\\")\",\n \"def runSingleTest(cube, instructions, interval):\\n root = Tk()\\n interface = Interface(root, cube)\\n root.after(0, interface.runInstructions, instructions, interval)\\n root.mainloop()\",\n \"def loop_run(self, loops):\\n self.loop_seek(self.num_loops + loops)\",\n \"def test_multi_molecules_diff_sizes(self, multi_mol_system_irregular, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_irregular)\\n found = self.sequence_from_system(multi_mol_system_irregular, \\\"test\\\")\\n assert found == expected\",\n \"def run_one_test_cycle(self):\\n logging.info(\\n \\\"{0} operations remaining: {1}\\\".format(\\n self.args.pm_operation, self.args.repetitions\\n )\\n )\\n\\n self.check_last_cycle_duration()\\n if self.args.repetitions > 0:\\n self.run_pm_command()\\n else:\\n self.summary()\",\n \"def algorithm_loop(self):\",\n \"def _run_cycle(self):\\n pass\",\n \"def do_simulation_loop(self) -> tuple[bool, bool]:\\n running, reset = True, False\\n for event in pygame.event.get():\\n if check_for_quit(event):\\n running = False\\n elif check_for_reset(event):\\n running = False\\n reset = True\\n self.simulation.do_step()\\n self.update_visualization()\\n self.simple_pygame.loop()\\n return running, reset\",\n \"def runMasking(self,roiNode,inputVolumes,inPlace):\\n\\n self.delayDisplay('Running the algorithm')\\n\\n for vol in inputVolumes:\\n self.maskVolume(vol, roiNode, inPlace)\\n\\n return True\\n\\n self.delayDisplay('Running the aglorithm')\",\n \"async def test_routine(self):\\n print('Running test routine...')\\n print('Waiting for axes to initialize...')\\n await self.robot.wait_until_initialized()\\n print('Synchronizing robot state with peripheral...')\\n await self.robot.synchronize_values()\\n print('Loading calibration data...')\\n await self.robot.load_calibrations()\\n await self.robot.go_to_alignment_hole()\\n\\n print('Starting 96-well plate test...')\\n await self.robot.go_to_96_well_plate(1, 'a')\\n await self.robot.dispense('96-well plate', 'far above')\\n for height in ['bottom', 'low', 'mid', 'high', 'top', 'above', 'far above']:\\n print('Testing with height {}...'.format(height))\\n for (row, volume) in [('a', 20), ('b', 30), ('c', 40), ('d', 50), ('e', 100)]:\\n print(\\n ' Testing precise with row {} and volume {} mL...'\\n .format(row, volume)\\n )\\n await self.test_individual_precise(row, height, volume / 1000)\\n await self.robot.dispense('96-well plate', height)\\n for (row, volume) in [\\n ('f', 100), ('g', 150), ('h', 200), ('a', 300), ('b', 400),\\n ('c', 500), ('d', 600), ('e', 700), ('g', 800), ('h', 900)\\n ]:\\n print(\\n ' Testing rough with row {} and volume {} mL...'\\n .format(row, volume / 1000)\\n )\\n await self.test_individual_rough(row, height, volume / 1000)\\n await self.robot.z.go_to_high_end_position()\\n await self.robot.y.go_to_low_end_position()\\n\\n print(batch.OUTPUT_FOOTER)\\n print('Quitting...')\",\n \"def test_omp(self):\\n ex = self.ex\\n j = self.j\\n\\n nreps = random.randint(1, 10)\\n ncalls = random.randint(1, 10)\\n ex.calls = ncalls * [ex.call]\\n ex.nreps = nreps\\n ex.calls_parallel = True\\n\\n cmds = ex.generate_cmds()\\n\\n self.assertEqual(cmds.count([\\\"{omp\\\"]), nreps)\\n self.assertEqual(cmds.count([\\\"}\\\"]), nreps)\\n\\n lensumrange = random.randint(1, 10)\\n ex.sumrange = [j, range(lensumrange)]\\n ex.sumrange_parallel = True\\n\\n cmds = ex.generate_cmds()\\n\\n self.assertEqual(cmds.count([\\\"{omp\\\"]), nreps)\\n self.assertEqual(cmds.count([\\\"}\\\"]), nreps)\",\n \"def runtest(self):\\n folder = self.path.parent\\n folders = folder.parts\\n cwd = os.path.abspath(os.path.join(folder, \\\"../..\\\"))\\n scenario = folders[-1]\\n # role = folders[-3] # noqa\\n\\n cmd = [sys.executable, \\\"-m\\\", \\\"molecule\\\"]\\n if self.config.option.molecule_base_config:\\n cmd.extend((\\\"--base-config\\\", self.config.option.molecule_base_config))\\n if self.config.option.skip_no_git_change:\\n try:\\n with subprocess.Popen(\\n [\\\"git\\\", \\\"diff\\\", self.config.option.skip_no_git_change, \\\"--\\\", \\\"./\\\"],\\n cwd=cwd,\\n stdout=subprocess.PIPE,\\n stderr=subprocess.STDOUT,\\n universal_newlines=True,\\n ) as proc:\\n proc.wait()\\n if len(proc.stdout.readlines()) == 0:\\n pytest.skip(\\\"No change in role\\\")\\n except Exception as exc: # pylint: disable=broad-except\\n pytest.fail(\\\"Error checking git diff. Error was:\\\" + str(exc))\\n\\n cmd.extend((self.name, \\\"-s\\\", scenario))\\n # We append the additional options to molecule call, allowing user to\\n # control how molecule is called by pytest-molecule\\n opts = os.environ.get(\\\"MOLECULE_OPTS\\\")\\n if opts:\\n cmd.extend(shlex.split(opts))\\n\\n print(f\\\"running: {' '.join(quote(arg) for arg in cmd)} (from {cwd})\\\")\\n try:\\n # Workaround for STDOUT/STDERR line ordering issue:\\n # https://github.com/pytest-dev/pytest/issues/5449\\n\\n with subprocess.Popen(\\n cmd,\\n cwd=cwd,\\n stdout=subprocess.PIPE,\\n stderr=subprocess.STDOUT,\\n universal_newlines=True,\\n ) as proc:\\n for line in proc.stdout:\\n print(line, end=\\\"\\\")\\n proc.wait()\\n if proc.returncode != 0:\\n pytest.fail(\\n f\\\"Error code {proc.returncode} returned by: {' '.join(cmd)}\\\",\\n pytrace=False,\\n )\\n except Exception as exc: # pylint: disable=broad-except\\n pytest.fail(f\\\"Exception {exc} returned by: {' '.join(cmd)}\\\", pytrace=False)\",\n \"def _run(self):\\n while(self._loop):\\n pass\",\n \"async def main(dut):\\n # Create a 10us period clock on port clk\\n clock = Clock(dut.clk_i, 10, units=\\\"us\\\")\\n cocotb.fork(clock.start())\\n\\n # Reset system\\n await FallingEdge(dut.clk_i)\\n dut.rst_n_i <= 0\\n dut.en_i <= 0\\n dut.data_i <= 0\\n dut.valid_i <= 0\\n\\n # reset\\n await FallingEdge(dut.clk_i)\\n dut.rst_n_i <= 1\\n\\n # test 1\\n dut.en_i <= 1\\n x, y = get_test_vector()\\n cocotb.fork(write_input(dut, x))\\n await check_output(dut, y)\\n\\n # test 2\\n dut.en_i <= 0\\n await check_output_no_en(dut)\\n\\n # test 3\\n dut.en_i <= 1\\n x, y = get_test_vector()\\n cocotb.fork(write_input(dut, x))\\n await check_output(dut, y)\",\n \"def correct(self):\\n stop_flag = False\\n self.orbit_class.online_calc = False\\n # read orbit devs\\n for elem in self.orbit.corrs:\\n try:\\n elem.kick_mrad = elem.mi.get_value()\\n except Exception as e:\\n stop_flag = True\\n logger.warning(elem.id + \\\" reading error: \\\" + str(e))\\n return stop_flag\\n \\n elem.angle_read = elem.kick_mrad*1e-3\\n elem.i_kick = elem.kick_mrad\\n elem.ui.set_init_value(elem.kick_mrad)\\n elem.ui.set_value(elem.kick_mrad)\\n elem.transfer_map = self.parent.lat.method.create_tm(elem)\\n if elem.ui.alarm:\\n stop_flag = True\\n logger.warning(\\\"correct - STOP: corrector shows alarm: \\\" + elem.id)\\n\\n\\n #self.parent.lat.update_transfer_maps()\\n\\n for elem in self.orbit.bpms:\\n if elem.id not in self.new_ref_orbit.keys():\\n logger.warning(\\\"correct - STOP: BPM is not in new ref orbit: \\\" + elem.id)\\n stop_flag = True\\n return stop_flag\\n elem.x = self.new_ref_orbit[elem.id][0]\\n elem.y = self.new_ref_orbit[elem.id][1]\\n elem.ui.set_value((elem.x*1000., elem.y*1000.))\\n if elem.ui.alarm:\\n logger.warning(\\\"correct - STOP: BPM shows alarm: \\\" + elem.id)\\n stop_flag = True\\n if stop_flag:\\n return stop_flag\\n self.orbit_class.online_calc = True\\n\\n\\n if not self.orbit_class.is_rm_ok(self.orbit):\\n logger.error(\\\" correct: Calculate Response Matrix\\\")\\n self.parent.error_box(\\\"Calculate Response Matrix\\\")\\n return 0\\n\\n self.orbit_class.golden_orbit.dict2golden_orbit()\\n\\n if self.orbit_class.ui.cb_close_orbit.isChecked():\\n self.orbit_class.close_orbit()\\n\\n self.calc_correction = {}\\n for cor in self.orbit.corrs:\\n cor.angle = 0.\\n self.calc_correction[cor.id] = cor.angle\\n\\n alpha = 0.\\n\\n self.orbit.correction(alpha=alpha, p_init=None, beta=0, print_log=False)\\n for cor in self.orbit.corrs:\\n self.calc_correction[cor.id] = cor.angle\\n\\n self.set_values2correctors()\\n return stop_flag\",\n \"def test_validation_correct_molecules():\\n paths = examples_paths()\\n molecules = [\\n {'name': 'toluene', 'leap': {'parameters': 'leaprc.gaff'}},\\n {'name': 'toluene', 'leap': {'parameters': ['leaprc.gaff', 'toluene.frcmod']}},\\n {'name': 'p-xylene', 'antechamber': {'charge_method': 'bcc'}},\\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'},\\n 'antechamber': {'charge_method': None}},\\n {'name': 'p-xylene', 'antechamber': {'charge_method': 'bcc'},\\n 'epik': {'ph': 7.6, 'ph_tolerance': 0.7, 'tautomerize': False, 'select': 0}},\\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'},\\n 'antechamber': {'charge_method': None}, 'epik': {'select': 1}},\\n\\n {'filepath': paths['abl']},\\n {'filepath': paths['abl'], 'leap': {'parameters': 'leaprc.ff99SBildn'}},\\n {'filepath': paths['abl'], 'leap': {'parameters': 'leaprc.ff99SBildn'}, 'select': 1},\\n {'filepath': paths['abl'], 'select': 'all'},\\n {'filepath': paths['abl'], 'select': 'all', 'strip_protons': True},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {}},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'add_missing_residues': True}},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'add_missing_atoms': 'all', 'ph': '8.0'}},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'remove_heterogens': 'all'}},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'replace_nonstandard_residues': True}},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'apply_mutations': {'chain_id': 'A', 'mutations': 'T85I'}}},\\n {'filepath': paths['abl'], 'select': 'all', 'modeller': {'apply_mutations': {'chain_id': 'A', 'mutations': 'T85I'}}},\\n {'filepath': paths['abl'], 'select': 'all', 'modeller': {'apply_mutations': {'chain_id': 'A', 'mutations': 'WT'}}},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'apply_mutations': {'chain_id': 'A', 'mutations': 'I8A/T9A'}}},\\n {'filepath': paths['toluene'], 'leap': {'parameters': 'leaprc.gaff'}},\\n {'filepath': paths['benzene'], 'epik': {'select': 1, 'tautomerize': False}},\\n # Regions tests, make sure all other combos still work\\n {'name': 'toluene', 'regions': {'a_region': 4}},\\n {'name': 'toluene', 'regions': {'a_region': 'dsl string'}},\\n {'name': 'toluene', 'regions': {'a_region': [0, 2, 3]}},\\n {'name': 'toluene', 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}},\\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': 4}},\\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': 'dsl string'}},\\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': [0, 2, 3]}},\\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}},\\n {'filepath': paths['abl'], 'regions': {'a_region': 4}},\\n {'filepath': paths['abl'], 'regions': {'a_region': 'dsl string'}},\\n {'filepath': paths['abl'], 'regions': {'a_region': [0, 2, 3]}},\\n {'filepath': paths['abl'], 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}},\\n {'filepath': paths['toluene'], 'regions': {'a_region': 4}},\\n {'filepath': paths['toluene'], 'regions': {'a_region': 'dsl string'}},\\n {'filepath': paths['toluene'], 'regions': {'a_region': [0, 2, 3]}},\\n {'filepath': paths['toluene'], 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}}\\n ]\\n for molecule in molecules:\\n yield ExperimentBuilder._validate_molecules, {'mol': molecule}\",\n \"def loop(self, loop: bool=None):\\n self._select_interface(self._rc_loop, self._http_loop, loop)\",\n \"def main():\\n moons = initialize_moons()\\n\\n # Do it again, to get a stable initial set of values to compare against.\\n initial_state = initialize_moons()\\n needed_cycles = [0] * 3\\n\\n # Because in the mechanics of this fake universe gravity and velocity in\\n # one dimension do not affect anything in the other two dimensions, we\\n # can loop altering one dimension at a time until\\n for dimension in (Position3d.X, Position3d.Y, Position3d.Z):\\n Position3d.set_dimension(dimension)\\n cycled = False\\n cycle_count = 0\\n while not cycled:\\n if cycle_count > 30000000000:\\n print(\\\"bailing!\\\")\\n break\\n cycle_count += 1\\n for moon in moons:\\n for other_moon in moons:\\n if moon is other_moon:\\n continue\\n moon.apply_gravity(other_moon)\\n for moon in moons:\\n moon.apply_velocity()\\n match = True\\n for idx, moon in enumerate(moons):\\n if moon != initial_state[idx]:\\n # Didn't complete a cycle back to original state for this\\n # dimension. Try again.\\n match = False\\n break\\n if match:\\n # Yea! Done with this dimension\\n needed_cycles[dimension] = cycle_count\\n cycled = True\\n\\n print(lcm(needed_cycles[2], lcm(needed_cycles[0], needed_cycles[1])),\\n \\\"cycles needed to loop.\\\")\\n print(\\\"Hawking would be proud.\\\")\",\n \"def setUp(self):\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Name the first molecule.\\n cdp.mol[0].name = 'Ap4Aase'\\n\\n # Add a second molecule to the system.\\n cdp.mol.add_item(mol_name='RNA')\\n\\n # Add two more residues to the first molecule (and set the residue number of the first).\\n cdp.mol[0].res[0].num = 1\\n cdp.mol[0].res.add_item(res_num=2, res_name='Glu')\\n cdp.mol[0].res.add_item(res_num=4, res_name='Pro')\\n\\n # Add some spin info to this molecule.\\n cdp.mol[0].res[0].spin[0].name = 'NH'\\n cdp.mol[0].res[0].spin[0].num = 60\\n cdp.mol[0].res[1].spin[0].name = 'NH'\\n cdp.mol[0].res[1].spin[0].num = 63\\n\\n # Add one more residue to the second molecule (and set the residue number of the first).\\n cdp.mol[1].res[0].num = -5\\n cdp.mol[1].res.add_item(res_num=-4)\\n\\n # Add a second set of spins to the second molecule (naming the first set first).\\n cdp.mol[1].res[0].spin[0].name = 'C8'\\n cdp.mol[1].res[1].spin[0].name = 'C8'\\n cdp.mol[1].res[0].spin.add_item(spin_name='N5')\\n cdp.mol[1].res[1].spin.add_item(spin_name='N5')\\n cdp.mol[1].res[1].spin.add_item(spin_name='2H', spin_num=132)\\n\\n # Deselect a number of spins.\\n cdp.mol[0].res[0].spin[0].select = 0\\n cdp.mol[0].res[2].spin[0].select = 0\\n cdp.mol[1].res[0].spin[0].select = 0\\n cdp.mol[1].res[1].spin[1].select = 0\\n\\n # Update the metadata.\\n mol_res_spin.metadata_update()\",\n \"def test_simulate(self, scml_system):\\n\\n # Reset the system and take a random action\\n scml_system.reset()\\n action = scml_system.action_space.sample()\\n # Set a defined intitial state\\n ode_state = np.array([3, 4, 5, 6])\\n scml_system._ode_solver.set_initial_value(ode_state)\\n # Perform the action on the system\\n next_state = scml_system.simulate(action)\\n solver_state_me = scml_system._ode_solver.y[:len(DummyLoad.state_names)]\\n solver_state_el = scml_system._ode_solver.y[len(DummyLoad.state_names):]\\n torque = [scml_system.electrical_motor.torque(solver_state_el)]\\n u_sup = [scml_system.supply.u_nominal]\\n u_in = [u * u_sup[0] for u in scml_system.converter.u_in]\\n # Calculate the next state\\n desired_next_state = (\\n np.concatenate((solver_state_me, torque, solver_state_el, u_in, u_sup))\\n ) / scml_system.limits\\n\\n # Assertions for correct simulation\\n assert all(desired_next_state == next_state), 'The calculated next state differs from the expected one'\\n assert scml_system.converter.action == action, 'The action was not passed correctly to the converter'\\n assert scml_system.converter.action_set_time == 0, 'The action start time was passed incorrect to the converter'\\n assert scml_system.converter.last_i_out == scml_system.electrical_motor.i_in(scml_system._ode_solver.last_y[2:])\",\n \"def run(self):\\n while True:\\n if self.job_q.empty():\\n self.message_q.put(False)\\n return\\n try:\\n smolecule = self.job_q.get()\\n self.data_pointer[smolecule].get_adp(self.Temp)\\n except IndexError:\\n self.message_q.put((smolecule, None))\\n try:\\n self.message_q.put((smolecule, [j.adp['cart_int'] for j in self.data_pointer[smolecule].atoms]))\\n except KeyError:\\n # =======================================================\\n # self.message_q.put((molecule,[0 for i in self.data_pointer[molecule].atoms]))\\n #=======================================================\\n pass\",\n \"def test_analog_in_out_loop(self):\\n for v in range(0, 6, 1):\\n self.l.output(ao0=v, ao1=v)\\n r = self.l.input(channels=(8,8,9,9), gains=(1,4,1,4))[0]\\n for i in r:\\n self.assertTrue(abs(v-i) < .1,\\n \\\"measured %g for %g\\\" % (i, v))\",\n \"def test_shared_wires(self):\\n wires = range(2)\\n estimation_wires = range(1, 3)\\n\\n with pytest.raises(ValueError, match=\\\"No wires can be shared between the wires\\\"):\\n quantum_monte_carlo(\\n lambda: None, wires=wires, target_wire=0, estimation_wires=estimation_wires\\n )\",\n \"def test_epik_enumeration():\\n with mmtools.utils.temporary_directory() as tmp_dir:\\n yaml_content = get_template_script(tmp_dir, keep_schrodinger=True)\\n exp_builder = ExperimentBuilder(yaml_content)\\n mol_ids = ['benzene-epik0', 'benzene-epikcustom']\\n exp_builder._db._setup_molecules(*mol_ids)\\n\\n for mol_id in mol_ids:\\n output_dir = exp_builder._db.get_molecule_dir(mol_id)\\n output_basename = os.path.join(output_dir, mol_id + '-epik.')\\n assert os.path.exists(output_basename + 'mol2')\\n assert os.path.getsize(output_basename + 'mol2') > 0\\n assert os.path.exists(output_basename + 'sdf')\\n assert os.path.getsize(output_basename + 'sdf') > 0\",\n \"def run(self):\\n while True:\\n try:\\n self.check_value()\\n except Exception as e:\\n print(f\\\"[ERROR]: Error running the continuous run loop on sample_module: {e}\\\")\\n continue\",\n \"def run( self, cycles=-1 ):\",\n \"def test_selection():\\n pdb_inp = iotbx.pdb.input(source_info=None, lines=pdb_answer_0)\\n ncs_obj_phil = ncs.input(\\n hierarchy=pdb_inp.construct_hierarchy())\\n nrg = ncs_obj_phil.get_ncs_restraints_group_list()\\n\\n m1 = list(nrg[0].master_iselection)\\n c1 = list(nrg[0].copies[0].iselection)\\n c2 = list(nrg[0].copies[1].iselection)\\n\\n assert len(m1) == len(c1) # renumbering\\n assert m1 == [0, 1, 2, 3, 4, 5, 6] # 0, 1, X, 3, X, 5, X | 0, 1, 3\\n assert c1 == [7, 8, 9, 10, 11, 12, 13] # 7, 8, 9, X, X, 12, X | 4, 5, 7\\n assert c2 == [14, 15, 16, 17, 18, 19, 20] # 14, 15, X, 17, X, 19, X | 8, 9, 11\\n\\n selection1 = flex.size_t([0,1,5,3,100,101])\\n selection2 = flex.size_t([0,1,5,3,7,8,9,12,100,101])\\n selection3 = flex.size_t([0,1,5,3,7,8,9,12,14,15,19,17,100,101])\\n # gone iseqs for selection3: 2,4,6,10,11,13,16,18,20-99\\n\\n new_nrg = nrg.select(flex.bool(102, selection1))\\n # only atoms in master are selected\\n mt = list(new_nrg[0].master_iselection)\\n c1t = list(new_nrg[0].copies[0].iselection)\\n\\n assert mt == []\\n assert c1t == []\\n\\n # atoms selected in both master and copies\\n new_nrg = nrg.select(flex.bool(102, selection2))\\n # only atoms in master are selected\\n mt = list(new_nrg[0].master_iselection)\\n c1t = list(new_nrg[0].copies[0].iselection)\\n\\n assert mt == []\\n assert c1t == []\\n\\n new_nrg = nrg.select(flex.bool(102, selection3))\\n # only atoms in master are selected\\n mt = list(new_nrg[0].master_iselection)\\n c1t = list(new_nrg[0].copies[0].iselection)\\n c2t = list(new_nrg[0].copies[1].iselection)\\n\\n assert mt == [0, 1, 3], list(mt)\\n assert c1t == [4, 5, 7], list(c1t)\\n assert c2t == [8, 9, 11], list(c2t)\",\n \"async def loop():\\n # ArmDevice.storage.joints_pos = await get_positions() # Use this if encoders are wired up.\\n # ArmDevice.storage.joints_pos = simulate_positions() # Use this for testing without position feedback.\\n log.debug(\\\"command: {}\\\".format(ArmDevice.storage.command))\\n ArmDevice.storage.controller.user_command(ArmDevice.storage.mode, *ArmDevice.storage.command)\\n ArmDevice.storage.speeds = ArmDevice.storage.controller.update_duties(ArmDevice.storage.joints_pos)\\n\\n # publish speeds/duty cycles here\\n log.debug(\\\"joints_pos: {}\\\".format(ArmDevice.storage.joints_pos))\\n log.debug(\\\"speeds: {}\\\".format(ArmDevice.storage.speeds))\\n await send_duties()\",\n \"def test_for_restart(self):\\n #print(\\\"entering test_for_restart()\\\")\\n self._compile_result(\\\"UserName: \\\" + self.user_name)\\n #if self.first_song == True:\\n # msg = \\\"Welcome_str\\\"\\n # self.first_song = False\\n if self._feedback_plat == \\\"RIVA\\\":\\n self._RIVA_message_num += 1\\n text_to_RIVA(\\\"Welcome_str\\\")\\n else:# self._feedback_plat == \\\"Text\\\":\\n self._RIVA_message_num += 1\\n #to_no_voice_log(\\\"NewData:{};TTS:{}\\\".format(self._RIVA_message_num, msg))\\n ###else:\\n ### text_to_ispeech(ispeech_formatter(msg))\\n while True:\\n self._check_completion()\\n if self._song_over is False:\\n print(\\\"Song Started\\\")\\n if self._feedback_plat == \\\"RIVA\\\":\\n reset_RIVA_log()\\n self._RIVA_message_num += 1\\n #text_to_RIVA(self.response_welcome())\\n elif self._feedback_plat == \\\"Text\\\":\\n to_no_voice_log((emo_less_feedback(0, 0, 0)))\\n self.execute_song()\\n print(\\\"Re-entered Test_for_restart()\\\")\\n if self._song_over is True:\\n interface_info = gather_info(\\n parse_csv(read_csv(CSV_functions.MUSICGLOVE)))\\n #print(interface_info)\\n #print(\\\"Song_over min/max = \\\", min_max)\\n self.user_stats.set_grips(interface_info)\\n self._compile_result(grip_avg_summary_str(interface_info))\\n evaluated_info = [evaluate_worst_grip(interface_info, self._last_worst_grip),\\n evaluate_best_grip(interface_info)]\\n summary = summary_generator(evaluated_info[0], evaluated_info[1])\\n if self._feedback_plat == \\\"RIVA\\\":\\n self._RIVA_message_num += 1\\n #print(\\\"message_num={} summary={}\\\".format(self._message_num, summary))\\n text_to_RIVA(summary)\\n else:# self._feedback_plat == \\\"Text\\\":\\n to_no_voice_log(emo_less_feedback(self._RIVA_message_num, evaluated_info[0], evaluated_info[1]))\\n ###else:\\n ### text_to_ispeech(ispeech_formatter(summary))\\n self._last_30_sec = []\\n self._compile_result(summary)\\n self._csv_result.extend(read_csv(CSV_functions.MUSICGLOVE))\\n make_csv(self._csv_result, CSV_functions.M_GLOVE_SUMMARIES, what_song(self._grip_count))\\n self.__init__(self.user_name, restart=True)\\n self._RIVA_message_num = 1\\n else:\\n pass\\n return\",\n \"def ml_loop(side: str):\\n\\n # === Here is the execution order of the loop === #\\n # 1. Put the initialization code here\\n ball_served = False\\n blocker_last_x = 0\\n\\n class Pred:\\n pred = 100\\n blocker_pred_x = 0\\n last_command = 0\\n blocker_vx = 0\\n\\n \\n def move_to(player, pred) : #move platform to predicted position to catch ball \\n if player == '1P':\\n if scene_info[\\\"platform_1P\\\"][0]+20 > (pred-10) and scene_info[\\\"platform_1P\\\"][0]+20 < (pred+10): return 0 # NONE\\n elif scene_info[\\\"platform_1P\\\"][0]+20 <= (pred-10) : return 1 # goes right\\n else : return 2 # goes left\\n else :\\n if scene_info[\\\"platform_2P\\\"][0]+20 > (pred-10) and scene_info[\\\"platform_2P\\\"][0]+20 < (pred+10): return 0 # NONE\\n elif scene_info[\\\"platform_2P\\\"][0]+20 <= (pred-10) : return 1 # goes right\\n else : return 2 # goes left\\n\\n def ml_loop_for_1P(): \\n # ball slicing\\n if scene_info[\\\"ball_speed\\\"][1] > 0 and (scene_info[\\\"ball\\\"][1]+scene_info[\\\"ball_speed\\\"][1]) >= 415 and Pred.last_command == 0:\\n print(\\\"------\\\")\\n ball_x = scene_info[\\\"ball\\\"][0]\\n ball_y = scene_info[\\\"ball\\\"][1]\\n ball_vx = scene_info[\\\"ball_speed\\\"][0]\\n ball_slice_vx = scene_info[\\\"ball_speed\\\"][0]+np.sign(scene_info[\\\"ball_speed\\\"][0])*3\\n ball_vy = scene_info[\\\"ball_speed\\\"][1] \\n blocker_x = scene_info['blocker'][0] + Pred.blocker_vx\\n \\n y = abs((415 - ball_y) // ball_vy)\\n pred_ball_1P = ball_x + ball_vx * y\\n\\n y = abs((415 - 260) // ball_vy)\\n pred_ball_blocker = pred_ball_1P + ball_slice_vx * y\\n bound = pred_ball_blocker // 200 # Determine if it is beyond the boundary\\n if (bound > 0): # pred > 200 # fix landing position\\n if (bound%2 == 0) : \\n pred_ball_blocker = pred_ball_blocker - bound*200 \\n else :\\n pred_ball_blocker = 200 - (pred_ball_blocker - 200*bound)\\n elif (bound < 0) : # pred < 0\\n if (bound%2 ==1) :\\n pred_ball_blocker = abs(pred_ball_blocker - (bound+1) *200)\\n else :\\n pred_ball_blocker = pred_ball_blocker + (abs(bound)*200)\\n \\n y = abs((415 - 260) // ball_vy)\\n Pred.blocker_pred_x = blocker_x + Pred.blocker_vx * y \\n if Pred.blocker_pred_x < 0: Pred.blocker_pred_x = abs(Pred.blocker_pred_x)\\n elif Pred.blocker_pred_x > 170: Pred.blocker_pred_x = 170 - (Pred.blocker_pred_x - 170)\\n \\n if pred_ball_blocker >= Pred.blocker_pred_x-10 and pred_ball_blocker < Pred.blocker_pred_x+40:\\n print(\\\"slice will hit blicker\\\")\\n # don't slice \\n # use origin ball vx to predict will hit blocker or not\\n # if will hit blicker let ball go reverse direction\\n y = abs((415 - 260) // ball_vy)\\n pred_ball_blocker = pred_ball_1P + ball_vx * y\\n bound = pred_ball_blocker // 200 # Determine if it is beyond the boundary\\n if (bound > 0): # pred > 200 # fix landing position\\n if (bound%2 == 0) : \\n pred_ball_blocker = pred_ball_blocker - bound*200 \\n else :\\n pred_ball_blocker = 200 - (pred_ball_blocker - 200*bound)\\n elif (bound < 0) : # pred < 0\\n if (bound%2 ==1) :\\n pred_ball_blocker = abs(pred_ball_blocker - (bound+1) *200)\\n else :\\n pred_ball_blocker = pred_ball_blocker + (abs(bound)*200)\\n\\n if pred_ball_blocker >= Pred.blocker_pred_x-10 and pred_ball_blocker < Pred.blocker_pred_x+40:\\n print(\\\"will hit blocker, hit reversed direction\\\")\\n if scene_info[\\\"ball_speed\\\"][0] > 0: return 2\\n else: return 1\\n else: \\n print(\\\"will not hit blicker, do nothing\\\")\\n return 0\\n else:\\n # slice\\n print(\\\"slice will not hit blocker\\\")\\n if scene_info[\\\"ball_speed\\\"][0] > 0: return 1\\n else: return 2\\n\\n elif scene_info[\\\"ball_speed\\\"][1] > 0 : # 球正在向下 # ball goes down\\n x = ( scene_info[\\\"platform_1P\\\"][1]-scene_info[\\\"ball\\\"][1] ) // scene_info[\\\"ball_speed\\\"][1] # 幾個frame以後會需要接 # x means how many frames before catch the ball\\n Pred.pred = scene_info[\\\"ball\\\"][0]+(scene_info[\\\"ball_speed\\\"][0]*x) # 預測最終位置 # pred means predict ball landing site \\n bound = Pred.pred // 200 # Determine if it is beyond the boundary\\n if (bound > 0): # pred > 200 # fix landing position\\n if (bound%2 == 0) : \\n Pred.pred = Pred.pred - bound*200 \\n else :\\n Pred.pred = 200 - (Pred.pred - 200*bound)\\n elif (bound < 0) : # pred < 0\\n if (bound%2 ==1) :\\n Pred.pred = abs(Pred.pred - (bound+1) *200)\\n else :\\n Pred.pred = Pred.pred + (abs(bound)*200)\\n return move_to(player = '1P',pred = Pred.pred)\\n \\n else : # 球正在向上 # ball goes up\\n return move_to(player = '1P',pred = 100)\\n\\n\\n\\n def ml_loop_for_2P(): # as same as 1P\\n if scene_info[\\\"ball_speed\\\"][1] > 0 : \\n return move_to(player = '2P',pred = 100)\\n else : \\n x = ( scene_info[\\\"platform_2P\\\"][1]+30-scene_info[\\\"ball\\\"][1] ) // scene_info[\\\"ball_speed\\\"][1] \\n pred = scene_info[\\\"ball\\\"][0]+(scene_info[\\\"ball_speed\\\"][0]*x) \\n bound = pred // 200 \\n if (bound > 0):\\n if (bound%2 == 0):\\n pred = pred - bound*200 \\n else :\\n pred = 200 - (pred - 200*bound)\\n elif (bound < 0) :\\n if bound%2 ==1:\\n pred = abs(pred - (bound+1) *200)\\n else :\\n pred = pred + (abs(bound)*200)\\n return move_to(player = '2P',pred = pred)\\n\\n # 2. Inform the game process that ml process is ready\\n comm.ml_ready()\\n\\n # 3. Start an endless loop\\n while True:\\n # 3.1. Receive the scene information sent from the game process\\n scene_info = comm.recv_from_game()\\n\\n # 3.2. If either of two sides wins the game, do the updating or\\n # resetting stuff and inform the game process when the ml process\\n # is ready.\\n if scene_info[\\\"status\\\"] != \\\"GAME_ALIVE\\\":\\n # Do some updating or resetting stuff\\n ball_served = False\\n\\n # 3.2.1 Inform the game process that\\n # the ml process is ready for the next round\\n comm.ml_ready()\\n continue\\n\\n # 3.3 Put the code here to handle the scene information\\n\\n # 3.4 Send the instruction for this frame to the game process\\n if not ball_served:\\n comm.send_to_game({\\\"frame\\\": scene_info[\\\"frame\\\"], \\\"command\\\": \\\"SERVE_TO_LEFT\\\"})\\n blocker_last_x = scene_info[\\\"blocker\\\"][0]\\n Pred.last_command = 0\\n ball_served = True\\n else:\\n if side == \\\"1P\\\":\\n Pred.blocker_vx = scene_info[\\\"blocker\\\"][0] - blocker_last_x\\n if scene_info[\\\"blocker\\\"][0] == 0: Pred.blocker_vx = 5\\n elif scene_info[\\\"blocker\\\"][0] == 170: Pred.blocker_vx = -5\\n command = ml_loop_for_1P()\\n blocker_last_x = scene_info[\\\"blocker\\\"][0]\\n Pred.last_command = command\\n else:\\n command = ml_loop_for_2P()\\n\\n if command == 0:\\n comm.send_to_game({\\\"frame\\\": scene_info[\\\"frame\\\"], \\\"command\\\": \\\"NONE\\\"})\\n elif command == 1:\\n comm.send_to_game({\\\"frame\\\": scene_info[\\\"frame\\\"], \\\"command\\\": \\\"MOVE_RIGHT\\\"})\\n else :\\n comm.send_to_game({\\\"frame\\\": scene_info[\\\"frame\\\"], \\\"command\\\": \\\"MOVE_LEFT\\\"})\",\n \"async def checkNewLoop(self):\\n pass\",\n \"def test_using_mirror_output_type():\\n\\n def check_correct_type(index):\\n # Force a race condition\\n if index == 0:\\n sleep(0.1)\\n if index % 2 == 0:\\n with _using_mirror_output_type():\\n sleep(0.5)\\n return cuml.global_settings.output_type == \\\"mirror\\\"\\n else:\\n output_type = test_output_types_str[index]\\n with using_output_type(output_type):\\n sleep(0.5)\\n return cuml.global_settings.output_type == output_type\\n\\n results = [\\n delayed(check_correct_type)(index)\\n for index in range(len(test_output_types_str))\\n ]\\n\\n assert (delayed(all)(results)).compute()\",\n \"def check_calcs_v2(list_mols, data_file=\\\"\\\", max_restart=False, depth='medium', frc=False):\\n import warnings\\n from gausspy.gaussian_job_manager import server_data_unequal\\n from gausspy.data_extract_utils import latest_restarts, import_moldata, load_from_server\\n from gausspy.data_extract_utils import oniom_components_on_server, export_moldata, clean_local_files\\n from gausspy import oniom_utils\\n\\n if max_restart:\\n list_mols = latest_restarts(list_mols)\\n\\n #if we are forcing we ignore previously saved data\\n if not frc:\\n current_data = import_moldata(data_file)\\n else:\\n current_data = []\\n\\n #check saved data against current list of molecules\\n current_labels = [m.calc.label for m in current_data]\\n mol_labels = [m.calc.label for m in list_mols]\\n mismatched_labels = [label for label in current_labels if label not in mol_labels]\\n\\n if mismatched_labels:\\n warnings.warn(\\n RuntimeWarning(\\n \\\"Calculations: {m} in data_file do not match molecules passed to check_calcs\\\".format(\\n m=\\\" \\\".join(mismatched_labels))\\n )\\n )\\n\\n #extract calculation data from the datafile (note at the moment we are not extracting the non calculation part\\n # which means that if the calculation modifies the original ase object those changes will be lost\\n for saved_mol in current_data:\\n try:\\n ind = mol_labels.index(saved_mol.calc.label)\\n #loading the entire object = list_mols[ind] = saved_mod\\n #but because of python's reference passing behaviour this would mean check_calcs_v2 would not act like check_calcs (think restarted incomplete calculations)\\n list_mols[ind].calc = saved_mol.calc\\n except ValueError:\\n pass\\n\\n if frc:\\n update_mask = [True for i in range(len(list_mols))]\\n else:\\n update_mask =server_data_unequal(list_mols)\\n\\n mols_to_update = [list_mols[i] for i in range(len(list_mols)) if update_mask[i]]\\n for mol in mols_to_update:\\n #if log files on home directory and server are different we copy those files to the home directory\\n mol = load_from_server(mol, depth)\\n\\n #if we have an oniom calculation we check to see if the components of the calculation have been run and if so we retrieve them and attach them to the calculation object\\n if 'oniom' in mol.calc.method and oniom_components_on_server(mol):\\n init_mol = copy.deepcopy(mol)\\n init_mol.calc.label += '_init'\\n init_mol = load_from_server(init_mol, depth)\\n mol.calc.components = oniom_utils.oniom_comp_calcs(init_mol)\\n mol.calc.components = check_calcs_v2(mol.calc.components, depth=depth, max_restart=True, frc=frc)\\n\\n if data_file and any(update_mask):\\n export_moldata(data_file, list_mols)\\n clean_local_files(mols_to_update)\\n\\n return list_mols\",\n \"def test_run_concurrency(microvm_factory, network_config, guest_kernel, rootfs):\\n\\n for i in range(NO_OF_MICROVMS):\\n microvm = microvm_factory.build(guest_kernel, rootfs)\\n microvm.spawn()\\n microvm.basic_config(vcpu_count=1, mem_size_mib=128)\\n microvm.ssh_network_config(network_config, str(i))\\n microvm.start()\\n\\n # We check that the vm is running by testing that the ssh does\\n # not time out.\\n microvm.ssh.run(\\\"true\\\")\",\n \"def test_modul1(self):\\n\\n self.delayDisplay(\\\"Starting the test\\\")\\n #\\n # first, get some data\\n #\\n import urllib\\n downloads = (\\n ('http://slicer.kitware.com/midas3/download?items=5767', 'FA.nrrd', slicer.util.loadVolume),\\n )\\n\\n for url,name,loader in downloads:\\n filePath = slicer.app.temporaryPath + '/' + name\\n if not os.path.exists(filePath) or os.stat(filePath).st_size == 0:\\n logging.info('Requesting download %s from %s...\\\\n' % (name, url))\\n urllib.urlretrieve(url, filePath)\\n if loader:\\n logging.info('Loading %s...' % (name,))\\n loader(filePath)\\n self.delayDisplay('Finished with download and loading')\\n\\n volumeNode = slicer.util.getNode(pattern=\\\"FA\\\")\\n logic = modulLogic()\\n self.assertTrue( logic.hasImageData(volumeNode) )\\n self.delayDisplay('Test passed!')\",\n \"def test_clashing_atoms():\\n benzene_path = examples_paths()['benzene']\\n toluene_path = examples_paths()['toluene']\\n with mmtools.utils.temporary_directory() as tmp_dir:\\n yaml_content = get_template_script(tmp_dir, keep_openeye=True)\\n system_id = 'explicit-system'\\n system_description = yaml_content['systems'][system_id]\\n system_description['pack'] = True\\n system_description['solvent'] = utils.CombinatorialLeaf(['vacuum', 'PME'])\\n\\n # Sanity check: at the beginning molecules clash\\n toluene_pos = utils.get_oe_mol_positions(utils.load_oe_molecules(toluene_path, molecule_idx=0))\\n benzene_pos = utils.get_oe_mol_positions(utils.load_oe_molecules(benzene_path, molecule_idx=0))\\n assert pipeline.compute_min_dist(toluene_pos, benzene_pos) < pipeline.SetupDatabase.CLASH_THRESHOLD\\n\\n exp_builder = ExperimentBuilder(yaml_content)\\n\\n for sys_id in [system_id + '_vacuum', system_id + '_PME']:\\n system_dir = os.path.dirname(\\n exp_builder._db.get_system(sys_id)[0].position_path)\\n\\n # Get positions of molecules in the final system\\n prmtop = openmm.app.AmberPrmtopFile(os.path.join(system_dir, 'complex.prmtop'))\\n inpcrd = openmm.app.AmberInpcrdFile(os.path.join(system_dir, 'complex.inpcrd'))\\n positions = inpcrd.getPositions(asNumpy=True).value_in_unit(unit.angstrom)\\n topography = Topography(prmtop.topology, ligand_atoms='resname TOL')\\n benzene_pos2 = positions.take(topography.receptor_atoms, axis=0)\\n toluene_pos2 = positions.take(topography.ligand_atoms, axis=0)\\n # atom_indices = pipeline.find_components(prmtop.createSystem(), prmtop.topology, 'resname TOL')\\n # benzene_pos2 = positions.take(atom_indices['receptor'], axis=0)\\n # toluene_pos2 = positions.take(atom_indices['ligand'], axis=0)\\n\\n # Test that clashes are resolved in the system\\n min_dist, max_dist = pipeline.compute_min_max_dist(toluene_pos2, benzene_pos2)\\n assert min_dist >= pipeline.SetupDatabase.CLASH_THRESHOLD\\n\\n # For solvent we check that molecule is within the box\\n if sys_id == system_id + '_PME':\\n assert max_dist <= exp_builder._db.solvents['PME']['clearance'].value_in_unit(unit.angstrom)\",\n \"def testMCShiftedLumiSplit(self):\\n singleMCSubscription = self.generateFakeMCFile(firstLumi=345,\\n lastLumi=345)\\n splitter = SplitterFactory()\\n jobFactory = splitter(singleMCSubscription)\\n\\n jobGroups = jobFactory(events_per_job=100,\\n performance=self.performanceParams)\\n self.assertEqual(len(jobGroups), 1,\\n \\\"Error: JobFactory did not return one JobGroup\\\")\\n self.assertEqual(len(jobGroups[0].jobs), 1,\\n \\\"Error: JobFactory created %s jobs not one\\\"\\n % len(jobGroups[0].jobs))\\n job = jobGroups[0].jobs.pop()\\n self.assertEqual(job[\\\"mask\\\"].getMaxEvents(), 100,\\n \\\"Error: Job's max events is incorrect.\\\")\\n self.assertEqual(job[\\\"mask\\\"][\\\"FirstEvent\\\"], 1,\\n \\\"Error: Job's first event is incorrect.\\\")\\n self.assertEqual(job[\\\"mask\\\"][\\\"FirstLumi\\\"], 345,\\n \\\"Error: Job's first lumi is incorrect.\\\")\\n\\n singleMCSubscription = self.generateFakeMCFile(firstLumi=345,\\n lastLumi=345)\\n splitter = SplitterFactory()\\n jobFactory = splitter(singleMCSubscription)\\n jobGroups = jobFactory(events_per_job=1000,\\n performance=self.performanceParams)\\n self.assertEqual(len(jobGroups), 1,\\n \\\"Error: JobFactory did not return one JobGroup\\\")\\n self.assertEqual(len(jobGroups[0].jobs), 1,\\n \\\"Error: JobFactory created %s jobs not one\\\"\\n % len(jobGroups[0].jobs))\\n job = jobGroups[0].jobs.pop()\\n self.assertEqual(job[\\\"mask\\\"].getMaxEvents(), 100,\\n \\\"Error: Job's max events is incorrect.\\\")\\n self.assertEqual(job[\\\"mask\\\"][\\\"FirstEvent\\\"], 1,\\n \\\"Error: Job's first event is incorrect.\\\")\\n self.assertEqual(job[\\\"mask\\\"][\\\"FirstLumi\\\"], 345,\\n \\\"Error: Job's first lumi is incorrect.\\\")\\n\\n singleMCSubscription = self.generateFakeMCFile(firstLumi=345,\\n lastLumi=345)\\n splitter = SplitterFactory()\\n jobFactory = splitter(singleMCSubscription)\\n jobGroups = jobFactory(events_per_job=99,\\n performance=self.performanceParams)\\n self.assertEqual(len(jobGroups), 1,\\n \\\"Error: JobFactory did not return one JobGroup\\\")\\n self.assertEqual(len(jobGroups[0].jobs), 2,\\n \\\"Error: JobFactory created %s jobs not two\\\"\\n % len(jobGroups[0].jobs))\\n for job in jobGroups[0].jobs:\\n firstJobCondition = (job[\\\"mask\\\"].getMaxEvents() == 99 and\\n job[\\\"mask\\\"][\\\"FirstLumi\\\"] == 345 and\\n job[\\\"mask\\\"][\\\"FirstEvent\\\"] == 1)\\n secondJobCondition = (job[\\\"mask\\\"].getMaxEvents() == 1 and\\n job[\\\"mask\\\"][\\\"FirstLumi\\\"] == 346 and\\n job[\\\"mask\\\"][\\\"FirstEvent\\\"] == 100)\\n self.assertTrue(firstJobCondition or secondJobCondition,\\n \\\"Job mask: %s didn't pass neither of the conditions\\\"\\n % job[\\\"mask\\\"])\\n\\n singleMCSubscription = self.generateFakeMCFile(firstLumi=345,\\n lastLumi=345)\\n splitter = SplitterFactory()\\n jobFactory = splitter(singleMCSubscription)\\n jobGroups = jobFactory(events_per_job=50,\\n performance=self.performanceParams)\\n self.assertEqual(len(jobGroups), 1,\\n \\\"Error: JobFactory did not return one JobGroup\\\")\\n self.assertEqual(len(jobGroups[0].jobs), 2,\\n \\\"Error: JobFactory created %s jobs not two\\\"\\n % len(jobGroups[0].jobs))\\n for job in jobGroups[0].jobs:\\n firstJobCondition = (job[\\\"mask\\\"].getMaxEvents() == 50 and\\n job[\\\"mask\\\"][\\\"FirstLumi\\\"] == 345 and\\n job[\\\"mask\\\"][\\\"FirstEvent\\\"] == 1)\\n secondJobCondition = (job[\\\"mask\\\"].getMaxEvents() == 50 and\\n job[\\\"mask\\\"][\\\"FirstLumi\\\"] == 346 and\\n job[\\\"mask\\\"][\\\"FirstEvent\\\"] == 51)\\n self.assertTrue(firstJobCondition or secondJobCondition,\\n \\\"Job mask: %s didn't pass neither of the conditions\\\"\\n % job[\\\"mask\\\"])\",\n \"def run_multiple_test_cycles(self):\\n # Perform as many cycles as required\\n while self.args.repetitions >= 0:\\n self.run_one_test_cycle()\\n self.args.repetitions -= 1\",\n \"def test_is_in_ring(self):\\n molecule = Molecule.from_smiles(\\\"c1ccccc1\\\")\\n\\n for atom in molecule.atoms:\\n if atom.atomic_number == 6:\\n assert atom.is_in_ring()\\n\\n for bond in molecule.bonds:\\n if 1 in (bond.atom1.atomic_number, bond.atom2.atomic_number):\\n continue\\n assert bond.is_in_ring()\",\n \"def set_test_loop(self , _iter):\\n\\t\\tself.__test=_iter\",\n \"def test_stream_loop(self):\\n chans, gains, scans, rate = (10,10,10,10), (1,2,4,5), 1024, 500\\n v = [v[0] for v in self.l.stream_sync(\\n channels=chans, gains=gains,\\n num_scans=scans, rate=rate)]\\n for vi in v:\\n for r in vi:\\n self.assertTrue(abs(r-2.5) < .1,\\n \\\"%s should be cal, 2.5v\\\" % vi[0])\",\n \"def PLAYERSELECTION_LOOP():\\n pass\",\n \"def run(self):\\n self.cmdloop()\",\n \"def run1():\\n #Reseting motors\\n ResetRobot.reset_wheel_motors()\\n ResetRobot.reset_attachment_motors()\\n CalibrateRobot.calibrate_gyro()\\n\\n #mission M01 and M02 - space travel and solar panel\\n M01_M02()\\n \\n #Mission M05- Extraction \\n M05_M14()\\n\\n #Back to base before Gerhard (Remove comment if necessary)\\n return_to_base1()\\n\\n # Must delete for competition.. This is to set up forklift to repeat run.\\n Robot.attachment_left.on_for_rotations(-100, 8) #Raises Forklift \",\n \"def test_set_molecule_error(self):\\n mol = Molecule.from_smiles(\\\"CCO\\\")\\n atom = Atom(6, 0, False)\\n atom.molecule = mol\\n with pytest.raises(AssertionError, match=\\\"already has an associated molecule\\\"):\\n atom.molecule = mol\",\n \"def test_react_parallel(self):\\n import rmgpy.rmg.main\\n rmgpy.rmg.main.maxproc = 2\\n procnum = 2\\n\\n spc_a = Species().from_smiles('[OH]')\\n spcs = [Species().from_smiles('CC'), Species().from_smiles('[CH3]')]\\n spc_tuples = [((spc_a, spc), ['H_Abstraction']) for spc in spcs]\\n\\n reaction_list = list(itertools.chain.from_iterable(react(spc_tuples, procnum)))\\n self.assertIsNotNone(reaction_list)\\n self.assertEqual(len(reaction_list), 3)\\n self.assertTrue(all([isinstance(rxn, TemplateReaction) for rxn in reaction_list]))\\n\\n # Reset module level maxproc back to default\\n rmgpy.rmg.main.maxproc = 1\",\n \"def test_is_multiplexed(self):\\n run_dir = 'data/nanopore_data/run4/done_demuxing/20200104_1412_MN19414_AAU644_68125dc2'\\n multiplexed_sample_sheet = 'data/nanopore_data/run4/done_demuxing/20200104_1412_MN19414_AAU644_68125dc2/SQK-LSK109_sample_sheet.csv'\\n non_multiplexed_sample_sheet = 'data/nanopore_data/run3/demultiplexing/20200103_1412_MN19414_AAU643_68125dc2/SQK-LSK109_AAU643_sample_sheet.csv'\\n multiplexed_run = MinIONqc(run_dir, multiplexed_sample_sheet, None)\\n non_multiplexed_run = MinIONqc(run_dir, non_multiplexed_sample_sheet, None)\\n self.assertTrue(multiplexed_run._is_multiplexed())\\n self.assertFalse(non_multiplexed_run._is_multiplexed())\",\n \"def temp_mainloop(self, cycles_to_respond=1000):\\n\\n if self.com_port_select.count() > 0:\\n report = \\\"Begin measuring\\\"\\n self.go_button.setEnabled(False) # don't allow to create new threads\\n self.state_temp_loop(True)\\n self.append_msg_box(report)\\n\\n while self.temp_loop_actiator:\\n for num in range(self.com_port_select.count()):\\n # self.MainWindow_exec_thread(lambda: self.sample_devices(cycles_to_respond, num))\\n self.sample_devices(cycles_to_respond, num)\\n self.temp_repr.plot_tc_temp(self.temp_log)\\n timeo = float(self.timeout.text()) # timeout\\n sleep(timeo)\\n # -------- record data once in msg box --------\\n\\n self.go_button.setEnabled(True)\\n self.led_light.setPixmap(QtGui.QPixmap(img[\\\"red_led\\\"]))\\n else:\\n self.append_msg_box(\\\"No device is connected\\\")\",\n \"def test_validation_wrong_molecules():\\n paths = examples_paths()\\n paths['wrongformat'] = utils.get_data_filename(os.path.join('tests', 'data', 'README.md'))\\n molecules = [\\n {'antechamber': {'charge_method': 'bcc'}},\\n {'filepath': paths['wrongformat']},\\n {'name': 'p-xylene', 'antechamber': {'charge_method': 'bcc'}, 'unknown': 4},\\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'}},\\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'invalid'},\\n 'antechamber': {'charge_method': None}},\\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'},\\n 'antechamber': {'charge_method': 'bcc'}},\\n {'filepath': 'nonexistentfile.pdb', 'leap': {'parameters': 'leaprc.ff14SB'}},\\n {'filepath': paths['toluene'], 'smiles': 'Cc1ccccc1'},\\n {'filepath': paths['toluene'], 'strip_protons': True},\\n {'filepath': paths['abl'], 'leap': {'parameters': 'oldff/leaprc.ff14SB'}, 'epik': {'select': 0}},\\n {'name': 'toluene', 'epik': 0},\\n {'name': 'toluene', 'epik': {'tautomerize': 6}},\\n {'name': 'toluene', 'epik': {'extract_range': 1}},\\n {'name': 'toluene', 'smiles': 'Cc1ccccc1'},\\n {'name': 3},\\n {'smiles': 'Cc1ccccc1', 'select': 1},\\n {'name': 'Cc1ccccc1', 'select': 1},\\n {'filepath': paths['abl'], 'leap': {'parameters': 'oldff/leaprc.ff14SB'}, 'select': 'notanoption'},\\n {'filepath': paths['abl'], 'regions': 5},\\n {'filepath': paths['abl'], 'regions': {'a_region': [-56, 5.23]}},\\n {'filepath': paths['toluene'], 'leap': {'parameters': 'leaprc.gaff'}, 'strip_protons': True},\\n ]\\n for molecule in molecules:\\n yield assert_raises, YamlParseError, ExperimentBuilder._validate_molecules, {'mol': molecule}\",\n \"def exe_tests(self):\\n self.rank = mpicom.rank()\\n self.size = mpicom.size()\\n if mpicom.parallel():\\n self.test(\\\"libname\\\",os.path.split(mpicom.__file__)[1],\\\"mpicom.so\\\")\\n else:\\n self.test(\\\"libname\\\",os.path.split(mpicom.__file__)[1],\\\"mpistub.pyc\\\")\\n self.test_broadcast()\\n self.test_reduce()\\n self.test_p2p()\\n self.test_gather()\\n self.test_scatter()\\n #self.test_alltoall()\",\n \"def add_control_loop(ui):\\n\\n loop = {}\\n content_1 = content_fk_jac_loops(ui, \\\"loops_1\\\")\\n content_2 = content_fk_jac_loops(ui, \\\"loops_2\\\")\\n\\n # Effector\\n if ui.radioButton_loops_effector.isChecked():\\n loop[\\\"type\\\"] = \\\"effector\\\"\\n\\n # Getting the current item\\n ind_o = ui.comboBox_loops_origin.currentIndex()\\n ind_d = ui.comboBox_loops_destination.currentIndex()\\n if ind_o == ind_d:\\n return\\n names = [0, 0]\\n ids = [0, 0]\\n # Finding the corresponding object\\n i = 0\\n for _, _, node in robot_obj.tree:\\n for od, ind in enumerate([ind_o, ind_d]):\\n if i == ind:\\n type_, nb = node.name.split('_')\\n nb = int(nb)\\n\\n if type_ == 'joint':\\n names[od] = robot_obj.joints[nb].name\\n else:\\n names[od] = robot_obj.links[nb].name\\n\\n ids[od] = names[od]\\n continue\\n i += 1\\n if content_1 == \\\"INVALID\\\":\\n return\\n ids.append(content_1)\\n loop[\\\"ids\\\"] = ids\\n\\n text = f\\\"{names[0]} ==> {names[1]} {parse_content(content_1)}\\\"\\n\\n # CoM\\n else:\\n loop[\\\"type\\\"] = \\\"com\\\"\\n loop[\\\"ids\\\"] = [None, None, content_1]\\n text = f\\\"Center of Mass {parse_content(content_1)}\\\"\\n\\n # Effector 2\\n if ui.radioButton_loops_effector_2.isChecked():\\n loop[\\\"type_2\\\"] = \\\"effector\\\"\\n\\n # Getting the current item\\n ind_o = ui.comboBox_loops_origin_2.currentIndex()\\n ind_d = ui.comboBox_loops_destination_2.currentIndex()\\n if ind_o == ind_d:\\n return\\n names = [0, 0]\\n ids = [0, 0]\\n # Finding the corresponding object\\n i = 0\\n for _, _, node in robot_obj.tree:\\n for od, ind in enumerate([ind_o, ind_d]):\\n if i == ind:\\n type_, nb = node.name.split('_')\\n nb = int(nb)\\n\\n if type_ == 'joint':\\n names[od] = robot_obj.joints[nb].name\\n else:\\n names[od] = robot_obj.links[nb].name\\n\\n ids[od] = names[od]\\n continue\\n i += 1\\n if content_2 == \\\"INVALID\\\":\\n return\\n ids.append(content_2)\\n loop[\\\"ids_2\\\"] = ids\\n\\n text += \\\" - \\\"\\n text += f\\\"{names[0]} ==> {names[1]} {parse_content(content_2)}\\\"\\n\\n # CoM 2\\n elif ui.radioButton_loops_com_2.isChecked():\\n loop[\\\"type_2\\\"] = \\\"com\\\"\\n loop[\\\"ids_2\\\"] = [None, None, content_2]\\n text += f\\\" - Center of Mass {parse_content(content_2)}\\\"\\n else:\\n loop[\\\"type_2\\\"] = None\\n loop[\\\"ids_2\\\"] = [None, None, None]\\n\\n loop[\\\"trajectory\\\"] = str(ui.comboBox_loops_trajectory.currentText())\\n if ui.radioButton_loops_geometric.isChecked():\\n loop[\\\"control_type\\\"] = \\\"geometric\\\"\\n elif ui.radioButton_loops_positions.isChecked():\\n loop[\\\"control_type\\\"] = \\\"positions\\\"\\n else:\\n loop[\\\"control_type\\\"] = \\\"velocities\\\"\\n loop[\\\"coppelia\\\"] = ui.checkBox_loops_coppelia.isChecked()\\n loop[\\\"constraints\\\"] = ui.checkBox_loops_constraints.isChecked()\\n\\n if loop in control_loops_list:\\n return\\n\\n text += (f\\\" - {loop['trajectory']} - {loop['control_type']}\\\"\\n f\\\"{' - Coppelia' if loop['coppelia'] else ''}\\\"\\n f\\\"{' - Constraints' if loop['constraints'] else ''}\\\")\\n\\n ui.listWidget_loops.addItem(text)\\n control_loops_list.append(loop)\\n print(loop)\",\n \"def test_chunk_pauli(self, method, device):\\n opts_no_chunk = {\\\"fusion_enable\\\": False}\\n opts_chunk = copy.copy(opts_no_chunk)\\n opts_chunk[\\\"blocking_enable\\\"] = True\\n opts_chunk[\\\"blocking_qubits\\\"] = 3\\n\\n backend = self.backend(method=method, device=device, **opts_chunk)\\n backend_no_chunk = self.backend(method=method, device=device, **opts_no_chunk)\\n\\n shots = 100\\n\\n qr = QuantumRegister(5)\\n cr = ClassicalRegister(5)\\n regs = (qr, cr)\\n circuit = QuantumCircuit(*regs)\\n circuit.h(qr[0])\\n circuit.h(qr[1])\\n circuit.h(qr[2])\\n circuit.h(qr[3])\\n circuit.h(qr[4])\\n circuit.pauli(\\\"YXZYX\\\", qr)\\n circuit.measure_all()\\n\\n result = backend.run(circuit, shots=shots, memory=True).result()\\n counts = result.get_counts(circuit)\\n result_no_chunk = backend_no_chunk.run(circuit, shots=shots, memory=True).result()\\n counts_no_chunk = result_no_chunk.get_counts(circuit)\\n\\n self.assertEqual(counts_no_chunk, counts)\",\n \"def test_expand_molecules(self):\\n yaml_content = \\\"\\\"\\\"\\n ---\\n molecules:\\n rec:\\n filepath: !Combinatorial [{}, {}]\\n leap: {{parameters: oldff/leaprc.ff14SB}}\\n lig:\\n name: !Combinatorial [iupac1, iupac2]\\n leap: {{parameters: leaprc.gaff}}\\n epik:\\n select: !Combinatorial [0, 2]\\n multi:\\n filepath: {}\\n leap: {{parameters: oldff/leaprc.ff14SB}}\\n select: all\\n smiles:\\n filepath: {}\\n leap: {{parameters: leaprc.gaff}}\\n select: all\\n sdf:\\n filepath: {}\\n leap: {{parameters: leaprc.gaff}}\\n select: all\\n mol2:\\n filepath: {}\\n leap: {{parameters: leaprc.gaff}}\\n select: all\\n solvents:\\n solv1:\\n nonbonded_method: NoCutoff\\n solv2:\\n nonbonded_method: PME\\n nonbonded_cutoff: 1*nanometer\\n clearance: 10*angstroms\\n protocols:{}\\n systems:\\n sys:\\n receptor: !Combinatorial [rec, multi]\\n ligand: lig\\n solvent: !Combinatorial [solv1, solv2]\\n experiments:\\n system: sys\\n protocol: absolute-binding\\n \\\"\\\"\\\".format(self.sdf_path, self.mol2_path, self.pdb_path,\\n self.smiles_path, self.sdf_path, self.mol2_path,\\n indent(indent(standard_protocol)))\\n yaml_content = textwrap.dedent(yaml_content)\\n\\n expected_content = \\\"\\\"\\\"\\n ---\\n molecules:\\n rec_multisdf:\\n filepath: {}\\n leap: {{parameters: oldff/leaprc.ff14SB}}\\n rec_multimol2:\\n filepath: {}\\n leap: {{parameters: oldff/leaprc.ff14SB}}\\n lig_0_iupac1:\\n name: iupac1\\n leap: {{parameters: leaprc.gaff}}\\n epik: {{select: 0}}\\n lig_2_iupac1:\\n name: iupac1\\n leap: {{parameters: leaprc.gaff}}\\n epik: {{select: 2}}\\n lig_0_iupac2:\\n name: iupac2\\n leap: {{parameters: leaprc.gaff}}\\n epik: {{select: 0}}\\n lig_2_iupac2:\\n name: iupac2\\n leap: {{parameters: leaprc.gaff}}\\n epik: {{select: 2}}\\n multi_0:\\n filepath: {}\\n leap: {{parameters: oldff/leaprc.ff14SB}}\\n select: 0\\n multi_1:\\n filepath: {}\\n leap: {{parameters: oldff/leaprc.ff14SB}}\\n select: 1\\n smiles_0:\\n filepath: {}\\n leap: {{parameters: leaprc.gaff}}\\n select: 0\\n smiles_1:\\n filepath: {}\\n leap: {{parameters: leaprc.gaff}}\\n select: 1\\n sdf_0:\\n filepath: {}\\n leap: {{parameters: leaprc.gaff}}\\n select: 0\\n sdf_1:\\n filepath: {}\\n leap: {{parameters: leaprc.gaff}}\\n select: 1\\n mol2_0:\\n filepath: {}\\n leap: {{parameters: leaprc.gaff}}\\n select: 0\\n mol2_1:\\n filepath: {}\\n leap: {{parameters: leaprc.gaff}}\\n select: 1\\n solvents:\\n solv1:\\n nonbonded_method: NoCutoff\\n solv2:\\n nonbonded_method: PME\\n nonbonded_cutoff: 1*nanometer\\n clearance: 10*angstroms\\n protocols:{}\\n systems:\\n sys:\\n receptor: !Combinatorial [rec_multimol2, rec_multisdf, multi_0, multi_1]\\n ligand: !Combinatorial [lig_0_iupac1, lig_0_iupac2, lig_2_iupac1, lig_2_iupac2]\\n solvent: !Combinatorial [solv1, solv2]\\n experiments:\\n system: sys\\n protocol: absolute-binding\\n \\\"\\\"\\\".format(self.sdf_path, self.mol2_path, self.pdb_path, self.pdb_path,\\n self.smiles_path, self.smiles_path, self.sdf_path, self.sdf_path,\\n self.mol2_path, self.mol2_path, indent(standard_protocol))\\n expected_content = textwrap.dedent(expected_content)\\n\\n raw = yank_load(yaml_content)\\n expanded = ExperimentBuilder(yaml_content)._expand_molecules(raw)\\n expected = yank_load(expected_content)\\n assert expanded == expected, 'Expected:\\\\n{}\\\\n\\\\nExpanded:\\\\n{}'.format(\\n expected['systems'], expanded['systems'])\",\n \"def __init__(self, test_group):\\n super().__init__(test_group=test_group, name='restart_test')\\n\\n self.add_step(\\n SetupMesh(test_case=self, initial_condition='zero'))\\n\\n name = 'full_run'\\n step = RunModel(test_case=self, name=name, subdir=name, ntasks=4,\\n openmp_threads=1)\\n # modify the namelist options and streams file\\n step.add_namelist_file(\\n 'compass.landice.tests.hydro_radial.restart_test',\\n 'namelist.full', out_name='namelist.landice')\\n step.add_streams_file(\\n 'compass.landice.tests.hydro_radial.restart_test',\\n 'streams.full', out_name='streams.landice')\\n self.add_step(step)\\n\\n input_dir = name\\n name = 'visualize_{}'.format(name)\\n step = Visualize(test_case=self, name=name, subdir=name,\\n input_dir=input_dir)\\n self.add_step(step, run_by_default=False)\\n\\n name = 'restart_run'\\n step = RunModel(test_case=self, name=name, subdir=name, ntasks=4,\\n openmp_threads=1,\\n suffixes=['landice', 'landice.rst'])\\n\\n # modify the namelist options and streams file\\n step.add_namelist_file(\\n 'compass.landice.tests.hydro_radial.restart_test',\\n 'namelist.restart', out_name='namelist.landice')\\n step.add_streams_file(\\n 'compass.landice.tests.hydro_radial.restart_test',\\n 'streams.restart', out_name='streams.landice')\\n\\n step.add_namelist_file(\\n 'compass.landice.tests.hydro_radial.restart_test',\\n 'namelist.restart.rst', out_name='namelist.landice.rst')\\n step.add_streams_file(\\n 'compass.landice.tests.hydro_radial.restart_test',\\n 'streams.restart.rst', out_name='streams.landice.rst')\\n self.add_step(step)\\n\\n input_dir = name\\n name = 'visualize_{}'.format(name)\\n step = Visualize(test_case=self, name=name, subdir=name,\\n input_dir=input_dir)\\n self.add_step(step, run_by_default=False)\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def molecule(\\n context, command, scenario=None, driver='docker'\\n):\\n if driver == \\\"docker\\\":\\n raise Exception(\\n \\\"Can't run tests under Docker as 'timedatectl status' command will fail\\\\n\\\"\\n \\\"(see https://stackoverflow.com/a/46837044 for details)\\\"\\n )\\n test_utils.run_molecule(context, command, scenario, driver)\",\n \"def test_motor_error(self):\\n # reproducible arbitrariness\\n np.random.seed(12325)\\n\\n nsteps = 10\\n nchan = 3\\n tmax = nsteps*self.dt\\n sequence = np.random.randn(nsteps, self.N)\\n\\n target = np.random.randn(nchan, nsteps)\\n controller = LinearController(self.G, target, tau=None)\\n controller.W = np.random.randn(*controller.W.shape)\\n\\n self.G.out_fct = lambda i: sequence[i]\\n\\n class MotorErrorGrabber(object):\\n def __init__(self, target):\\n self.target = target\\n self.order = 10\\n \\n def prepare(self, tmax, dt):\\n nsteps = int_r(tmax/dt)\\n self.motor_error = np.zeros((nsteps, self.target.N))\\n\\n def evolve(self, t, dt):\\n i = int_r(t/dt)\\n self.motor_error[i, :] = self.target.get_motor_error()\\n\\n M = MotorErrorGrabber(controller)\\n M1 = simulation.StateMonitor(controller, 'out')\\n\\n sim = simulation.Simulation(self.G, controller, M, M1, dt=self.dt)\\n sim.run(tmax)\\n\\n for i in xrange(int_r(tmax/self.dt)):\\n diff = M1.out[:, i] - target[:, i]\\n self.assertTrue(np.allclose(M.motor_error[i], diff))\",\n \"def test_integration(self):\\n\\n m = 5 # number of wires in A\\n M = 2**m\\n\\n xmax = np.pi # bound to region [-pi, pi]\\n xs = np.linspace(-xmax, xmax, M)\\n\\n probs = np.array([norm().pdf(x) for x in xs])\\n probs /= np.sum(probs)\\n\\n func = lambda i: np.sin(xs[i]) ** 2\\n r_rotations = np.array([2 * np.arcsin(np.sqrt(func(i))) for i in range(M)])\\n\\n A_wires = [0, \\\"a\\\", -1.1, -10, \\\"bbb\\\"]\\n target_wire = \\\"Ancilla\\\"\\n wires = A_wires + [target_wire]\\n estimation_wires = [\\\"bob\\\", -3, 42, \\\"penny\\\", \\\"lane\\\"]\\n\\n def fn():\\n qml.templates.MottonenStatePreparation(np.sqrt(probs), wires=A_wires)\\n r_unitary(qml.RY, r_rotations, control_wires=A_wires[::-1], target_wire=target_wire)\\n\\n qmc_circuit = qml.quantum_monte_carlo(\\n fn, wires=wires, target_wire=target_wire, estimation_wires=estimation_wires\\n )\\n\\n with qml.queuing.AnnotatedQueue() as q:\\n qmc_circuit()\\n qml.probs(estimation_wires)\\n\\n tape = qml.tape.QuantumScript.from_queue(q)\\n tape = tape.expand(depth=2)\\n\\n assert all(\\n not isinstance(op, (qml.MultiControlledX, qml.templates.QFT, qml.tape.QuantumScript))\\n for op in tape.operations\\n )\\n\\n dev = qml.device(\\\"default.qubit\\\", wires=wires + estimation_wires)\\n res = dev.execute(tape)\\n\\n @qml.qnode(dev)\\n def circuit():\\n qml.templates.QuantumMonteCarlo(\\n probs, func, target_wires=wires, estimation_wires=estimation_wires\\n )\\n return qml.probs(estimation_wires)\\n\\n res_expected = circuit()\\n assert np.allclose(res, res_expected)\",\n \"def test_template_forloop(self):\\n print \\\"Running: %s - %s\\\" % (self.id(), self.shortDescription())\\n # compare sequence items\\n for i in range(0, 3):\\n input_item = g.config['templates']['sequence'][i]\\n output_item = self.output_config['out_templates']['sequence'][i]\\n\\n self.assertEqual(input_item, output_item,\\n 'sequence items (%i) do not match' % i)\",\n \"def test_interaction_on_master(self, admin_remote):\\n timeout = 1 # minute\\n sleep_between_restart = 1 # minute\\n\\n # Stop rabbit and check that there are no errors in output\\n self.control_rabbit_service(admin_remote, 'stop')\\n\\n # Wait till rabbitmq-server has \\\"Status: \\\"Exited.\\\"\\\" string\\n self.wait_rabbit_became_exited(admin_remote, timeout)\\n sleep(60 * sleep_between_restart)\\n\\n # Rabbit start-stops with check that there are no errors in output\\n for i in range(5):\\n self.control_rabbit_service(admin_remote, 'start')\\n sleep(60 * sleep_between_restart)\\n self.control_rabbit_service(admin_remote, 'stop')\\n\\n # Wait till rabbitmq-server has \\\"Active: active (running)\\\" string\\n self.control_rabbit_service(admin_remote, 'start')\\n self.wait_rabbit_became_active(admin_remote, timeout)\",\n \"def loop_context():\\n loop = setup_test_loop()\\n yield loop\\n # teardown_test_loop(loop)\",\n \"def watch_loop(self):\\n # Double threaded function that allows to stop the loop mid execution\\n def repeatIt():\\n # reset UI and flag before starting loop\\n self.resetLabels()\\n self.reset_scrollbar()\\n # enable stop button\\n self.btnStop.config(state=\\\"normal\\\")\\n # disable button while loop is running\\n self.btnStart.config(state=\\\"disabled\\\")\\n self.txtLoop.config(state=\\\"disabled\\\", textvariable=self.loopCounterUI)\\n self.labelLoop.config(text=\\\"Loop Count: \\\")\\n\\n while self.loopCount.get() > 0:\\n # move scrollbar to bottom\\n self.testCanvas.yview_moveto(0)\\n # count the loop\\n self.loopCounterUI.set(self.loopCounterUI.get() + 1)\\n\\n # Run the test cases\\n self.runThis()\\n\\n # Below are just to reset the UI\\n if not self.stopLoop:\\n print(\\\"loop not stopped so proceed\\\")\\n # let user know script is stopping\\n x = Label(\\n self.testFrame, text=f'End of Loop',\\n background=self.bgChooser(),\\n foreground=\\\"#630984\\\",\\n font=self.boldFont)\\n x.pack(fill=X)\\n # flag gor BG and labels\\n self.bgCounter += 1\\n self.LabelLists.append(x)\\n # allow window to catch up\\n self.tkRoot.update()\\n self.update_scrollbar()\\n else:\\n print(\\\"loop has been stopped so not gonna print End of Loop\\\")\\n\\n # pause before restarting loop\\n self.loopCount.set(self.loopCount.get()-1)\\n time.sleep(1)\\n\\n # disable stop button\\n self.btnStop.config(state=\\\"disabled\\\")\\n # re-enable button after loop is done\\n self.btnStart.config(state=\\\"normal\\\")\\n self.txtLoop.config(state=\\\"normal\\\", textvariable=self.loopCount)\\n self.labelLoop.config(text=\\\"Enter Loop Count: \\\")\\n # self.testCanvas.yview_moveto(0)\\n # Let user know the script is done\\n if not self.stopLoop:\\n # loop did not stopped\\n x = Label(\\n self.testFrame, text=f'Test is done!',\\n background=self.bgChooser(),\\n foreground=\\\"#057224\\\",\\n font=self.boldFont)\\n x.pack(fill=X)\\n self.bgCounter += 1\\n else:\\n x = Label(\\n self.testFrame, text=f'Test stopped!',\\n background=self.bgChooser(),\\n foreground=\\\"#057224\\\",\\n font=self.boldFont)\\n x.pack(fill=X)\\n self.bgCounter += 1\\n self.btnStart.config(state=\\\"normal\\\")\\n self.txtLoop.config(state=\\\"normal\\\", textvariable=self.loopCount)\\n self.labelLoop.config(text=\\\"Enter Loop count: \\\")\\n self.loopCount.set(50000)\\n self.LabelLists.append(x)\\n # allow window to catch up\\n self.tkRoot.update()\\n self.update_scrollbar()\\n thread = threading.Thread(target=repeatIt)\\n thread.start()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.78410846","0.72731423","0.71487254","0.7066662","0.6906277","0.6623356","0.6518581","0.64826006","0.64725286","0.6450824","0.6367674","0.62304765","0.61855984","0.61084175","0.60988086","0.609054","0.6079127","0.5973447","0.59563404","0.55609775","0.54880345","0.5448034","0.53954214","0.5382176","0.53472996","0.5342508","0.5320194","0.5286563","0.52584887","0.52371144","0.5232206","0.5212187","0.5206892","0.51857036","0.5173262","0.5167763","0.50953597","0.50937414","0.50898033","0.5061302","0.5054946","0.50536776","0.50533384","0.50039774","0.4971128","0.49532852","0.4943114","0.49421078","0.49365807","0.4926819","0.49180844","0.49166542","0.49120024","0.4893609","0.4892132","0.48756948","0.4867441","0.48662776","0.48631394","0.4857338","0.48527536","0.4849501","0.4829397","0.48265165","0.48259157","0.4821398","0.48200867","0.48173302","0.4814219","0.48129317","0.48126224","0.4810852","0.48087233","0.48078656","0.47840923","0.4782325","0.47768265","0.4770795","0.47691292","0.476874","0.47648028","0.47636065","0.47583398","0.47500476","0.47499716","0.47459337","0.47459134","0.47309953","0.47301224","0.47235528","0.47172248","0.47143194","0.4704808","0.47025144","0.46965224","0.46931085","0.46918842","0.46765122","0.4675709","0.46699655"],"string":"[\n \"0.78410846\",\n \"0.72731423\",\n \"0.71487254\",\n \"0.7066662\",\n \"0.6906277\",\n \"0.6623356\",\n \"0.6518581\",\n \"0.64826006\",\n \"0.64725286\",\n \"0.6450824\",\n \"0.6367674\",\n \"0.62304765\",\n \"0.61855984\",\n \"0.61084175\",\n \"0.60988086\",\n \"0.609054\",\n \"0.6079127\",\n \"0.5973447\",\n \"0.59563404\",\n \"0.55609775\",\n \"0.54880345\",\n \"0.5448034\",\n \"0.53954214\",\n \"0.5382176\",\n \"0.53472996\",\n \"0.5342508\",\n \"0.5320194\",\n \"0.5286563\",\n \"0.52584887\",\n \"0.52371144\",\n \"0.5232206\",\n \"0.5212187\",\n \"0.5206892\",\n \"0.51857036\",\n \"0.5173262\",\n \"0.5167763\",\n \"0.50953597\",\n \"0.50937414\",\n \"0.50898033\",\n \"0.5061302\",\n \"0.5054946\",\n \"0.50536776\",\n \"0.50533384\",\n \"0.50039774\",\n \"0.4971128\",\n \"0.49532852\",\n \"0.4943114\",\n \"0.49421078\",\n \"0.49365807\",\n \"0.4926819\",\n \"0.49180844\",\n \"0.49166542\",\n \"0.49120024\",\n \"0.4893609\",\n \"0.4892132\",\n \"0.48756948\",\n \"0.4867441\",\n \"0.48662776\",\n \"0.48631394\",\n \"0.4857338\",\n \"0.48527536\",\n \"0.4849501\",\n \"0.4829397\",\n \"0.48265165\",\n \"0.48259157\",\n \"0.4821398\",\n \"0.48200867\",\n \"0.48173302\",\n \"0.4814219\",\n \"0.48129317\",\n \"0.48126224\",\n \"0.4810852\",\n \"0.48087233\",\n \"0.48078656\",\n \"0.47840923\",\n \"0.4782325\",\n \"0.47768265\",\n \"0.4770795\",\n \"0.47691292\",\n \"0.476874\",\n \"0.47648028\",\n \"0.47636065\",\n \"0.47583398\",\n \"0.47500476\",\n \"0.47499716\",\n \"0.47459337\",\n \"0.47459134\",\n \"0.47309953\",\n \"0.47301224\",\n \"0.47235528\",\n \"0.47172248\",\n \"0.47143194\",\n \"0.4704808\",\n \"0.47025144\",\n \"0.46965224\",\n \"0.46931085\",\n \"0.46918842\",\n \"0.46765122\",\n \"0.4675709\",\n \"0.46699655\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.75784975"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":81490,"cells":{"query":{"kind":"string","value":"Test the proper operation of the molecule loop when no data is present. The function tested is pipe_control.mol_res_spin.molecule_loop()."},"document":{"kind":"string","value":"def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_molecule_loop_no_selection(self):\n\n # Molecule data.\n name = ['Ap4Aase', 'RNA']\n\n # Loop over the molecules.\n i = 0\n for mol in mol_res_spin.molecule_loop():\n # Test the molecule names.\n self.assertEqual(mol.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_molecule_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for molecule in mol_res_spin.molecule_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_molecule_loop(self):\n\n # Loop over the molecules.\n for mol in mol_res_spin.molecule_loop('#RNA'):\n # Test the molecule name.\n self.assertEqual(mol.name, 'RNA')\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_spin_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for spin in mol_res_spin.spin_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_residue_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for residue in mol_res_spin.residue_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def test_spin_loop_no_selection(self):\n\n # Spin data.\n select = [0, 1, 0, 0, 1, 1, 0, 1]\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 8)","def test_spin_loop(self):\n\n # Spin data.\n select = [1, 0]\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, 'N5')\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 2)","def test_run_molecule_not_selected(self, single_mol_system):\n sequence = \"ABCDE\"\n processor = dssp.AnnotateResidues(\n \"test\", sequence, molecule_selector=lambda mol: False\n )\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert vermouth.utils.are_all_equal(found)\n assert found[0] is None","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def run(self):\n while True:\n if self.job_q.empty():\n self.message_q.put(False)\n return\n try:\n smolecule = self.job_q.get()\n self.data_pointer[smolecule].get_adp(self.Temp)\n except IndexError:\n self.message_q.put((smolecule, None))\n try:\n self.message_q.put((smolecule, [j.adp['cart_int'] for j in self.data_pointer[smolecule].atoms]))\n except KeyError:\n # =======================================================\n # self.message_q.put((molecule,[0 for i in self.data_pointer[molecule].atoms]))\n #=======================================================\n pass","def test_spin_loop_multiatom(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_run_loop_success(self):\n found = False\n pyint = Interpreter(limit=15)\n try:\n pyint.run(code=BF_CODE_LOOP_TWICE)\n except SystemExit: \n found = True\n self.assertFalse(found)","def test_return_molecule_pipe_fail(self):\n\n # Try to get a molecule from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')","def test_spin_loop_wildcard(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N*'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def loop(self):\n raise NotImplementedError()","def _run(self):\n while(self._loop):\n pass","async def checkNewLoop(self):\n pass","def test_residue_loop(self):\n\n # Loop over the residues.\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\n # Test the selection.\n self.assertEqual(res.num, 2)\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)","def loop(self):\n pass","def test_return_molecule(self):\n\n # Ask for a few molecules.\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\n\n # Test the data of molecule 1.\n self.assertEqual(mol1.name, 'Ap4Aase')\n\n # Test the data of molecule 2.\n self.assertEqual(mol2.name, 'RNA')","def test_single_molecules_cycle_one(self, single_mol_system):\n sequence = \"A\"\n expected = [sequence] * (5 * 3)\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def test_multi_molecules_cycle_one(self, multi_mol_system_irregular):\n sequence = \"A\"\n expected = [sequence] * (15 * 3)\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_irregular)\n found = self.sequence_from_system(multi_mol_system_irregular, \"test\")\n assert found == expected","def test_no_immediate_stop(self):\n script = ControlScript()\n options = ControlOptions()\n options.parseOptions([b\"--data-path\", self.mktemp()])\n self.assertNoResult(script.main(MemoryCoreReactor(), options))","def test_run_molecule(self, single_mol_system):\n sequence = \"ABCDE\"\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def run(self):\n while True:\n try:\n self.check_value()\n except Exception as e:\n print(f\"[ERROR]: Error running the continuous run loop on sample_module: {e}\")\n continue","def test_reset(self):\n ran = []\n def foo():\n ran.append(None)\n\n c = task.Clock()\n lc = TestableLoopingCall(c, foo)\n lc.start(2, now=False)\n c.advance(1)\n lc.reset()\n c.advance(1)\n self.assertEqual(ran, [])\n c.advance(1)\n self.assertEqual(ran, [None])","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_circularloop(self):\n cmd = f\"{SRC_LISTER} -i {PWD}/main\"\n with subprocess.Popen(\n shlex.split(cmd), stdout=subprocess.PIPE, stderr=subprocess.PIPE\n ) as proc:\n try:\n out, err = proc.communicate(timeout=5)\n assert len(err.strip()) > 0, \"Expected a circular reference error\"\n except subprocess.TimeoutExpired as te:\n print(\"Unexpected parser timeout during infinite loop test\")","def test_multi_molecules_cycle(self, multi_mol_system_regular, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n expected = expected * 3\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_regular)\n found = self.sequence_from_system(multi_mol_system_regular, \"test\")\n assert found == expected","def algorithm_loop(self):","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","async def hold_loop(self, *args) -> bool:\n raise NotImplementedError","def test_noFailure(self):\n for i in range(10):\n self.assertTrue(self.circuit_breaker.available())","def test_block_missing_batch(self):\n pass","def test_empty_with_filter(multi_mol_system_irregular):\n sequence = \"not empty\"\n processor = dssp.AnnotateResidues(\n \"test\", sequence, molecule_selector=lambda mol: False\n )\n with pytest.raises(ValueError):\n processor.run_system(multi_mol_system_irregular)","def infinite_loop():\n return True","def _loop_raw(raw):\n raise NotImplemented","def run_one_test_cycle(self):\n logging.info(\n \"{0} operations remaining: {1}\".format(\n self.args.pm_operation, self.args.repetitions\n )\n )\n\n self.check_last_cycle_duration()\n if self.args.repetitions > 0:\n self.run_pm_command()\n else:\n self.summary()","def _while_loop(pd, nmax, max_loop, ncore, outfile):\n \n # make sure the random seed is different for every processor\n random_number_seeds = [3456789, 7654321, 2435467, 8273645,\n 1085712, 4154712, 1248291, 8415917,\n 2345161, 5710916, 5718601, 7516234,\n 9235161, 4917519, 1111245, 8167834] \n \n # get the processor ID (1 - Ncore) and convert to single integer\n current = multiprocessing.current_process()\n pid = current._identity\n pid = pid[0]\n \n #\n # choose a different seed for each processor from the list so each processor has\n # a different randum number seed. Then, fiddle with each seed a little so \n # the seeds aren't the same every time the code is run\n seed = np.int(random_number_seeds[pid] * (np.random.rand()*(10.0 - 0.01) + 0.01))\n \n np.random.seed(seed)\n \n #print 'id and seed', pid, seed\n \n n_particles = 0\n loop_counter = 0\n fmin_scale = 1.0E-100 # -16 -> -32 -> -100\n F_max = np.max(pd.DF.f) #; F_min = np.min(pd.DF.f);\n F_min = np.min(pd.DF.f) * fmin_scale\n # F_max = np.max(pd.DF.f[:-1])#; F_max = 1.0E-88\n #print F_min, F_max\n if pd.optimize:\n relative_potential = pd._interpolate_relative_potential\n else:\n relative_potential = pd.DF.relative_potential\n \n \n pos = np.zeros((nmax, 3))\n vel = np.zeros((nmax, 3)) \n \n while (( n_particles < nmax) and (loop_counter < max_loop)):\n \n r = pd._choose_position()\n Psi = relative_potential(r) \n \n v = pd._choose_velocity(r, Psi)\n \n E = Psi - 0.5 * v * v\n \n f_E = pd.DF.interpolate_f(E)\n \n logF = ( np.random.rand()*(np.log10(F_max) - np.log10(F_min)) + np.log10(F_min) )\n \n # if choosing random F in log F, might be good to do the comparison in logspace as well\n #.... i.e log(F) <= log(f_E) \n #\n # 0 FOR F_E MEANS THAT E < E_min of the potential. THis happens when Psi - KE is smaller\n # than the value of the potential at large_r... should this be considered unbound \n # even though it isn't zero? Is this effectively zero? This has been adjusted in the velocity\n # picking routine but needs verification to make sure it works.... but regardless, I doubt\n # that this is the reason why the particles are failing for NFW but working for hernquist....\n #\n if np.abs(np.log10(f_E)) == np.inf:\n keep_particle = False\n _my_print('log value error... throwing out particle')\n else:\n keep_particle = (logF <= np.log10(f_E))\n\n \n if keep_particle: \n index = n_particles \n \n # \n # need to sample in cosine theta NOT theta!!!!! WTF!!!!!\n #\n #\n \n theta = np.arccos( np.random.rand() * (2.0) - 1.0)\n \n # convert position to cartesian using random theta and phi\n phi = np.random.rand() * 2.0 * np.pi\n \n x = np.sin(theta) * np.cos(phi)\n y = np.sin(theta) * np.sin(phi)\n z = np.cos(theta)\n \n pos[index] = r * np.array([x,y,z])\n\n # repeat for velocity using new random numbersw\n theta = np.arccos( np.random.rand() * (2.0) - 1.0)\n phi = np.random.rand() * 2.0 * np.pi\n \n vx = np.sin(theta) * np.cos(phi)\n vy = np.sin(theta) * np.sin(phi)\n vz = np.cos(theta)\n \n vel[index] = v * np.array([vx,vy,vz])\n \"\"\" \n #else: # do strict cartesian ... slower.... less attractive\n # \n # axis_list = [0, 1, 2]\n # random.shuffle(axis_list)\n \n # #axis_index = np.random.randint(3)\n # first_axis = axis_list[0]\n #\n # pos[index, first_axis] = np.random.rand() * (2.0*r) - r\n #del axis_list[axis_index]\n \n #axis_index = np.random.randint(2)\n # second_axis = axis_list[1]\n \n max_r = np.sqrt(r*r - pos[index,first_axis]**2)\n \n pos[index, second_axis] = np.random.rand()*(2.0 * max_r) - max_r\n #del axis_list[axis_index]\n \n max_r = np.sqrt(r*r - pos[index,first_axis]**2 - pos[index,second_axis]**2)\n \n third_axis = axis_list[2]\n pos[index, third_axis] = np.random.rand() * (2.0 * max_r) - max_r\n \n if np.sqrt(pos[index,0]**2 + pos[index,1]**2 + pos[index,2]**2) > r:\n _my_print('R IS TOO LARGE')\n \n ###\n axis_list = [0, 1, 2]\n random.shuffle(axis_list)\n \n #axis_index = np.random.randint(3)\n first_axis = axis_list[0]\n \n vel[index, first_axis] = np.random.rand() * (2.0*v) - v\n #del axis_list[axis_index]\n \n #axis_index = np.random.randint(2)\n second_axis = axis_list[1]\n \n max_v = np.sqrt(v*v - vel[index,first_axis]**2)\n \n vel[index, second_axis] = np.random.rand()*(2.0 * max_v) - max_v\n #del axis_list[axis_index]\n \n max_v = np.sqrt(v*v - vel[index,first_axis]**2 - vel[index,second_axis]**2)\n \n third_axis = axis_list[2]\n vel[index, third_axis] = np.random.rand() * (2.0 * max_v) - max_v \n \n \n \"\"\"\n n_particles = n_particles + 1\n \n if (loop_counter % 5000) == 0:\n _my_print(\"Have %4i particles. On loop %6i\"%(n_particles, loop_counter))\n loop_counter = loop_counter + 1\n \n # now write out to a temporary file\n f = open(outfile + \"_%02i_\"%(pid) + \".temp\", 'w')\n fmt = \"%12.12E %12.12E %12.12E %12.12E %12.12E %12.12E %12.12E\\n\"\n \n \n for i in np.arange(nmax):\n f.write(fmt%(pd.M_part, pos[i,0], pos[i,1], pos[i,2], \n vel[i,0], vel[i,1], vel[i,2]))\n \n \n f.close() \n \n return pos, vel","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def do_simulation_loop(self) -> tuple[bool, bool]:\n running, reset = True, False\n for event in pygame.event.get():\n if check_for_quit(event):\n running = False\n elif check_for_reset(event):\n running = False\n reset = True\n self.simulation.do_step()\n self.update_visualization()\n self.simple_pygame.loop()\n return running, reset","async def loop():\n # ArmDevice.storage.joints_pos = await get_positions() # Use this if encoders are wired up.\n # ArmDevice.storage.joints_pos = simulate_positions() # Use this for testing without position feedback.\n log.debug(\"command: {}\".format(ArmDevice.storage.command))\n ArmDevice.storage.controller.user_command(ArmDevice.storage.mode, *ArmDevice.storage.command)\n ArmDevice.storage.speeds = ArmDevice.storage.controller.update_duties(ArmDevice.storage.joints_pos)\n\n # publish speeds/duty cycles here\n log.debug(\"joints_pos: {}\".format(ArmDevice.storage.joints_pos))\n log.debug(\"speeds: {}\".format(ArmDevice.storage.speeds))\n await send_duties()","def run_no_input(self, initial=None, context=None):\n for _ in self.run(initial, context):\n raise RuntimeError(\"Machine requires input to continue!\")","def test_control_loop_example():\n example.control.print_error_measurement()\n matplotlib.use('agg')\n example.control.visualise_error_measurement(fig_file='cs_compare.pdf')\n assert path.isfile('cs_compare.pdf')\n example.control.sil_comparison()","def _handle_loop(self):\n pass","def run_until_stop(self):\n while self.commands[self.pointer] != END:\n # Get the cmd\n cmd = self.commands[self.pointer]\n opcode = cmd % 100\n modes = cmd // 100\n \n vals, locs, self.pointer = get_vals_and_locs(opcode, modes, self.pointer, self.commands)\n \n if opcode == ADD:\n self.commands[locs[2]] = vals[0] + vals[1]\n elif opcode == MUL:\n self.commands[locs[2]] = vals[0] * vals[1]\n elif opcode == INP:\n if self.inputs:\n self.commands[locs[0]] = self.inputs.pop(0)\n else:\n # Put the pointer back, so we run this opcode again\n self.pointer -= 2\n return False\n elif opcode == OUT:\n self.outputs.append(vals[0])\n elif opcode == JIT:\n if vals[0] != 0:\n self.pointer = vals[1]\n elif opcode == JIF:\n if vals[0] == 0:\n self.pointer = vals[1]\n elif opcode == LT:\n self.commands[locs[2]] = 1 if vals[0] < vals[1] else 0\n elif opcode == EQ:\n self.commands[locs[2]] = 1 if vals[0] == vals[1] else 0\n else:\n print(\"FAIL????\")\n\n return True","def test_empty_input_data(self):\n self.data.diffusion_data = np.array([])\n self.assertRaises(ValueError, module_05.run_module,\n self.data)","def test_readiness(self):\n self.command.package = self.input_ovf\n ready, reason = self.command.ready_to_run()\n self.assertFalse(ready)\n self.assertRegex(reason, \"No file information\")\n self.assertRaises(InvalidInputError, self.command.run)\n\n self.command.file_path = \"input.vmdk\"\n ready, reason = self.command.ready_to_run()\n self.assertTrue(ready)\n\n self.command.file_path = None\n self.command.file_id = \"file1\"\n ready, reason = self.command.ready_to_run()\n self.assertTrue(ready)","def test_run_loop_exc(self):\n with self.assertRaises(ExecutionException):\n pyint = Interpreter(limit=1)\n pyint.run(code=BF_CODE_LOOP_TWICE)","def run_nop(self):\n pass","def test_sync_task_no_server(comm):\n run_server, server_args, run_client, client_args = helper_config(comm, \"sync\")\n client = run_client(**client_args)\n try:\n client.connect()\n except Exception as exc: # pylint: disable=broad-except\n assert False, f\"unexpected exception: {exc}\"\n sleep(0.1)\n if comm == \"udp\":\n rr = client.read_coils(1, 1, slave=0x01)\n assert isinstance(rr, ModbusIOException)\n else:\n with pytest.raises((asyncio.exceptions.TimeoutError, ConnectionException)):\n client.read_coils(1, 1, slave=0x01)\n client.close()","def test_for_restart(self):\n #print(\"entering test_for_restart()\")\n self._compile_result(\"UserName: \" + self.user_name)\n #if self.first_song == True:\n # msg = \"Welcome_str\"\n # self.first_song = False\n if self._feedback_plat == \"RIVA\":\n self._RIVA_message_num += 1\n text_to_RIVA(\"Welcome_str\")\n else:# self._feedback_plat == \"Text\":\n self._RIVA_message_num += 1\n #to_no_voice_log(\"NewData:{};TTS:{}\".format(self._RIVA_message_num, msg))\n ###else:\n ### text_to_ispeech(ispeech_formatter(msg))\n while True:\n self._check_completion()\n if self._song_over is False:\n print(\"Song Started\")\n if self._feedback_plat == \"RIVA\":\n reset_RIVA_log()\n self._RIVA_message_num += 1\n #text_to_RIVA(self.response_welcome())\n elif self._feedback_plat == \"Text\":\n to_no_voice_log((emo_less_feedback(0, 0, 0)))\n self.execute_song()\n print(\"Re-entered Test_for_restart()\")\n if self._song_over is True:\n interface_info = gather_info(\n parse_csv(read_csv(CSV_functions.MUSICGLOVE)))\n #print(interface_info)\n #print(\"Song_over min/max = \", min_max)\n self.user_stats.set_grips(interface_info)\n self._compile_result(grip_avg_summary_str(interface_info))\n evaluated_info = [evaluate_worst_grip(interface_info, self._last_worst_grip),\n evaluate_best_grip(interface_info)]\n summary = summary_generator(evaluated_info[0], evaluated_info[1])\n if self._feedback_plat == \"RIVA\":\n self._RIVA_message_num += 1\n #print(\"message_num={} summary={}\".format(self._message_num, summary))\n text_to_RIVA(summary)\n else:# self._feedback_plat == \"Text\":\n to_no_voice_log(emo_less_feedback(self._RIVA_message_num, evaluated_info[0], evaluated_info[1]))\n ###else:\n ### text_to_ispeech(ispeech_formatter(summary))\n self._last_30_sec = []\n self._compile_result(summary)\n self._csv_result.extend(read_csv(CSV_functions.MUSICGLOVE))\n make_csv(self._csv_result, CSV_functions.M_GLOVE_SUMMARIES, what_song(self._grip_count))\n self.__init__(self.user_name, restart=True)\n self._RIVA_message_num = 1\n else:\n pass\n return","def test_modul1(self):\n\n self.delayDisplay(\"Starting the test\")\n #\n # first, get some data\n #\n import urllib\n downloads = (\n ('http://slicer.kitware.com/midas3/download?items=5767', 'FA.nrrd', slicer.util.loadVolume),\n )\n\n for url,name,loader in downloads:\n filePath = slicer.app.temporaryPath + '/' + name\n if not os.path.exists(filePath) or os.stat(filePath).st_size == 0:\n logging.info('Requesting download %s from %s...\\n' % (name, url))\n urllib.urlretrieve(url, filePath)\n if loader:\n logging.info('Loading %s...' % (name,))\n loader(filePath)\n self.delayDisplay('Finished with download and loading')\n\n volumeNode = slicer.util.getNode(pattern=\"FA\")\n logic = modulLogic()\n self.assertTrue( logic.hasImageData(volumeNode) )\n self.delayDisplay('Test passed!')","def _readloop(self):\r\n\r\n while self._ll_alive:\r\n with self._rx_lock:\r\n data = self._Random(1)\r\n if len(data) != 0: # check for timeout\r\n self._uart_rx_queue.put(data)","def nanny(self): \n while not self.started and not self.failed:\n eventlet.sleep(.1)\n return not self.failed","def test_single_molecule(self, single_mol_system, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def test_stream_loop(self):\n chans, gains, scans, rate = (10,10,10,10), (1,2,4,5), 1024, 500\n v = [v[0] for v in self.l.stream_sync(\n channels=chans, gains=gains,\n num_scans=scans, rate=rate)]\n for vi in v:\n for r in vi:\n self.assertTrue(abs(r-2.5) < .1,\n \"%s should be cal, 2.5v\" % vi[0])","def test_compute_bulkiness(tmp_path: Path):\n df = read_molecules(PATH_TEST / \"smiles_carboxylic.csv\")\n opts = create_options(tmp_path)\n\n data = compute_batch_bulkiness(df.smiles, opts, pd.Index(list(range(4))))\n assert not np.all(np.isnan(data))","def worker(self, loop):\n # CONNECTION LOOP\n while True:\n # if we are in reconnect status, sleep before connecting\n if self.reconnect_time > 0:\n yield from asyncio.sleep(1)\n\n # if we've been reconnecting for over 60s, bail out\n if (time.time() - self.reconnect_time) > 60:\n self.logger.error(\"Could not reconnect to mochad after 60s\")\n loop.stop()\n break\n\n try:\n yield from self.connect()\n except OSError as e:\n if self.reconnect_time == 0:\n self.reconnect_time = time.time()\n self.logger.warn(\n \"Could not connect to mochad. Retrying: {}\".format(e))\n # reconnect_time = -1 here means the first connection failed\n elif self.reconnect_time == -1:\n self.logger.error(\n \"Could not connect to mochad: {}\".format(e))\n loop.stop()\n break\n\n # keep trying to reconnect\n continue\n\n # if we make it this far we've successfully connected, reset the\n # reconnect time\n self.reconnect_time = 0\n self.logger.info(\"Connected to mochad\")\n\n # READ FROM NETWORK LOOP\n while True:\n line = yield from self.reader.readline()\n # an empty string means connection lost, exit read loop\n if not line and self.reader.at_eof():\n break\n # parse the line\n try:\n addr, message_dict, kind = self.parse_mochad_line(\n line.decode(\"utf-8\").rstrip())\n except Exception as e:\n self.logger.error(\n \"Failed to parse mochad message {}: {}\".format(\n line, e))\n continue \n\n # addr/func will be blank when we have nothing to dispatch\n if addr and message_dict:\n # we don't to use mochad's timestamp because it lacks a year\n message_dict['dispatch_time'] = datetime.now(\n pytz.UTC).isoformat()\n\n asyncio.async(self.dispatch_message(addr, message_dict, kind))\n\n\n # we broke out of the read loop: we got disconnected, retry connect\n self.logger.warn(\"Lost connection to mochad. Retrying.\")\n self.reconnect_time = time.time()","def _run(self):\n logging.warning('-> perform EMPTY experiment...')","def test_chunk_pauli(self, method, device):\n opts_no_chunk = {\"fusion_enable\": False}\n opts_chunk = copy.copy(opts_no_chunk)\n opts_chunk[\"blocking_enable\"] = True\n opts_chunk[\"blocking_qubits\"] = 3\n\n backend = self.backend(method=method, device=device, **opts_chunk)\n backend_no_chunk = self.backend(method=method, device=device, **opts_no_chunk)\n\n shots = 100\n\n qr = QuantumRegister(5)\n cr = ClassicalRegister(5)\n regs = (qr, cr)\n circuit = QuantumCircuit(*regs)\n circuit.h(qr[0])\n circuit.h(qr[1])\n circuit.h(qr[2])\n circuit.h(qr[3])\n circuit.h(qr[4])\n circuit.pauli(\"YXZYX\", qr)\n circuit.measure_all()\n\n result = backend.run(circuit, shots=shots, memory=True).result()\n counts = result.get_counts(circuit)\n result_no_chunk = backend_no_chunk.run(circuit, shots=shots, memory=True).result()\n counts_no_chunk = result_no_chunk.get_counts(circuit)\n\n self.assertEqual(counts_no_chunk, counts)","def has_no_yielded_molecules(self, batch: Batch[T]) -> bool:\n return all(\n self._key_maker.get_key(molecule) not in self._molecules\n for molecule in (record.get_molecule() for record in batch)\n )","def testReset(self):\n \n clk = Signal(0)\n rst = Signal(1)\n clock_gen = ClkDriver(clk, period=4)\n \n out = Signal(intbv(0)[4:])\n counter = Counter(out, clk, rst)\n \n def test():\n for i in range(200):\n # count up to 9 then reset\n if int(out) == 9:\n rst.next = 0\n yield delay(1)\n self.assertEqual(int(out), 0)\n # turn off reset next time\n else:\n rst.next = 1\n yield delay(1)\n \n check = test()\n sim = Simulation(counter, clock_gen, check)\n sim.run(400, quiet=1)","def test_run_simulation_returns_nothing(self):\n sim = ss.Simulation()\n assert sim.run_simulation(10) is None","def run(self):\n\n if self.success and not self.running:\n self.log.info(\"Humidity and temp control started...\")\n self.running = True\n elif self.testmode and not self.running:\n self.log.critical(\"Humidity and temp TEST MODE started!!!\")\n self.running = True\n elif not self.running:\n self.log.info(\"Humidity and temp control NOT started...\")\n return\n\n if not self.stop_measurement_loop and self.success:\n try:\n # Query the environemnt etc from Brandbox\n envvalues = self.vcw.query(\n self.resource, self.resource[\"get_environment\"]\n )\n envvalues = envvalues.split(\",\")\n\n # Get dewpoint\n boxvalues = self.vcw.query(\n self.resource, self.resource[\"get_box_environment\"]\n )\n boxvalues = boxvalues.split(\",\")\n\n vacuumvalues = self.vcw.query(\n self.resource, self.resource[\"get_vacuum\"]\n )\n\n # get light\n luxvalues = self.vcw.query(self.resource, self.resource[\"get_lux\"])\n luxvalues = luxvalues.split(\",\")[0]\n\n # if an error happen, as so often with the brandbox read the queue\n if self.readqueue:\n try:\n ans = self.vcw.read(self.resource)\n if ans:\n self.log.critical(\"Brandbox had an non empty queue: {}\".format(ans))\n except:\n self.log.info(\"Brandbox indicated an non empty queue, reading queue yielded no queue...\", exc_info=True)\n\n\n try:\n if float(luxvalues) >= 0.5:\n self.framework[\"Configs\"][\"config\"][\"settings\"][\"lights\"] = True\n else:\n self.framework[\"Configs\"][\"config\"][\"settings\"][\"lights\"] = False\n\n # get door\n # doorvalues = self.vcw.query(self.resource, self.resource[\"get_door\"])\n # doorvalues = doorvalues.split(\",\")[0]\n # if doorvalues == \"1\":\n # self.framework[\"Configs\"][\"config\"][\"settings\"][\"door\"] = False\n # else:\n # self.framework[\"Configs\"][\"config\"][\"settings\"][\"door\"] = True\n\n # get light\n vacuumvalues = vacuumvalues.split(\",\")[0]\n if vacuumvalues == \"1\":\n self.framework[\"Configs\"][\"config\"][\"settings\"][\"vacuum\"] = True\n else:\n self.framework[\"Configs\"][\"config\"][\"settings\"][\"vacuum\"] = False\n\n # Here a list\n self.main.humidity_history = np.append(\n self.main.humidity_history, float(envvalues[1])\n ) # todo: memory leak since no values will be deleted\n self.main.temperatur_history = np.append(\n self.main.humidity_history, float(envvalues[3])\n )\n\n # Write the pt100 and light status and environement in the box to the global variables\n self.framework[\"Configs\"][\"config\"][\"settings\"][\n \"chuck_temperature\"\n ] = float(envvalues[3])\n self.framework[\"Configs\"][\"config\"][\"settings\"][\n \"air_temperature\"\n ] = float(envvalues[0])\n self.framework[\"Configs\"][\"config\"][\"settings\"][\"dew_point\"] = float(\n boxvalues[3]\n )\n\n # Send data to main\n self.queue_to_main.put(\n {\n \"temperature_air\": [float(time()), float(envvalues[0])],\n \"temperature_chuck\": [float(time()), float(envvalues[3])],\n \"dew_point\": [float(time()), float(boxvalues[3])],\n \"humidity\": [float(time()), float(envvalues[1])],\n }\n )\n except:\n self.readqueue = True\n\n except Exception as err:\n self.log.error(\n \"The temperature and humidity controller seems not to be responding. Error: {!s}\".format(\n err\n ),\n exc_info=True,\n )\n\n elif self.testmode:\n self.log.critical(\"Testmode sends message to main!\")\n self.queue_to_main.put(\n {\n \"temperature\": [float(time()), float(random.randint(1, 10))],\n \"humidity\": [float(time()), float(random.randint(1, 10))],\n }\n )\n\n if not self.main.stop_measurement_loop:\n self.start_timer(self.run)\n else:\n self.log.info(\n \"Shutting down environment control due to stop of measurement loop\"\n )","def test_run_read(self):\n\n self.ictrl[0] = 1 + 2 + 4 + 8\n vmec_f90wrap.runvmec(self.ictrl, self.filename, self.verbose, \\\n self.fcomm, reset_file)\n\n self.assertTrue(self.ictrl[1] in success_codes)\n\n self.assertEqual(vmec_f90wrap.vmec_input.nfp, 3)\n self.assertEqual(vmec_f90wrap.vmec_input.mpol, 4)\n self.assertEqual(vmec_f90wrap.vmec_input.ntor, 3)\n print('rbc.shape:', vmec_f90wrap.vmec_input.rbc.shape)\n print('rbc:',vmec_f90wrap.vmec_input.rbc[101:103, 0:4])\n\n # n = 0, m = 0:\n self.assertAlmostEqual(vmec_f90wrap.vmec_input.rbc[101,0], 1.3782)\n\n # n = 0, m = 1:\n self.assertAlmostEqual(vmec_f90wrap.vmec_input.zbs[101,1], 4.6465E-01)\n\n # n = 1, m = 1:\n self.assertAlmostEqual(vmec_f90wrap.vmec_input.zbs[102,1], 1.6516E-01)\n\n # Now try reading in the output\n wout_file = os.path.join(os.path.dirname(__file__), 'wout_li383_low_res.nc')\n ierr = 0\n vmec_f90wrap.read_wout_mod.read_wout_file(wout_file, ierr)\n self.assertEqual(ierr, 0)\n self.assertAlmostEqual(vmec_f90wrap.read_wout_mod.betatot, \\\n 0.0426215030653306, places=4)\n\n print('iotaf.shape:',vmec_f90wrap.read_wout_mod.iotaf.shape)\n print('rmnc.shape:',vmec_f90wrap.read_wout_mod.rmnc.shape)\n\n self.assertAlmostEqual(vmec_f90wrap.read_wout_mod.iotaf[-1], \\\n 0.654868168783638, places=4)\n\n self.assertAlmostEqual(vmec_f90wrap.read_wout_mod.rmnc[0, 0], \\\n 1.4773028173065, places=4)","async def hold_loop(self):\n pass","def test_io_counter_loop(self):\n self.l.output(conf_io=0x8, state_io=0x0)\n self.l.count(reset=True)\n for i in range(10):\n self.l.output(state_io=0x8)\n self.l.output(state_io=0x0)\n c, t = self.l.count()\n self.assertEqual(c, 9,\n \"counted %g pulses\" % c)","def test_simulationRun(self):\n self.opt = { 'temperature' : 300.0, 'friction' : 1, 'dt' : 0.00002,\n 'nIter' : 2, 'nstepsNC' : 2, 'nstepsMD' : 1, 'nprop' : 1,\n 'nonbondedMethod' : 'NoCutoff', 'constraints': 'HBonds',\n 'trajectory_interval' : 1, 'reporter_interval' : 1,\n 'outfname' : 'mc-test',\n 'platform' : None,\n 'constraints' : 'HBonds',\n 'mc_per_iter' : 2 }\n\n structure = self.full_struct\n class SetRotationMove(RandomLigandRotationMove):\n def __init__(self, structure, resname='LIG'):\n super(SetRotationMove, self).__init__(structure, resname)\n\n def move(self, context):\n \"\"\"Function that performs a random rotation about the\n center of mass of the ligand.\n \"\"\"\n #TODO: check if we need to deepcopy\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\n\n self.positions = positions[self.atom_indices]\n self.center_of_mass = self.getCenterOfMass(self.positions, self.masses)\n reduced_pos = self.positions - self.center_of_mass\n\n # Define random rotational move on the ligand\n #set rotation so that test is reproducible\n set_rotation_matrix = np.array([[-0.62297988, -0.17349253, 0.7627558 ],\n [ 0.55082352, -0.78964857, 0.27027502],\n [ 0.55541834, 0.58851973, 0.58749893]])\n\n\n #set_rotation_matrix = np.array([[1, 0, 0],\n # [0, 1, 0],\n # [0, 0, 1]])\n\n #multiply lig coordinates by rot matrix and add back COM translation from origin\n rot_move = np.dot(reduced_pos, set_rotation_matrix) * positions.unit + self.center_of_mass\n\n # Update ligand positions in nc_sim\n for index, atomidx in enumerate(self.atom_indices):\n positions[atomidx] = rot_move[index]\n context.setPositions(positions)\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\n self.positions = positions[self.atom_indices]\n return context\n\n\n self.model = SetRotationMove(structure, resname='ALA')\n #self.model = RandomLigandRotationMove(structure, resname='ALA')\n\n self.model.atom_indices = range(22)\n self.model.topology = structure[self.model.atom_indices].topology\n self.model.positions = structure[self.model.atom_indices].positions\n self.model.calculateProperties()\n\n self.mover = MoveEngine(self.model)\n #Initialize the SimulationFactory object\n sims = SimulationFactory(structure, self.mover, **self.opt)\n #print(sims)\n system = sims.generateSystem(structure, **self.opt)\n simdict = sims.createSimulationSet()\n alch_system = sims.generateAlchSystem(system, self.model.atom_indices)\n self.nc_sim = sims.generateSimFromStruct(structure, self.mover, alch_system, ncmc=True, **self.opt)\n self.model.calculateProperties()\n self.initial_positions = self.nc_sim.context.getState(getPositions=True).getPositions(asNumpy=True)\n mc_sim = Simulation(sims, self.mover, **self.opt)\n #monkeypatch to access acceptance value\n def nacceptRejectMC(self, temperature=300, **opt):\n \"\"\"Function that chooses to accept or reject the proposed move.\n \"\"\"\n md_state0 = self.current_state['md']['state0']\n md_state1 = self.current_state['md']['state1']\n log_mc = (md_state1['potential_energy'] - md_state0['potential_energy']) * (-1.0/self.nc_sim.context._integrator.kT)\n randnum = math.log(np.random.random())\n\n if log_mc > randnum:\n self.accept += 1\n print('MC MOVE ACCEPTED: log_mc {} > randnum {}'.format(log_mc, randnum) )\n self.md_sim.context.setPositions(md_state1['positions'])\n else:\n self.reject += 1\n print('MC MOVE REJECTED: log_mc {} < {}'.format(log_mc, randnum) )\n self.md_sim.context.setPositions(md_state0['positions'])\n self.log_mc = log_mc\n self.md_sim.context.setVelocitiesToTemperature(self.opt['temperature'])\n mc_sim.acceptRejectMC = nacceptRejectMC\n nacceptRejectMC.__get__(mc_sim)\n mc_sim.acceptRejectMC = types.MethodType(nacceptRejectMC, mc_sim)\n mc_sim.runMC(self.opt['nIter'])\n #get log acceptance\n print(mc_sim.log_mc)\n #if mc is working, should be around -24.1\n assert mc_sim.log_mc <= -23.8 and mc_sim.log_mc >= -24.3","def has_loop(self) -> bool:\n try:\n list(self)\n return False\n except ContainsLoopError:\n return True","def test_read_mol_input():\n # good input\n read_mol_input(os.path.join(TEST_DIR, \"example_mol_input_file.txt\"))\n # good input with extra spaces\n read_mol_input(os.path.join(TEST_DIR, \"example2_mol_input_file.txt\"))\n # no such file error\n assert_raises(FileNotFoundError, read_mol_input, 'no-such-file')\n # qcm appears twice\n assert_raises(ValueError, read_mol_input, os.path.join(TEST_DIR, \"bad1_mol_input_file.txt\"))\n # missing struct type\n assert_raises(ValueError, read_mol_input, os.path.join(TEST_DIR, \"bad2_mol_input_file.txt\"))","def test_run(self):\n engine = Engine(self.config_file, self.api_token, 23)\n engine.msg_wait_iterations = 0\n\n # Put some stuff on the task queue\n self.setup_helper.add_volumetric_tasks(self.aws_creds[\"access_key\"],\n self.aws_creds['secret_key'],\n self.upload_queue_url, engine.backend)\n\n engine.join()\n engine.run()\n\n # Check for tile to exist\n s3 = boto3.resource('s3')\n ingest_bucket = s3.Bucket(self.ingest_bucket_name)\n\n with tempfile.NamedTemporaryFile() as test_file:\n with open(test_file.name, 'wb') as raw_data:\n ingest_bucket.download_fileobj(VOLUMETRIC_CUBOID_KEY, raw_data)\n with open(test_file.name, 'rb') as raw_data:\n # Using an empty CloudVolume dataset so all values should be 0.\n # dtype set in boss-v0.2-test.json under chunk_processor.params.info.data_type\n cuboid = self.s3_object_to_cuboid(raw_data.read(), 'uint8')\n unique_vals = np.unique(cuboid)\n assert 1 == len(unique_vals)\n assert 0 == unique_vals[0]","async def main(dut):\n # Create a 10us period clock on port clk\n clock = Clock(dut.clk_i, 10, units=\"us\")\n cocotb.fork(clock.start())\n\n # Reset system\n await FallingEdge(dut.clk_i)\n dut.rst_n_i <= 0\n dut.en_i <= 0\n dut.data_i <= 0\n dut.valid_i <= 0\n\n # reset\n await FallingEdge(dut.clk_i)\n dut.rst_n_i <= 1\n\n # test 1\n dut.en_i <= 1\n x, y = get_test_vector()\n cocotb.fork(write_input(dut, x))\n await check_output(dut, y)\n\n # test 2\n dut.en_i <= 0\n await check_output_no_en(dut)\n\n # test 3\n dut.en_i <= 1\n x, y = get_test_vector()\n cocotb.fork(write_input(dut, x))\n await check_output(dut, y)","def __main_loop(self):\n\n while not self.stop:\n self.__lock_data = True\n self.__bus_messages_copy = deepcopy(self.__bus_messages)\n self.__line_messages_copy = deepcopy(self.__line_messages)\n self.__global_messages_copy = deepcopy(self.__global_messages)\n self.__bus_messages = {}\n self.__line_messages = {}\n self.__global_messages = {\"kick reason\": \"\", \"free text\": \"\"}\n buses_to_kick_copy = deepcopy(self.__buses_to_kick)\n self.__buses_to_kick = list()\n self.__lock_data = False\n\n for bus in buses_to_kick_copy: # handles the buses that need to be kicked\n message = \"kicked for reason:\" + self.__global_messages_copy[\"kick reason\"]\n if bus.line_num in self.__line_messages_copy.keys():\n message += self.__line_messages_copy[bus.line_num][\"kick reason\"]\n if bus.line_num in self.__line_messages_copy.keys() and bus.id in self.__bus_messages_copy[\n bus.line_num].keys():\n message += self.__bus_messages_copy[bus.line_num][bus.id][\"kick reason\"]\n print(f\"sending message{message.strip()}\")\n bus.send_to_bus(message.strip())\n\n global_message = self.__build_global_update()\n for line, buses in self.__bus_controller.bus_dict.items():\n line_message = self.__build_line_update(line)\n for bus in buses:\n bus_message = self.__build_bus_update(bus)\n message = global_message + line_message + bus_message\n message = message.strip(\"\\n\")\n if message != \"\":\n bus.send_to_bus(message)\n\n sleep(MessagesSender.SLEEP_TIME)\n\n self.__shut_down()\n print(\"polling thread stopped\")","def test_shutdown_restart(self):\n log.info(\"CONFIG: %s\", self._agent_config())\n self.create_sample_data_set_dir('node59p1_step2.dat', TELEM_DIR, \"node59p1.dat\")\n\n self.assert_initialize(final_state=ResourceAgentState.COMMAND)\n\n # Slow down processing to 1 per second to give us time to stop\n self.dataset_agent_client.set_resource({DriverParameter.RECORDS_PER_SECOND: 1})\n self.assert_start_sampling()\n\n # Verify we get one sample\n try:\n # Read the first file and verify the data\n result = self.data_subscribers.get_samples(DataParticleType.CONTROL, 1)\n result1 = self.data_subscribers.get_samples(DataParticleType.SAMPLE, 3)\n result.extend(result1)\n log.debug(\"RESULT: %s\", result)\n\n # Verify values\n self.assert_data_values(result, 'test_data_1-2.txt.result.yml')\n self.assert_sample_queue_size(DataParticleType.CONTROL, 0)\n self.assert_sample_queue_size(DataParticleType.SAMPLE, 0)\n\n self.create_sample_data_set_dir('node59p1_step4.dat', TELEM_DIR, \"node59p1.dat\")\n # Now read the first record of the second file then stop\n result = self.data_subscribers.get_samples(DataParticleType.SAMPLE, 3)\n log.debug(\"RESULT 1: %s\", result)\n self.assert_stop_sampling()\n self.assert_sample_queue_size(DataParticleType.CONTROL, 0)\n self.assert_sample_queue_size(DataParticleType.SAMPLE, 0)\n\n # stop and re-start the agent\n self.stop_dataset_agent_client()\n self.init_dataset_agent_client()\n # re-initialize\n self.assert_initialize()\n\n result2 = self.data_subscribers.get_samples(DataParticleType.SAMPLE, 3)\n log.debug(\"RESULT 2: %s\", result2)\n result.extend(result2)\n log.debug(\"RESULT: %s\", result)\n self.assert_data_values(result, 'test_data_3-4.txt.result.yml')\n self.assert_sample_queue_size(DataParticleType.CONTROL, 0)\n self.assert_sample_queue_size(DataParticleType.SAMPLE, 0)\n except SampleTimeout as e:\n log.error(\"Exception trapped: %s\", e, exc_info=True)\n self.fail(\"Sample timeout.\")","def ml_loop(side: str):\n\n # === Here is the execution order of the loop === #\n # 1. Put the initialization code here\n ball_served = False\n blocker_last_x = 0\n\n class Pred:\n pred = 100\n blocker_pred_x = 0\n last_command = 0\n blocker_vx = 0\n\n \n def move_to(player, pred) : #move platform to predicted position to catch ball \n if player == '1P':\n if scene_info[\"platform_1P\"][0]+20 > (pred-10) and scene_info[\"platform_1P\"][0]+20 < (pred+10): return 0 # NONE\n elif scene_info[\"platform_1P\"][0]+20 <= (pred-10) : return 1 # goes right\n else : return 2 # goes left\n else :\n if scene_info[\"platform_2P\"][0]+20 > (pred-10) and scene_info[\"platform_2P\"][0]+20 < (pred+10): return 0 # NONE\n elif scene_info[\"platform_2P\"][0]+20 <= (pred-10) : return 1 # goes right\n else : return 2 # goes left\n\n def ml_loop_for_1P(): \n # ball slicing\n if scene_info[\"ball_speed\"][1] > 0 and (scene_info[\"ball\"][1]+scene_info[\"ball_speed\"][1]) >= 415 and Pred.last_command == 0:\n print(\"------\")\n ball_x = scene_info[\"ball\"][0]\n ball_y = scene_info[\"ball\"][1]\n ball_vx = scene_info[\"ball_speed\"][0]\n ball_slice_vx = scene_info[\"ball_speed\"][0]+np.sign(scene_info[\"ball_speed\"][0])*3\n ball_vy = scene_info[\"ball_speed\"][1] \n blocker_x = scene_info['blocker'][0] + Pred.blocker_vx\n \n y = abs((415 - ball_y) // ball_vy)\n pred_ball_1P = ball_x + ball_vx * y\n\n y = abs((415 - 260) // ball_vy)\n pred_ball_blocker = pred_ball_1P + ball_slice_vx * y\n bound = pred_ball_blocker // 200 # Determine if it is beyond the boundary\n if (bound > 0): # pred > 200 # fix landing position\n if (bound%2 == 0) : \n pred_ball_blocker = pred_ball_blocker - bound*200 \n else :\n pred_ball_blocker = 200 - (pred_ball_blocker - 200*bound)\n elif (bound < 0) : # pred < 0\n if (bound%2 ==1) :\n pred_ball_blocker = abs(pred_ball_blocker - (bound+1) *200)\n else :\n pred_ball_blocker = pred_ball_blocker + (abs(bound)*200)\n \n y = abs((415 - 260) // ball_vy)\n Pred.blocker_pred_x = blocker_x + Pred.blocker_vx * y \n if Pred.blocker_pred_x < 0: Pred.blocker_pred_x = abs(Pred.blocker_pred_x)\n elif Pred.blocker_pred_x > 170: Pred.blocker_pred_x = 170 - (Pred.blocker_pred_x - 170)\n \n if pred_ball_blocker >= Pred.blocker_pred_x-10 and pred_ball_blocker < Pred.blocker_pred_x+40:\n print(\"slice will hit blicker\")\n # don't slice \n # use origin ball vx to predict will hit blocker or not\n # if will hit blicker let ball go reverse direction\n y = abs((415 - 260) // ball_vy)\n pred_ball_blocker = pred_ball_1P + ball_vx * y\n bound = pred_ball_blocker // 200 # Determine if it is beyond the boundary\n if (bound > 0): # pred > 200 # fix landing position\n if (bound%2 == 0) : \n pred_ball_blocker = pred_ball_blocker - bound*200 \n else :\n pred_ball_blocker = 200 - (pred_ball_blocker - 200*bound)\n elif (bound < 0) : # pred < 0\n if (bound%2 ==1) :\n pred_ball_blocker = abs(pred_ball_blocker - (bound+1) *200)\n else :\n pred_ball_blocker = pred_ball_blocker + (abs(bound)*200)\n\n if pred_ball_blocker >= Pred.blocker_pred_x-10 and pred_ball_blocker < Pred.blocker_pred_x+40:\n print(\"will hit blocker, hit reversed direction\")\n if scene_info[\"ball_speed\"][0] > 0: return 2\n else: return 1\n else: \n print(\"will not hit blicker, do nothing\")\n return 0\n else:\n # slice\n print(\"slice will not hit blocker\")\n if scene_info[\"ball_speed\"][0] > 0: return 1\n else: return 2\n\n elif scene_info[\"ball_speed\"][1] > 0 : # 球正在向下 # ball goes down\n x = ( scene_info[\"platform_1P\"][1]-scene_info[\"ball\"][1] ) // scene_info[\"ball_speed\"][1] # 幾個frame以後會需要接 # x means how many frames before catch the ball\n Pred.pred = scene_info[\"ball\"][0]+(scene_info[\"ball_speed\"][0]*x) # 預測最終位置 # pred means predict ball landing site \n bound = Pred.pred // 200 # Determine if it is beyond the boundary\n if (bound > 0): # pred > 200 # fix landing position\n if (bound%2 == 0) : \n Pred.pred = Pred.pred - bound*200 \n else :\n Pred.pred = 200 - (Pred.pred - 200*bound)\n elif (bound < 0) : # pred < 0\n if (bound%2 ==1) :\n Pred.pred = abs(Pred.pred - (bound+1) *200)\n else :\n Pred.pred = Pred.pred + (abs(bound)*200)\n return move_to(player = '1P',pred = Pred.pred)\n \n else : # 球正在向上 # ball goes up\n return move_to(player = '1P',pred = 100)\n\n\n\n def ml_loop_for_2P(): # as same as 1P\n if scene_info[\"ball_speed\"][1] > 0 : \n return move_to(player = '2P',pred = 100)\n else : \n x = ( scene_info[\"platform_2P\"][1]+30-scene_info[\"ball\"][1] ) // scene_info[\"ball_speed\"][1] \n pred = scene_info[\"ball\"][0]+(scene_info[\"ball_speed\"][0]*x) \n bound = pred // 200 \n if (bound > 0):\n if (bound%2 == 0):\n pred = pred - bound*200 \n else :\n pred = 200 - (pred - 200*bound)\n elif (bound < 0) :\n if bound%2 ==1:\n pred = abs(pred - (bound+1) *200)\n else :\n pred = pred + (abs(bound)*200)\n return move_to(player = '2P',pred = pred)\n\n # 2. Inform the game process that ml process is ready\n comm.ml_ready()\n\n # 3. Start an endless loop\n while True:\n # 3.1. Receive the scene information sent from the game process\n scene_info = comm.recv_from_game()\n\n # 3.2. If either of two sides wins the game, do the updating or\n # resetting stuff and inform the game process when the ml process\n # is ready.\n if scene_info[\"status\"] != \"GAME_ALIVE\":\n # Do some updating or resetting stuff\n ball_served = False\n\n # 3.2.1 Inform the game process that\n # the ml process is ready for the next round\n comm.ml_ready()\n continue\n\n # 3.3 Put the code here to handle the scene information\n\n # 3.4 Send the instruction for this frame to the game process\n if not ball_served:\n comm.send_to_game({\"frame\": scene_info[\"frame\"], \"command\": \"SERVE_TO_LEFT\"})\n blocker_last_x = scene_info[\"blocker\"][0]\n Pred.last_command = 0\n ball_served = True\n else:\n if side == \"1P\":\n Pred.blocker_vx = scene_info[\"blocker\"][0] - blocker_last_x\n if scene_info[\"blocker\"][0] == 0: Pred.blocker_vx = 5\n elif scene_info[\"blocker\"][0] == 170: Pred.blocker_vx = -5\n command = ml_loop_for_1P()\n blocker_last_x = scene_info[\"blocker\"][0]\n Pred.last_command = command\n else:\n command = ml_loop_for_2P()\n\n if command == 0:\n comm.send_to_game({\"frame\": scene_info[\"frame\"], \"command\": \"NONE\"})\n elif command == 1:\n comm.send_to_game({\"frame\": scene_info[\"frame\"], \"command\": \"MOVE_RIGHT\"})\n else :\n comm.send_to_game({\"frame\": scene_info[\"frame\"], \"command\": \"MOVE_LEFT\"})","def test_back_fill(self):\n self.driver.start_sampling()\n\n # step 2 contains 2 blocks, start with this and get both since we used them\n # separately in other tests \n self.clear_async_data()\n self.create_sample_data_set_dir(\n \"node59p1_step2.dat\",\n TELEM_DIR,\n \"node59p1.dat\",\n copy_metadata=False\n )\n self.assert_data(\n (DostadParserTelemeteredDataParticle, DostadParserTelemeteredMetadataDataParticle),\n 'test_data_1-2.txt.result.yml',\n count=3\n )\n\n # This file has had a section of DO data replaced with 0s\n self.clear_async_data()\n self.create_sample_data_set_dir(\n 'node59p1_step3.dat',\n TELEM_DIR,\n \"node59p1.dat\",\n copy_metadata=False\n )\n self.assert_data(\n DostadParserTelemeteredDataParticle,\n 'test_data_3.txt.result.yml',\n count=3\n )\n\n # Now fill in the zeroed section from step3, this should just return the new\n # data\n self.clear_async_data()\n self.create_sample_data_set_dir(\n 'node59p1_step4.dat',\n TELEM_DIR,\n \"node59p1.dat\",\n copy_metadata=False\n )\n self.assert_data(\n DostadParserTelemeteredDataParticle,\n 'test_data_4.txt.result.yml',\n count=1\n )\n\n # start over now, using step 4\n self.driver.stop_sampling()\n\n # Reset the driver with no memento\n self.memento = None\n self.driver = MflmDOSTADDataSetDriver(\n self._driver_config()['startup_config'],\n self.memento,\n self.data_callback,\n self.state_callback,\n self.event_callback,\n self.exception_callback)\n self.driver.start_sampling()\n\n self.clear_async_data()\n self.create_sample_data_set_dir(\n 'node59p1_step4.dat',\n TELEM_DIR,\n \"node59p1.dat\",\n copy_metadata=False\n )\n self.assert_data(\n (DostadParserTelemeteredDataParticle, DostadParserTelemeteredMetadataDataParticle),\n 'test_data_1-4.txt.result.yml',\n count=7\n )","def test_fleur_relax_continue_converged(self, run_with_cache, mock_code_factory):\n assert False","def _run_cycle(self):\n pass","def loop_run(self, loops):\n self.loop_seek(self.num_loops + loops)","def testPluginNoError(self):\n schema = self.dataset.makeMinimalSchema()\n task = lsst.meas.base.SingleFrameMeasurementTask(schema=schema, config=self.config)\n exposure, cat = self.dataset.realize(noise=100.0, schema=schema, randomSeed=0)\n task.run(cat, exposure)\n source = cat[0]\n self.assertFalse(source.get(self.algName + \"_flag\"))\n self.assertFalse(source.get(self.algName + \"_flag_containsNan\"))\n self.assertFalse(source.get(self.algName + \"_flag_edge\"))","def loop(self):\n while self.dispatch(True) is not QUIT:\n pass","def mainloop(self, run, *args, **kwds):\r\n #self.m.make()\r\n self.time = 0\r\n Dummy = things(0,0,0)\r\n Dummy.threadqueue.append(-1)\r\n Dummy.s=self\r\n Dummy.name = 'End of simulation.'\r\n heappush(self.queue, (self.timeout, (Dummy, 1000)))\r\n #count = 0\r\n while self.time < self.timeout:\r\n run(*args, **kwds)\r\n (now, (item, i)) = heappop(self.queue)\r\n self.CalculateResourse(now)\r\n self.time = now\r\n item.creat()\r\n #count += 1\r\n #print 'Number of loops' , count\r","def pauseLoop(self):\n print('SYNC stim detected LOW')\n self.loopRunning = False","def test_shutdown_restart(self):\n log.info(\"CONFIG: %s\", self._agent_config())\n self.create_sample_data_set_dir(\n 'node59p1_step2.dat',\n TELEM_DIR,\n \"node59p1.dat\",\n copy_metadata=False\n )\n\n self.assert_initialize(final_state=ResourceAgentState.COMMAND)\n\n # Slow down processing to 1 per second to give us time to stop\n self.dataset_agent_client.set_resource({DriverParameter.RECORDS_PER_SECOND: 1})\n self.assert_start_sampling()\n\n # Verify we get one sample\n try:\n # Read the first file and verify the data\n result = self.data_subscribers.get_samples(DataParticleType.METADATA_TELEMETERED, 1)\n result1 = self.data_subscribers.get_samples(DataParticleType.SAMPLE_TELEMETERED, 2)\n result.extend(result1)\n log.debug(\"RESULT: %s\", result)\n\n # Verify values\n self.assert_data_values(result, 'test_data_1-2.txt.result.yml')\n self.assert_sample_queue_size(DataParticleType.METADATA_TELEMETERED, 0)\n self.assert_sample_queue_size(DataParticleType.SAMPLE_TELEMETERED, 0)\n\n self.create_sample_data_set_dir(\n 'node59p1_step4.dat',\n TELEM_DIR,\n \"node59p1.dat\",\n copy_metadata=False\n )\n # Now read the first records of the second file then stop\n result1 = self.data_subscribers.get_samples(DataParticleType.SAMPLE_TELEMETERED, 2)\n log.debug(\"RESULT 1: %s\", result1)\n self.assert_stop_sampling()\n self.assert_sample_queue_size(DataParticleType.METADATA_TELEMETERED, 0)\n self.assert_sample_queue_size(DataParticleType.SAMPLE_TELEMETERED, 0)\n\n # stop and re-start the agent\n self.stop_dataset_agent_client()\n self.init_dataset_agent_client()\n # re-initialize\n self.assert_initialize()\n\n # Restart sampling and ensure we get the last 2 records of the file\n result2 = self.data_subscribers.get_samples(DataParticleType.SAMPLE_TELEMETERED, 2)\n log.debug(\"RESULT 2: %s\", result2)\n result = result1\n result.extend(result2)\n log.debug(\"RESULT: %s\", result)\n self.assert_sample_queue_size(DataParticleType.METADATA_TELEMETERED, 0)\n self.assert_data_values(result, 'test_data_3-4.txt.result.yml')\n self.assert_sample_queue_size(DataParticleType.METADATA_TELEMETERED, 0)\n self.assert_sample_queue_size(DataParticleType.SAMPLE_TELEMETERED, 0)\n except SampleTimeout as e:\n log.error(\"Exception trapped: %s\", e, exc_info=True)\n self.fail(\"Sample timeout.\")","def block(self):\n # I WILL RUN FOR EVER \n # BUT WHY ARE YOU RUNNING ?\n self.__loop.run_forever()","def test_for_loop(self, modes, parse_input_mocked_metadata):\n bb = parse_input_mocked_metadata(\n \"for int m in {}\\n\\tMeasureFock() | m\".format(modes)\n )\n assert np.all(\n bb._forvar[\"m\"] == np.array(modes)\n )\n assert bb.operations == [\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[0]]},\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[1]]},\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[2]]}\n ]","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","async def get_peak_loop(self):\n while True:\n try:\n self.blockchain_state = await self.node_rpc_client.get_blockchain_state()\n self.wallet_synced = await self.wallet_rpc_client.get_synced()\n await asyncio.sleep(30)\n except asyncio.CancelledError:\n self.log.info(\"Cancelled get_peak_loop, closing\")\n return\n except Exception as e:\n self.log.error(f\"Unexpected error in get_peak_loop: {e}\")\n await asyncio.sleep(30)","async def get_peak_loop(self):\n while True:\n try:\n self.blockchain_state = await self.node_rpc_client.get_blockchain_state()\n self.wallet_synced = await self.wallet_rpc_client.get_synced()\n await asyncio.sleep(30)\n except asyncio.CancelledError:\n self.log.info(\"Cancelled get_peak_loop, closing\")\n return\n except Exception as e:\n self.log.error(f\"Unexpected error in get_peak_loop: {e}\")\n await asyncio.sleep(30)","def run_metropolis_PBC(self):\n\n # Initialize the posistions for each new Monte Carlo run\n positions = np.random.rand(self.num_p, self.num_d)\n # Initialize the distance matrix\n self.s.positions_distances_PBC(positions)\n # check if the wave function is zero\n while True:\n test_wavefunction = self.w.wavefunction(positions)\n if test_wavefunction**2 <= 1e-14:\n # print ('obs')\n # Initialize the posistions for each new Monte Carlo run\n positions = np.random.rand(self.num_p, self.num_d)\n # Initialize the distance matrix\n self.s.positions_distances_PBC(positions)\n else:\n break\n # Initialize sampler method for each new Monte Carlo run\n self.sam.initialize()\n\n for i in range(self.mc_cycles):\n new_positions = self.metropolis_step_PBC(positions)\n positions = new_positions\n self.sam.sample_values(positions)\n\n self.sam.average_values(self.mc_cycles)\n energy = self.sam.local_energy\n d_El = self.sam.derivative_energy\n var = self.sam.variance\n print ('w = ', self.w.wavefunction(positions))\n self.print_averages()\n return d_El, energy, var","def fatal_error_processor(self):\n while True:\n _ = (yield)\n self.failed = True\n self.converged = False\n self.solve_completed = False","def _monitor_loop(self):\n while self._continue_running():\n for wl in self._workloads:\n if not wl.running():\n self.log.info('%-20s FAILED', wl.name())\n self._restart_workload(wl)\n else:\n self.log.info('%-20s OK', wl.name())\n\n time.sleep(self._monitor_delay)","def run(self):\n\n while not self.__done:\n self.single_cycle()\n\n \"\"\"\n while not self.__done:\n self.step()\n self.debug()\n \"\"\"","def test_shd_should_not_crash_executed_heal_info(self):\n # pylint: disable=too-many-statements\n bricks_list = get_all_bricks(self.mnode, self.volname)\n # Setting options\n g.log.info('Setting options...')\n options = {\"metadata-self-heal\": \"off\",\n \"entry-self-heal\": \"off\",\n \"data-self-heal\": \"off\"}\n ret = set_volume_options(self.mnode, self.volname, options)\n self.assertTrue(ret, 'Failed to set options %s' % options)\n g.log.info(\"Successfully set %s for volume %s\",\n options, self.volname)\n\n # Creating files on client side\n for mount_obj in self.mounts:\n g.log.info(\"Generating data for %s:%s\",\n mount_obj.client_system, mount_obj.mountpoint)\n # Create files\n g.log.info('Creating files...')\n command = (\"python %s create_files -f 10 --fixed-file-size 1M %s\"\n % (self.script_upload_path, mount_obj.mountpoint))\n\n proc = g.run_async(mount_obj.client_system, command,\n user=mount_obj.user)\n self.all_mounts_procs.append(proc)\n self.io_validation_complete = False\n\n # Validate IO\n self.assertTrue(\n validate_io_procs(self.all_mounts_procs, self.mounts),\n \"IO failed on some of the clients\"\n )\n self.io_validation_complete = True\n\n # Bring brick0 offline\n g.log.info('Bringing bricks %s offline', bricks_list[0])\n ret = bring_bricks_offline(self.volname, bricks_list[0])\n self.assertTrue(ret, 'Failed to bring bricks %s offline'\n % bricks_list[0])\n\n ret = are_bricks_offline(self.mnode, self.volname,\n [bricks_list[0]])\n self.assertTrue(ret, 'Bricks %s are not offline'\n % bricks_list[0])\n g.log.info('Bringing bricks %s offline is successful',\n bricks_list[0])\n\n # Creating files on client side\n number_of_files_one_brick_off = '1000'\n self.all_mounts_procs = []\n for mount_obj in self.mounts:\n g.log.info(\"Generating data for %s:%s\",\n mount_obj.client_system, mount_obj.mountpoint)\n # Create files\n g.log.info('Creating files...')\n command = (\"python %s create_files \"\n \"-f %s \"\n \"--fixed-file-size 1k \"\n \"--base-file-name new_file \"\n \"%s\"\n % (self.script_upload_path,\n number_of_files_one_brick_off,\n mount_obj.mountpoint))\n\n proc = g.run_async(mount_obj.client_system, command,\n user=mount_obj.user)\n self.all_mounts_procs.append(proc)\n self.io_validation_complete = False\n\n # Validate IO\n self.assertTrue(\n validate_io_procs(self.all_mounts_procs, self.mounts),\n \"IO failed on some of the clients\"\n )\n self.io_validation_complete = True\n\n # Get heal info\n g.log.info(\"Getting heal info...\")\n heal_info_data = get_heal_info_summary(self.mnode, self.volname)\n self.assertIsNotNone(heal_info_data, 'Failed to get heal info.')\n g.log.info('Success in getting heal info')\n\n # Check quantity of file pending heal\n for brick in bricks_list[1:]:\n self.assertEqual(heal_info_data[brick]['numberOfEntries'],\n str(int(number_of_files_one_brick_off)+1),\n 'Number of files pending heal is not correct')\n\n # Setting options\n g.log.info('Setting options...')\n options = {\"performance.enable-least-priority\": \"enable\"}\n ret = set_volume_options(self.mnode, self.volname, options)\n self.assertTrue(ret, 'Failed to set options %s' % options)\n g.log.info(\"Successfully set %s for volume %s\",\n options, self.volname)\n\n # Bring brick1 offline\n g.log.info('Bringing bricks %s offline', bricks_list[1])\n ret = bring_bricks_offline(self.volname, bricks_list[1])\n self.assertTrue(ret, 'Failed to bring bricks %s offline'\n % bricks_list[1])\n\n ret = are_bricks_offline(self.mnode, self.volname,\n [bricks_list[1]])\n self.assertTrue(ret, 'Bricks %s are not offline'\n % bricks_list[1])\n g.log.info('Bringing bricks %s offline is successful',\n bricks_list[1])\n\n # Setting options\n g.log.info('Setting options...')\n options = {\"quorum-type\": \"fixed\"}\n ret = set_volume_options(self.mnode, self.volname, options)\n self.assertTrue(ret, 'Failed to set options %s' % options)\n g.log.info(\"Successfully set %s for volume %s\",\n options, self.volname)\n\n # Creating files on client side\n number_of_files_two_brick_off = '100'\n self.all_mounts_procs = []\n for mount_obj in self.mounts:\n g.log.info(\"Generating data for %s:%s\",\n mount_obj.client_system, mount_obj.mountpoint)\n # Create files\n g.log.info('Creating files...')\n command = (\"python %s create_files \"\n \"-f %s \"\n \"--fixed-file-size 1k \"\n \"--base-file-name new_new_file \"\n \"%s\"\n % (self.script_upload_path,\n number_of_files_two_brick_off,\n mount_obj.mountpoint))\n\n proc = g.run_async(mount_obj.client_system, command,\n user=mount_obj.user)\n self.all_mounts_procs.append(proc)\n self.io_validation_complete = False\n\n # Validate IO\n self.assertTrue(\n validate_io_procs(self.all_mounts_procs, self.mounts),\n \"IO failed on some of the clients\"\n )\n self.io_validation_complete = True\n\n # Get heal info\n g.log.info(\"Getting heal info...\")\n heal_info_data = get_heal_info_summary(self.mnode, self.volname)\n self.assertIsNotNone(heal_info_data, 'Failed to get heal info.')\n g.log.info('Success in getting heal info')\n\n # Check quantity of file pending heal\n number_of_files_to_check = str(int(number_of_files_one_brick_off) +\n int(number_of_files_two_brick_off) + 1)\n self.assertEqual(heal_info_data[bricks_list[-1]]['numberOfEntries'],\n number_of_files_to_check,\n 'Number of files pending heal is not correct')"],"string":"[\n \"def test_molecule_loop_no_selection(self):\\n\\n # Molecule data.\\n name = ['Ap4Aase', 'RNA']\\n\\n # Loop over the molecules.\\n i = 0\\n for mol in mol_res_spin.molecule_loop():\\n # Test the molecule names.\\n self.assertEqual(mol.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_molecule_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for molecule in mol_res_spin.molecule_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_molecule_loop(self):\\n\\n # Loop over the molecules.\\n for mol in mol_res_spin.molecule_loop('#RNA'):\\n # Test the molecule name.\\n self.assertEqual(mol.name, 'RNA')\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_spin_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for spin in mol_res_spin.spin_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_residue_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for residue in mol_res_spin.residue_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def test_spin_loop_no_selection(self):\\n\\n # Spin data.\\n select = [0, 1, 0, 0, 1, 1, 0, 1]\\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 8)\",\n \"def test_spin_loop(self):\\n\\n # Spin data.\\n select = [1, 0]\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, 'N5')\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 2)\",\n \"def test_run_molecule_not_selected(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\", sequence, molecule_selector=lambda mol: False\\n )\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert vermouth.utils.are_all_equal(found)\\n assert found[0] is None\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def run(self):\\n while True:\\n if self.job_q.empty():\\n self.message_q.put(False)\\n return\\n try:\\n smolecule = self.job_q.get()\\n self.data_pointer[smolecule].get_adp(self.Temp)\\n except IndexError:\\n self.message_q.put((smolecule, None))\\n try:\\n self.message_q.put((smolecule, [j.adp['cart_int'] for j in self.data_pointer[smolecule].atoms]))\\n except KeyError:\\n # =======================================================\\n # self.message_q.put((molecule,[0 for i in self.data_pointer[molecule].atoms]))\\n #=======================================================\\n pass\",\n \"def test_spin_loop_multiatom(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_run_loop_success(self):\\n found = False\\n pyint = Interpreter(limit=15)\\n try:\\n pyint.run(code=BF_CODE_LOOP_TWICE)\\n except SystemExit: \\n found = True\\n self.assertFalse(found)\",\n \"def test_return_molecule_pipe_fail(self):\\n\\n # Try to get a molecule from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')\",\n \"def test_spin_loop_wildcard(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N*'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def loop(self):\\n raise NotImplementedError()\",\n \"def _run(self):\\n while(self._loop):\\n pass\",\n \"async def checkNewLoop(self):\\n pass\",\n \"def test_residue_loop(self):\\n\\n # Loop over the residues.\\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\\n # Test the selection.\\n self.assertEqual(res.num, 2)\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)\",\n \"def loop(self):\\n pass\",\n \"def test_return_molecule(self):\\n\\n # Ask for a few molecules.\\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\\n\\n # Test the data of molecule 1.\\n self.assertEqual(mol1.name, 'Ap4Aase')\\n\\n # Test the data of molecule 2.\\n self.assertEqual(mol2.name, 'RNA')\",\n \"def test_single_molecules_cycle_one(self, single_mol_system):\\n sequence = \\\"A\\\"\\n expected = [sequence] * (5 * 3)\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def test_multi_molecules_cycle_one(self, multi_mol_system_irregular):\\n sequence = \\\"A\\\"\\n expected = [sequence] * (15 * 3)\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_irregular)\\n found = self.sequence_from_system(multi_mol_system_irregular, \\\"test\\\")\\n assert found == expected\",\n \"def test_no_immediate_stop(self):\\n script = ControlScript()\\n options = ControlOptions()\\n options.parseOptions([b\\\"--data-path\\\", self.mktemp()])\\n self.assertNoResult(script.main(MemoryCoreReactor(), options))\",\n \"def test_run_molecule(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def run(self):\\n while True:\\n try:\\n self.check_value()\\n except Exception as e:\\n print(f\\\"[ERROR]: Error running the continuous run loop on sample_module: {e}\\\")\\n continue\",\n \"def test_reset(self):\\n ran = []\\n def foo():\\n ran.append(None)\\n\\n c = task.Clock()\\n lc = TestableLoopingCall(c, foo)\\n lc.start(2, now=False)\\n c.advance(1)\\n lc.reset()\\n c.advance(1)\\n self.assertEqual(ran, [])\\n c.advance(1)\\n self.assertEqual(ran, [None])\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_circularloop(self):\\n cmd = f\\\"{SRC_LISTER} -i {PWD}/main\\\"\\n with subprocess.Popen(\\n shlex.split(cmd), stdout=subprocess.PIPE, stderr=subprocess.PIPE\\n ) as proc:\\n try:\\n out, err = proc.communicate(timeout=5)\\n assert len(err.strip()) > 0, \\\"Expected a circular reference error\\\"\\n except subprocess.TimeoutExpired as te:\\n print(\\\"Unexpected parser timeout during infinite loop test\\\")\",\n \"def test_multi_molecules_cycle(self, multi_mol_system_regular, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n expected = expected * 3\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_regular)\\n found = self.sequence_from_system(multi_mol_system_regular, \\\"test\\\")\\n assert found == expected\",\n \"def algorithm_loop(self):\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"async def hold_loop(self, *args) -> bool:\\n raise NotImplementedError\",\n \"def test_noFailure(self):\\n for i in range(10):\\n self.assertTrue(self.circuit_breaker.available())\",\n \"def test_block_missing_batch(self):\\n pass\",\n \"def test_empty_with_filter(multi_mol_system_irregular):\\n sequence = \\\"not empty\\\"\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\", sequence, molecule_selector=lambda mol: False\\n )\\n with pytest.raises(ValueError):\\n processor.run_system(multi_mol_system_irregular)\",\n \"def infinite_loop():\\n return True\",\n \"def _loop_raw(raw):\\n raise NotImplemented\",\n \"def run_one_test_cycle(self):\\n logging.info(\\n \\\"{0} operations remaining: {1}\\\".format(\\n self.args.pm_operation, self.args.repetitions\\n )\\n )\\n\\n self.check_last_cycle_duration()\\n if self.args.repetitions > 0:\\n self.run_pm_command()\\n else:\\n self.summary()\",\n \"def _while_loop(pd, nmax, max_loop, ncore, outfile):\\n \\n # make sure the random seed is different for every processor\\n random_number_seeds = [3456789, 7654321, 2435467, 8273645,\\n 1085712, 4154712, 1248291, 8415917,\\n 2345161, 5710916, 5718601, 7516234,\\n 9235161, 4917519, 1111245, 8167834] \\n \\n # get the processor ID (1 - Ncore) and convert to single integer\\n current = multiprocessing.current_process()\\n pid = current._identity\\n pid = pid[0]\\n \\n #\\n # choose a different seed for each processor from the list so each processor has\\n # a different randum number seed. Then, fiddle with each seed a little so \\n # the seeds aren't the same every time the code is run\\n seed = np.int(random_number_seeds[pid] * (np.random.rand()*(10.0 - 0.01) + 0.01))\\n \\n np.random.seed(seed)\\n \\n #print 'id and seed', pid, seed\\n \\n n_particles = 0\\n loop_counter = 0\\n fmin_scale = 1.0E-100 # -16 -> -32 -> -100\\n F_max = np.max(pd.DF.f) #; F_min = np.min(pd.DF.f);\\n F_min = np.min(pd.DF.f) * fmin_scale\\n # F_max = np.max(pd.DF.f[:-1])#; F_max = 1.0E-88\\n #print F_min, F_max\\n if pd.optimize:\\n relative_potential = pd._interpolate_relative_potential\\n else:\\n relative_potential = pd.DF.relative_potential\\n \\n \\n pos = np.zeros((nmax, 3))\\n vel = np.zeros((nmax, 3)) \\n \\n while (( n_particles < nmax) and (loop_counter < max_loop)):\\n \\n r = pd._choose_position()\\n Psi = relative_potential(r) \\n \\n v = pd._choose_velocity(r, Psi)\\n \\n E = Psi - 0.5 * v * v\\n \\n f_E = pd.DF.interpolate_f(E)\\n \\n logF = ( np.random.rand()*(np.log10(F_max) - np.log10(F_min)) + np.log10(F_min) )\\n \\n # if choosing random F in log F, might be good to do the comparison in logspace as well\\n #.... i.e log(F) <= log(f_E) \\n #\\n # 0 FOR F_E MEANS THAT E < E_min of the potential. THis happens when Psi - KE is smaller\\n # than the value of the potential at large_r... should this be considered unbound \\n # even though it isn't zero? Is this effectively zero? This has been adjusted in the velocity\\n # picking routine but needs verification to make sure it works.... but regardless, I doubt\\n # that this is the reason why the particles are failing for NFW but working for hernquist....\\n #\\n if np.abs(np.log10(f_E)) == np.inf:\\n keep_particle = False\\n _my_print('log value error... throwing out particle')\\n else:\\n keep_particle = (logF <= np.log10(f_E))\\n\\n \\n if keep_particle: \\n index = n_particles \\n \\n # \\n # need to sample in cosine theta NOT theta!!!!! WTF!!!!!\\n #\\n #\\n \\n theta = np.arccos( np.random.rand() * (2.0) - 1.0)\\n \\n # convert position to cartesian using random theta and phi\\n phi = np.random.rand() * 2.0 * np.pi\\n \\n x = np.sin(theta) * np.cos(phi)\\n y = np.sin(theta) * np.sin(phi)\\n z = np.cos(theta)\\n \\n pos[index] = r * np.array([x,y,z])\\n\\n # repeat for velocity using new random numbersw\\n theta = np.arccos( np.random.rand() * (2.0) - 1.0)\\n phi = np.random.rand() * 2.0 * np.pi\\n \\n vx = np.sin(theta) * np.cos(phi)\\n vy = np.sin(theta) * np.sin(phi)\\n vz = np.cos(theta)\\n \\n vel[index] = v * np.array([vx,vy,vz])\\n \\\"\\\"\\\" \\n #else: # do strict cartesian ... slower.... less attractive\\n # \\n # axis_list = [0, 1, 2]\\n # random.shuffle(axis_list)\\n \\n # #axis_index = np.random.randint(3)\\n # first_axis = axis_list[0]\\n #\\n # pos[index, first_axis] = np.random.rand() * (2.0*r) - r\\n #del axis_list[axis_index]\\n \\n #axis_index = np.random.randint(2)\\n # second_axis = axis_list[1]\\n \\n max_r = np.sqrt(r*r - pos[index,first_axis]**2)\\n \\n pos[index, second_axis] = np.random.rand()*(2.0 * max_r) - max_r\\n #del axis_list[axis_index]\\n \\n max_r = np.sqrt(r*r - pos[index,first_axis]**2 - pos[index,second_axis]**2)\\n \\n third_axis = axis_list[2]\\n pos[index, third_axis] = np.random.rand() * (2.0 * max_r) - max_r\\n \\n if np.sqrt(pos[index,0]**2 + pos[index,1]**2 + pos[index,2]**2) > r:\\n _my_print('R IS TOO LARGE')\\n \\n ###\\n axis_list = [0, 1, 2]\\n random.shuffle(axis_list)\\n \\n #axis_index = np.random.randint(3)\\n first_axis = axis_list[0]\\n \\n vel[index, first_axis] = np.random.rand() * (2.0*v) - v\\n #del axis_list[axis_index]\\n \\n #axis_index = np.random.randint(2)\\n second_axis = axis_list[1]\\n \\n max_v = np.sqrt(v*v - vel[index,first_axis]**2)\\n \\n vel[index, second_axis] = np.random.rand()*(2.0 * max_v) - max_v\\n #del axis_list[axis_index]\\n \\n max_v = np.sqrt(v*v - vel[index,first_axis]**2 - vel[index,second_axis]**2)\\n \\n third_axis = axis_list[2]\\n vel[index, third_axis] = np.random.rand() * (2.0 * max_v) - max_v \\n \\n \\n \\\"\\\"\\\"\\n n_particles = n_particles + 1\\n \\n if (loop_counter % 5000) == 0:\\n _my_print(\\\"Have %4i particles. On loop %6i\\\"%(n_particles, loop_counter))\\n loop_counter = loop_counter + 1\\n \\n # now write out to a temporary file\\n f = open(outfile + \\\"_%02i_\\\"%(pid) + \\\".temp\\\", 'w')\\n fmt = \\\"%12.12E %12.12E %12.12E %12.12E %12.12E %12.12E %12.12E\\\\n\\\"\\n \\n \\n for i in np.arange(nmax):\\n f.write(fmt%(pd.M_part, pos[i,0], pos[i,1], pos[i,2], \\n vel[i,0], vel[i,1], vel[i,2]))\\n \\n \\n f.close() \\n \\n return pos, vel\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def do_simulation_loop(self) -> tuple[bool, bool]:\\n running, reset = True, False\\n for event in pygame.event.get():\\n if check_for_quit(event):\\n running = False\\n elif check_for_reset(event):\\n running = False\\n reset = True\\n self.simulation.do_step()\\n self.update_visualization()\\n self.simple_pygame.loop()\\n return running, reset\",\n \"async def loop():\\n # ArmDevice.storage.joints_pos = await get_positions() # Use this if encoders are wired up.\\n # ArmDevice.storage.joints_pos = simulate_positions() # Use this for testing without position feedback.\\n log.debug(\\\"command: {}\\\".format(ArmDevice.storage.command))\\n ArmDevice.storage.controller.user_command(ArmDevice.storage.mode, *ArmDevice.storage.command)\\n ArmDevice.storage.speeds = ArmDevice.storage.controller.update_duties(ArmDevice.storage.joints_pos)\\n\\n # publish speeds/duty cycles here\\n log.debug(\\\"joints_pos: {}\\\".format(ArmDevice.storage.joints_pos))\\n log.debug(\\\"speeds: {}\\\".format(ArmDevice.storage.speeds))\\n await send_duties()\",\n \"def run_no_input(self, initial=None, context=None):\\n for _ in self.run(initial, context):\\n raise RuntimeError(\\\"Machine requires input to continue!\\\")\",\n \"def test_control_loop_example():\\n example.control.print_error_measurement()\\n matplotlib.use('agg')\\n example.control.visualise_error_measurement(fig_file='cs_compare.pdf')\\n assert path.isfile('cs_compare.pdf')\\n example.control.sil_comparison()\",\n \"def _handle_loop(self):\\n pass\",\n \"def run_until_stop(self):\\n while self.commands[self.pointer] != END:\\n # Get the cmd\\n cmd = self.commands[self.pointer]\\n opcode = cmd % 100\\n modes = cmd // 100\\n \\n vals, locs, self.pointer = get_vals_and_locs(opcode, modes, self.pointer, self.commands)\\n \\n if opcode == ADD:\\n self.commands[locs[2]] = vals[0] + vals[1]\\n elif opcode == MUL:\\n self.commands[locs[2]] = vals[0] * vals[1]\\n elif opcode == INP:\\n if self.inputs:\\n self.commands[locs[0]] = self.inputs.pop(0)\\n else:\\n # Put the pointer back, so we run this opcode again\\n self.pointer -= 2\\n return False\\n elif opcode == OUT:\\n self.outputs.append(vals[0])\\n elif opcode == JIT:\\n if vals[0] != 0:\\n self.pointer = vals[1]\\n elif opcode == JIF:\\n if vals[0] == 0:\\n self.pointer = vals[1]\\n elif opcode == LT:\\n self.commands[locs[2]] = 1 if vals[0] < vals[1] else 0\\n elif opcode == EQ:\\n self.commands[locs[2]] = 1 if vals[0] == vals[1] else 0\\n else:\\n print(\\\"FAIL????\\\")\\n\\n return True\",\n \"def test_empty_input_data(self):\\n self.data.diffusion_data = np.array([])\\n self.assertRaises(ValueError, module_05.run_module,\\n self.data)\",\n \"def test_readiness(self):\\n self.command.package = self.input_ovf\\n ready, reason = self.command.ready_to_run()\\n self.assertFalse(ready)\\n self.assertRegex(reason, \\\"No file information\\\")\\n self.assertRaises(InvalidInputError, self.command.run)\\n\\n self.command.file_path = \\\"input.vmdk\\\"\\n ready, reason = self.command.ready_to_run()\\n self.assertTrue(ready)\\n\\n self.command.file_path = None\\n self.command.file_id = \\\"file1\\\"\\n ready, reason = self.command.ready_to_run()\\n self.assertTrue(ready)\",\n \"def test_run_loop_exc(self):\\n with self.assertRaises(ExecutionException):\\n pyint = Interpreter(limit=1)\\n pyint.run(code=BF_CODE_LOOP_TWICE)\",\n \"def run_nop(self):\\n pass\",\n \"def test_sync_task_no_server(comm):\\n run_server, server_args, run_client, client_args = helper_config(comm, \\\"sync\\\")\\n client = run_client(**client_args)\\n try:\\n client.connect()\\n except Exception as exc: # pylint: disable=broad-except\\n assert False, f\\\"unexpected exception: {exc}\\\"\\n sleep(0.1)\\n if comm == \\\"udp\\\":\\n rr = client.read_coils(1, 1, slave=0x01)\\n assert isinstance(rr, ModbusIOException)\\n else:\\n with pytest.raises((asyncio.exceptions.TimeoutError, ConnectionException)):\\n client.read_coils(1, 1, slave=0x01)\\n client.close()\",\n \"def test_for_restart(self):\\n #print(\\\"entering test_for_restart()\\\")\\n self._compile_result(\\\"UserName: \\\" + self.user_name)\\n #if self.first_song == True:\\n # msg = \\\"Welcome_str\\\"\\n # self.first_song = False\\n if self._feedback_plat == \\\"RIVA\\\":\\n self._RIVA_message_num += 1\\n text_to_RIVA(\\\"Welcome_str\\\")\\n else:# self._feedback_plat == \\\"Text\\\":\\n self._RIVA_message_num += 1\\n #to_no_voice_log(\\\"NewData:{};TTS:{}\\\".format(self._RIVA_message_num, msg))\\n ###else:\\n ### text_to_ispeech(ispeech_formatter(msg))\\n while True:\\n self._check_completion()\\n if self._song_over is False:\\n print(\\\"Song Started\\\")\\n if self._feedback_plat == \\\"RIVA\\\":\\n reset_RIVA_log()\\n self._RIVA_message_num += 1\\n #text_to_RIVA(self.response_welcome())\\n elif self._feedback_plat == \\\"Text\\\":\\n to_no_voice_log((emo_less_feedback(0, 0, 0)))\\n self.execute_song()\\n print(\\\"Re-entered Test_for_restart()\\\")\\n if self._song_over is True:\\n interface_info = gather_info(\\n parse_csv(read_csv(CSV_functions.MUSICGLOVE)))\\n #print(interface_info)\\n #print(\\\"Song_over min/max = \\\", min_max)\\n self.user_stats.set_grips(interface_info)\\n self._compile_result(grip_avg_summary_str(interface_info))\\n evaluated_info = [evaluate_worst_grip(interface_info, self._last_worst_grip),\\n evaluate_best_grip(interface_info)]\\n summary = summary_generator(evaluated_info[0], evaluated_info[1])\\n if self._feedback_plat == \\\"RIVA\\\":\\n self._RIVA_message_num += 1\\n #print(\\\"message_num={} summary={}\\\".format(self._message_num, summary))\\n text_to_RIVA(summary)\\n else:# self._feedback_plat == \\\"Text\\\":\\n to_no_voice_log(emo_less_feedback(self._RIVA_message_num, evaluated_info[0], evaluated_info[1]))\\n ###else:\\n ### text_to_ispeech(ispeech_formatter(summary))\\n self._last_30_sec = []\\n self._compile_result(summary)\\n self._csv_result.extend(read_csv(CSV_functions.MUSICGLOVE))\\n make_csv(self._csv_result, CSV_functions.M_GLOVE_SUMMARIES, what_song(self._grip_count))\\n self.__init__(self.user_name, restart=True)\\n self._RIVA_message_num = 1\\n else:\\n pass\\n return\",\n \"def test_modul1(self):\\n\\n self.delayDisplay(\\\"Starting the test\\\")\\n #\\n # first, get some data\\n #\\n import urllib\\n downloads = (\\n ('http://slicer.kitware.com/midas3/download?items=5767', 'FA.nrrd', slicer.util.loadVolume),\\n )\\n\\n for url,name,loader in downloads:\\n filePath = slicer.app.temporaryPath + '/' + name\\n if not os.path.exists(filePath) or os.stat(filePath).st_size == 0:\\n logging.info('Requesting download %s from %s...\\\\n' % (name, url))\\n urllib.urlretrieve(url, filePath)\\n if loader:\\n logging.info('Loading %s...' % (name,))\\n loader(filePath)\\n self.delayDisplay('Finished with download and loading')\\n\\n volumeNode = slicer.util.getNode(pattern=\\\"FA\\\")\\n logic = modulLogic()\\n self.assertTrue( logic.hasImageData(volumeNode) )\\n self.delayDisplay('Test passed!')\",\n \"def _readloop(self):\\r\\n\\r\\n while self._ll_alive:\\r\\n with self._rx_lock:\\r\\n data = self._Random(1)\\r\\n if len(data) != 0: # check for timeout\\r\\n self._uart_rx_queue.put(data)\",\n \"def nanny(self): \\n while not self.started and not self.failed:\\n eventlet.sleep(.1)\\n return not self.failed\",\n \"def test_single_molecule(self, single_mol_system, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def test_stream_loop(self):\\n chans, gains, scans, rate = (10,10,10,10), (1,2,4,5), 1024, 500\\n v = [v[0] for v in self.l.stream_sync(\\n channels=chans, gains=gains,\\n num_scans=scans, rate=rate)]\\n for vi in v:\\n for r in vi:\\n self.assertTrue(abs(r-2.5) < .1,\\n \\\"%s should be cal, 2.5v\\\" % vi[0])\",\n \"def test_compute_bulkiness(tmp_path: Path):\\n df = read_molecules(PATH_TEST / \\\"smiles_carboxylic.csv\\\")\\n opts = create_options(tmp_path)\\n\\n data = compute_batch_bulkiness(df.smiles, opts, pd.Index(list(range(4))))\\n assert not np.all(np.isnan(data))\",\n \"def worker(self, loop):\\n # CONNECTION LOOP\\n while True:\\n # if we are in reconnect status, sleep before connecting\\n if self.reconnect_time > 0:\\n yield from asyncio.sleep(1)\\n\\n # if we've been reconnecting for over 60s, bail out\\n if (time.time() - self.reconnect_time) > 60:\\n self.logger.error(\\\"Could not reconnect to mochad after 60s\\\")\\n loop.stop()\\n break\\n\\n try:\\n yield from self.connect()\\n except OSError as e:\\n if self.reconnect_time == 0:\\n self.reconnect_time = time.time()\\n self.logger.warn(\\n \\\"Could not connect to mochad. Retrying: {}\\\".format(e))\\n # reconnect_time = -1 here means the first connection failed\\n elif self.reconnect_time == -1:\\n self.logger.error(\\n \\\"Could not connect to mochad: {}\\\".format(e))\\n loop.stop()\\n break\\n\\n # keep trying to reconnect\\n continue\\n\\n # if we make it this far we've successfully connected, reset the\\n # reconnect time\\n self.reconnect_time = 0\\n self.logger.info(\\\"Connected to mochad\\\")\\n\\n # READ FROM NETWORK LOOP\\n while True:\\n line = yield from self.reader.readline()\\n # an empty string means connection lost, exit read loop\\n if not line and self.reader.at_eof():\\n break\\n # parse the line\\n try:\\n addr, message_dict, kind = self.parse_mochad_line(\\n line.decode(\\\"utf-8\\\").rstrip())\\n except Exception as e:\\n self.logger.error(\\n \\\"Failed to parse mochad message {}: {}\\\".format(\\n line, e))\\n continue \\n\\n # addr/func will be blank when we have nothing to dispatch\\n if addr and message_dict:\\n # we don't to use mochad's timestamp because it lacks a year\\n message_dict['dispatch_time'] = datetime.now(\\n pytz.UTC).isoformat()\\n\\n asyncio.async(self.dispatch_message(addr, message_dict, kind))\\n\\n\\n # we broke out of the read loop: we got disconnected, retry connect\\n self.logger.warn(\\\"Lost connection to mochad. Retrying.\\\")\\n self.reconnect_time = time.time()\",\n \"def _run(self):\\n logging.warning('-> perform EMPTY experiment...')\",\n \"def test_chunk_pauli(self, method, device):\\n opts_no_chunk = {\\\"fusion_enable\\\": False}\\n opts_chunk = copy.copy(opts_no_chunk)\\n opts_chunk[\\\"blocking_enable\\\"] = True\\n opts_chunk[\\\"blocking_qubits\\\"] = 3\\n\\n backend = self.backend(method=method, device=device, **opts_chunk)\\n backend_no_chunk = self.backend(method=method, device=device, **opts_no_chunk)\\n\\n shots = 100\\n\\n qr = QuantumRegister(5)\\n cr = ClassicalRegister(5)\\n regs = (qr, cr)\\n circuit = QuantumCircuit(*regs)\\n circuit.h(qr[0])\\n circuit.h(qr[1])\\n circuit.h(qr[2])\\n circuit.h(qr[3])\\n circuit.h(qr[4])\\n circuit.pauli(\\\"YXZYX\\\", qr)\\n circuit.measure_all()\\n\\n result = backend.run(circuit, shots=shots, memory=True).result()\\n counts = result.get_counts(circuit)\\n result_no_chunk = backend_no_chunk.run(circuit, shots=shots, memory=True).result()\\n counts_no_chunk = result_no_chunk.get_counts(circuit)\\n\\n self.assertEqual(counts_no_chunk, counts)\",\n \"def has_no_yielded_molecules(self, batch: Batch[T]) -> bool:\\n return all(\\n self._key_maker.get_key(molecule) not in self._molecules\\n for molecule in (record.get_molecule() for record in batch)\\n )\",\n \"def testReset(self):\\n \\n clk = Signal(0)\\n rst = Signal(1)\\n clock_gen = ClkDriver(clk, period=4)\\n \\n out = Signal(intbv(0)[4:])\\n counter = Counter(out, clk, rst)\\n \\n def test():\\n for i in range(200):\\n # count up to 9 then reset\\n if int(out) == 9:\\n rst.next = 0\\n yield delay(1)\\n self.assertEqual(int(out), 0)\\n # turn off reset next time\\n else:\\n rst.next = 1\\n yield delay(1)\\n \\n check = test()\\n sim = Simulation(counter, clock_gen, check)\\n sim.run(400, quiet=1)\",\n \"def test_run_simulation_returns_nothing(self):\\n sim = ss.Simulation()\\n assert sim.run_simulation(10) is None\",\n \"def run(self):\\n\\n if self.success and not self.running:\\n self.log.info(\\\"Humidity and temp control started...\\\")\\n self.running = True\\n elif self.testmode and not self.running:\\n self.log.critical(\\\"Humidity and temp TEST MODE started!!!\\\")\\n self.running = True\\n elif not self.running:\\n self.log.info(\\\"Humidity and temp control NOT started...\\\")\\n return\\n\\n if not self.stop_measurement_loop and self.success:\\n try:\\n # Query the environemnt etc from Brandbox\\n envvalues = self.vcw.query(\\n self.resource, self.resource[\\\"get_environment\\\"]\\n )\\n envvalues = envvalues.split(\\\",\\\")\\n\\n # Get dewpoint\\n boxvalues = self.vcw.query(\\n self.resource, self.resource[\\\"get_box_environment\\\"]\\n )\\n boxvalues = boxvalues.split(\\\",\\\")\\n\\n vacuumvalues = self.vcw.query(\\n self.resource, self.resource[\\\"get_vacuum\\\"]\\n )\\n\\n # get light\\n luxvalues = self.vcw.query(self.resource, self.resource[\\\"get_lux\\\"])\\n luxvalues = luxvalues.split(\\\",\\\")[0]\\n\\n # if an error happen, as so often with the brandbox read the queue\\n if self.readqueue:\\n try:\\n ans = self.vcw.read(self.resource)\\n if ans:\\n self.log.critical(\\\"Brandbox had an non empty queue: {}\\\".format(ans))\\n except:\\n self.log.info(\\\"Brandbox indicated an non empty queue, reading queue yielded no queue...\\\", exc_info=True)\\n\\n\\n try:\\n if float(luxvalues) >= 0.5:\\n self.framework[\\\"Configs\\\"][\\\"config\\\"][\\\"settings\\\"][\\\"lights\\\"] = True\\n else:\\n self.framework[\\\"Configs\\\"][\\\"config\\\"][\\\"settings\\\"][\\\"lights\\\"] = False\\n\\n # get door\\n # doorvalues = self.vcw.query(self.resource, self.resource[\\\"get_door\\\"])\\n # doorvalues = doorvalues.split(\\\",\\\")[0]\\n # if doorvalues == \\\"1\\\":\\n # self.framework[\\\"Configs\\\"][\\\"config\\\"][\\\"settings\\\"][\\\"door\\\"] = False\\n # else:\\n # self.framework[\\\"Configs\\\"][\\\"config\\\"][\\\"settings\\\"][\\\"door\\\"] = True\\n\\n # get light\\n vacuumvalues = vacuumvalues.split(\\\",\\\")[0]\\n if vacuumvalues == \\\"1\\\":\\n self.framework[\\\"Configs\\\"][\\\"config\\\"][\\\"settings\\\"][\\\"vacuum\\\"] = True\\n else:\\n self.framework[\\\"Configs\\\"][\\\"config\\\"][\\\"settings\\\"][\\\"vacuum\\\"] = False\\n\\n # Here a list\\n self.main.humidity_history = np.append(\\n self.main.humidity_history, float(envvalues[1])\\n ) # todo: memory leak since no values will be deleted\\n self.main.temperatur_history = np.append(\\n self.main.humidity_history, float(envvalues[3])\\n )\\n\\n # Write the pt100 and light status and environement in the box to the global variables\\n self.framework[\\\"Configs\\\"][\\\"config\\\"][\\\"settings\\\"][\\n \\\"chuck_temperature\\\"\\n ] = float(envvalues[3])\\n self.framework[\\\"Configs\\\"][\\\"config\\\"][\\\"settings\\\"][\\n \\\"air_temperature\\\"\\n ] = float(envvalues[0])\\n self.framework[\\\"Configs\\\"][\\\"config\\\"][\\\"settings\\\"][\\\"dew_point\\\"] = float(\\n boxvalues[3]\\n )\\n\\n # Send data to main\\n self.queue_to_main.put(\\n {\\n \\\"temperature_air\\\": [float(time()), float(envvalues[0])],\\n \\\"temperature_chuck\\\": [float(time()), float(envvalues[3])],\\n \\\"dew_point\\\": [float(time()), float(boxvalues[3])],\\n \\\"humidity\\\": [float(time()), float(envvalues[1])],\\n }\\n )\\n except:\\n self.readqueue = True\\n\\n except Exception as err:\\n self.log.error(\\n \\\"The temperature and humidity controller seems not to be responding. Error: {!s}\\\".format(\\n err\\n ),\\n exc_info=True,\\n )\\n\\n elif self.testmode:\\n self.log.critical(\\\"Testmode sends message to main!\\\")\\n self.queue_to_main.put(\\n {\\n \\\"temperature\\\": [float(time()), float(random.randint(1, 10))],\\n \\\"humidity\\\": [float(time()), float(random.randint(1, 10))],\\n }\\n )\\n\\n if not self.main.stop_measurement_loop:\\n self.start_timer(self.run)\\n else:\\n self.log.info(\\n \\\"Shutting down environment control due to stop of measurement loop\\\"\\n )\",\n \"def test_run_read(self):\\n\\n self.ictrl[0] = 1 + 2 + 4 + 8\\n vmec_f90wrap.runvmec(self.ictrl, self.filename, self.verbose, \\\\\\n self.fcomm, reset_file)\\n\\n self.assertTrue(self.ictrl[1] in success_codes)\\n\\n self.assertEqual(vmec_f90wrap.vmec_input.nfp, 3)\\n self.assertEqual(vmec_f90wrap.vmec_input.mpol, 4)\\n self.assertEqual(vmec_f90wrap.vmec_input.ntor, 3)\\n print('rbc.shape:', vmec_f90wrap.vmec_input.rbc.shape)\\n print('rbc:',vmec_f90wrap.vmec_input.rbc[101:103, 0:4])\\n\\n # n = 0, m = 0:\\n self.assertAlmostEqual(vmec_f90wrap.vmec_input.rbc[101,0], 1.3782)\\n\\n # n = 0, m = 1:\\n self.assertAlmostEqual(vmec_f90wrap.vmec_input.zbs[101,1], 4.6465E-01)\\n\\n # n = 1, m = 1:\\n self.assertAlmostEqual(vmec_f90wrap.vmec_input.zbs[102,1], 1.6516E-01)\\n\\n # Now try reading in the output\\n wout_file = os.path.join(os.path.dirname(__file__), 'wout_li383_low_res.nc')\\n ierr = 0\\n vmec_f90wrap.read_wout_mod.read_wout_file(wout_file, ierr)\\n self.assertEqual(ierr, 0)\\n self.assertAlmostEqual(vmec_f90wrap.read_wout_mod.betatot, \\\\\\n 0.0426215030653306, places=4)\\n\\n print('iotaf.shape:',vmec_f90wrap.read_wout_mod.iotaf.shape)\\n print('rmnc.shape:',vmec_f90wrap.read_wout_mod.rmnc.shape)\\n\\n self.assertAlmostEqual(vmec_f90wrap.read_wout_mod.iotaf[-1], \\\\\\n 0.654868168783638, places=4)\\n\\n self.assertAlmostEqual(vmec_f90wrap.read_wout_mod.rmnc[0, 0], \\\\\\n 1.4773028173065, places=4)\",\n \"async def hold_loop(self):\\n pass\",\n \"def test_io_counter_loop(self):\\n self.l.output(conf_io=0x8, state_io=0x0)\\n self.l.count(reset=True)\\n for i in range(10):\\n self.l.output(state_io=0x8)\\n self.l.output(state_io=0x0)\\n c, t = self.l.count()\\n self.assertEqual(c, 9,\\n \\\"counted %g pulses\\\" % c)\",\n \"def test_simulationRun(self):\\n self.opt = { 'temperature' : 300.0, 'friction' : 1, 'dt' : 0.00002,\\n 'nIter' : 2, 'nstepsNC' : 2, 'nstepsMD' : 1, 'nprop' : 1,\\n 'nonbondedMethod' : 'NoCutoff', 'constraints': 'HBonds',\\n 'trajectory_interval' : 1, 'reporter_interval' : 1,\\n 'outfname' : 'mc-test',\\n 'platform' : None,\\n 'constraints' : 'HBonds',\\n 'mc_per_iter' : 2 }\\n\\n structure = self.full_struct\\n class SetRotationMove(RandomLigandRotationMove):\\n def __init__(self, structure, resname='LIG'):\\n super(SetRotationMove, self).__init__(structure, resname)\\n\\n def move(self, context):\\n \\\"\\\"\\\"Function that performs a random rotation about the\\n center of mass of the ligand.\\n \\\"\\\"\\\"\\n #TODO: check if we need to deepcopy\\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\\n\\n self.positions = positions[self.atom_indices]\\n self.center_of_mass = self.getCenterOfMass(self.positions, self.masses)\\n reduced_pos = self.positions - self.center_of_mass\\n\\n # Define random rotational move on the ligand\\n #set rotation so that test is reproducible\\n set_rotation_matrix = np.array([[-0.62297988, -0.17349253, 0.7627558 ],\\n [ 0.55082352, -0.78964857, 0.27027502],\\n [ 0.55541834, 0.58851973, 0.58749893]])\\n\\n\\n #set_rotation_matrix = np.array([[1, 0, 0],\\n # [0, 1, 0],\\n # [0, 0, 1]])\\n\\n #multiply lig coordinates by rot matrix and add back COM translation from origin\\n rot_move = np.dot(reduced_pos, set_rotation_matrix) * positions.unit + self.center_of_mass\\n\\n # Update ligand positions in nc_sim\\n for index, atomidx in enumerate(self.atom_indices):\\n positions[atomidx] = rot_move[index]\\n context.setPositions(positions)\\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\\n self.positions = positions[self.atom_indices]\\n return context\\n\\n\\n self.model = SetRotationMove(structure, resname='ALA')\\n #self.model = RandomLigandRotationMove(structure, resname='ALA')\\n\\n self.model.atom_indices = range(22)\\n self.model.topology = structure[self.model.atom_indices].topology\\n self.model.positions = structure[self.model.atom_indices].positions\\n self.model.calculateProperties()\\n\\n self.mover = MoveEngine(self.model)\\n #Initialize the SimulationFactory object\\n sims = SimulationFactory(structure, self.mover, **self.opt)\\n #print(sims)\\n system = sims.generateSystem(structure, **self.opt)\\n simdict = sims.createSimulationSet()\\n alch_system = sims.generateAlchSystem(system, self.model.atom_indices)\\n self.nc_sim = sims.generateSimFromStruct(structure, self.mover, alch_system, ncmc=True, **self.opt)\\n self.model.calculateProperties()\\n self.initial_positions = self.nc_sim.context.getState(getPositions=True).getPositions(asNumpy=True)\\n mc_sim = Simulation(sims, self.mover, **self.opt)\\n #monkeypatch to access acceptance value\\n def nacceptRejectMC(self, temperature=300, **opt):\\n \\\"\\\"\\\"Function that chooses to accept or reject the proposed move.\\n \\\"\\\"\\\"\\n md_state0 = self.current_state['md']['state0']\\n md_state1 = self.current_state['md']['state1']\\n log_mc = (md_state1['potential_energy'] - md_state0['potential_energy']) * (-1.0/self.nc_sim.context._integrator.kT)\\n randnum = math.log(np.random.random())\\n\\n if log_mc > randnum:\\n self.accept += 1\\n print('MC MOVE ACCEPTED: log_mc {} > randnum {}'.format(log_mc, randnum) )\\n self.md_sim.context.setPositions(md_state1['positions'])\\n else:\\n self.reject += 1\\n print('MC MOVE REJECTED: log_mc {} < {}'.format(log_mc, randnum) )\\n self.md_sim.context.setPositions(md_state0['positions'])\\n self.log_mc = log_mc\\n self.md_sim.context.setVelocitiesToTemperature(self.opt['temperature'])\\n mc_sim.acceptRejectMC = nacceptRejectMC\\n nacceptRejectMC.__get__(mc_sim)\\n mc_sim.acceptRejectMC = types.MethodType(nacceptRejectMC, mc_sim)\\n mc_sim.runMC(self.opt['nIter'])\\n #get log acceptance\\n print(mc_sim.log_mc)\\n #if mc is working, should be around -24.1\\n assert mc_sim.log_mc <= -23.8 and mc_sim.log_mc >= -24.3\",\n \"def has_loop(self) -> bool:\\n try:\\n list(self)\\n return False\\n except ContainsLoopError:\\n return True\",\n \"def test_read_mol_input():\\n # good input\\n read_mol_input(os.path.join(TEST_DIR, \\\"example_mol_input_file.txt\\\"))\\n # good input with extra spaces\\n read_mol_input(os.path.join(TEST_DIR, \\\"example2_mol_input_file.txt\\\"))\\n # no such file error\\n assert_raises(FileNotFoundError, read_mol_input, 'no-such-file')\\n # qcm appears twice\\n assert_raises(ValueError, read_mol_input, os.path.join(TEST_DIR, \\\"bad1_mol_input_file.txt\\\"))\\n # missing struct type\\n assert_raises(ValueError, read_mol_input, os.path.join(TEST_DIR, \\\"bad2_mol_input_file.txt\\\"))\",\n \"def test_run(self):\\n engine = Engine(self.config_file, self.api_token, 23)\\n engine.msg_wait_iterations = 0\\n\\n # Put some stuff on the task queue\\n self.setup_helper.add_volumetric_tasks(self.aws_creds[\\\"access_key\\\"],\\n self.aws_creds['secret_key'],\\n self.upload_queue_url, engine.backend)\\n\\n engine.join()\\n engine.run()\\n\\n # Check for tile to exist\\n s3 = boto3.resource('s3')\\n ingest_bucket = s3.Bucket(self.ingest_bucket_name)\\n\\n with tempfile.NamedTemporaryFile() as test_file:\\n with open(test_file.name, 'wb') as raw_data:\\n ingest_bucket.download_fileobj(VOLUMETRIC_CUBOID_KEY, raw_data)\\n with open(test_file.name, 'rb') as raw_data:\\n # Using an empty CloudVolume dataset so all values should be 0.\\n # dtype set in boss-v0.2-test.json under chunk_processor.params.info.data_type\\n cuboid = self.s3_object_to_cuboid(raw_data.read(), 'uint8')\\n unique_vals = np.unique(cuboid)\\n assert 1 == len(unique_vals)\\n assert 0 == unique_vals[0]\",\n \"async def main(dut):\\n # Create a 10us period clock on port clk\\n clock = Clock(dut.clk_i, 10, units=\\\"us\\\")\\n cocotb.fork(clock.start())\\n\\n # Reset system\\n await FallingEdge(dut.clk_i)\\n dut.rst_n_i <= 0\\n dut.en_i <= 0\\n dut.data_i <= 0\\n dut.valid_i <= 0\\n\\n # reset\\n await FallingEdge(dut.clk_i)\\n dut.rst_n_i <= 1\\n\\n # test 1\\n dut.en_i <= 1\\n x, y = get_test_vector()\\n cocotb.fork(write_input(dut, x))\\n await check_output(dut, y)\\n\\n # test 2\\n dut.en_i <= 0\\n await check_output_no_en(dut)\\n\\n # test 3\\n dut.en_i <= 1\\n x, y = get_test_vector()\\n cocotb.fork(write_input(dut, x))\\n await check_output(dut, y)\",\n \"def __main_loop(self):\\n\\n while not self.stop:\\n self.__lock_data = True\\n self.__bus_messages_copy = deepcopy(self.__bus_messages)\\n self.__line_messages_copy = deepcopy(self.__line_messages)\\n self.__global_messages_copy = deepcopy(self.__global_messages)\\n self.__bus_messages = {}\\n self.__line_messages = {}\\n self.__global_messages = {\\\"kick reason\\\": \\\"\\\", \\\"free text\\\": \\\"\\\"}\\n buses_to_kick_copy = deepcopy(self.__buses_to_kick)\\n self.__buses_to_kick = list()\\n self.__lock_data = False\\n\\n for bus in buses_to_kick_copy: # handles the buses that need to be kicked\\n message = \\\"kicked for reason:\\\" + self.__global_messages_copy[\\\"kick reason\\\"]\\n if bus.line_num in self.__line_messages_copy.keys():\\n message += self.__line_messages_copy[bus.line_num][\\\"kick reason\\\"]\\n if bus.line_num in self.__line_messages_copy.keys() and bus.id in self.__bus_messages_copy[\\n bus.line_num].keys():\\n message += self.__bus_messages_copy[bus.line_num][bus.id][\\\"kick reason\\\"]\\n print(f\\\"sending message{message.strip()}\\\")\\n bus.send_to_bus(message.strip())\\n\\n global_message = self.__build_global_update()\\n for line, buses in self.__bus_controller.bus_dict.items():\\n line_message = self.__build_line_update(line)\\n for bus in buses:\\n bus_message = self.__build_bus_update(bus)\\n message = global_message + line_message + bus_message\\n message = message.strip(\\\"\\\\n\\\")\\n if message != \\\"\\\":\\n bus.send_to_bus(message)\\n\\n sleep(MessagesSender.SLEEP_TIME)\\n\\n self.__shut_down()\\n print(\\\"polling thread stopped\\\")\",\n \"def test_shutdown_restart(self):\\n log.info(\\\"CONFIG: %s\\\", self._agent_config())\\n self.create_sample_data_set_dir('node59p1_step2.dat', TELEM_DIR, \\\"node59p1.dat\\\")\\n\\n self.assert_initialize(final_state=ResourceAgentState.COMMAND)\\n\\n # Slow down processing to 1 per second to give us time to stop\\n self.dataset_agent_client.set_resource({DriverParameter.RECORDS_PER_SECOND: 1})\\n self.assert_start_sampling()\\n\\n # Verify we get one sample\\n try:\\n # Read the first file and verify the data\\n result = self.data_subscribers.get_samples(DataParticleType.CONTROL, 1)\\n result1 = self.data_subscribers.get_samples(DataParticleType.SAMPLE, 3)\\n result.extend(result1)\\n log.debug(\\\"RESULT: %s\\\", result)\\n\\n # Verify values\\n self.assert_data_values(result, 'test_data_1-2.txt.result.yml')\\n self.assert_sample_queue_size(DataParticleType.CONTROL, 0)\\n self.assert_sample_queue_size(DataParticleType.SAMPLE, 0)\\n\\n self.create_sample_data_set_dir('node59p1_step4.dat', TELEM_DIR, \\\"node59p1.dat\\\")\\n # Now read the first record of the second file then stop\\n result = self.data_subscribers.get_samples(DataParticleType.SAMPLE, 3)\\n log.debug(\\\"RESULT 1: %s\\\", result)\\n self.assert_stop_sampling()\\n self.assert_sample_queue_size(DataParticleType.CONTROL, 0)\\n self.assert_sample_queue_size(DataParticleType.SAMPLE, 0)\\n\\n # stop and re-start the agent\\n self.stop_dataset_agent_client()\\n self.init_dataset_agent_client()\\n # re-initialize\\n self.assert_initialize()\\n\\n result2 = self.data_subscribers.get_samples(DataParticleType.SAMPLE, 3)\\n log.debug(\\\"RESULT 2: %s\\\", result2)\\n result.extend(result2)\\n log.debug(\\\"RESULT: %s\\\", result)\\n self.assert_data_values(result, 'test_data_3-4.txt.result.yml')\\n self.assert_sample_queue_size(DataParticleType.CONTROL, 0)\\n self.assert_sample_queue_size(DataParticleType.SAMPLE, 0)\\n except SampleTimeout as e:\\n log.error(\\\"Exception trapped: %s\\\", e, exc_info=True)\\n self.fail(\\\"Sample timeout.\\\")\",\n \"def ml_loop(side: str):\\n\\n # === Here is the execution order of the loop === #\\n # 1. Put the initialization code here\\n ball_served = False\\n blocker_last_x = 0\\n\\n class Pred:\\n pred = 100\\n blocker_pred_x = 0\\n last_command = 0\\n blocker_vx = 0\\n\\n \\n def move_to(player, pred) : #move platform to predicted position to catch ball \\n if player == '1P':\\n if scene_info[\\\"platform_1P\\\"][0]+20 > (pred-10) and scene_info[\\\"platform_1P\\\"][0]+20 < (pred+10): return 0 # NONE\\n elif scene_info[\\\"platform_1P\\\"][0]+20 <= (pred-10) : return 1 # goes right\\n else : return 2 # goes left\\n else :\\n if scene_info[\\\"platform_2P\\\"][0]+20 > (pred-10) and scene_info[\\\"platform_2P\\\"][0]+20 < (pred+10): return 0 # NONE\\n elif scene_info[\\\"platform_2P\\\"][0]+20 <= (pred-10) : return 1 # goes right\\n else : return 2 # goes left\\n\\n def ml_loop_for_1P(): \\n # ball slicing\\n if scene_info[\\\"ball_speed\\\"][1] > 0 and (scene_info[\\\"ball\\\"][1]+scene_info[\\\"ball_speed\\\"][1]) >= 415 and Pred.last_command == 0:\\n print(\\\"------\\\")\\n ball_x = scene_info[\\\"ball\\\"][0]\\n ball_y = scene_info[\\\"ball\\\"][1]\\n ball_vx = scene_info[\\\"ball_speed\\\"][0]\\n ball_slice_vx = scene_info[\\\"ball_speed\\\"][0]+np.sign(scene_info[\\\"ball_speed\\\"][0])*3\\n ball_vy = scene_info[\\\"ball_speed\\\"][1] \\n blocker_x = scene_info['blocker'][0] + Pred.blocker_vx\\n \\n y = abs((415 - ball_y) // ball_vy)\\n pred_ball_1P = ball_x + ball_vx * y\\n\\n y = abs((415 - 260) // ball_vy)\\n pred_ball_blocker = pred_ball_1P + ball_slice_vx * y\\n bound = pred_ball_blocker // 200 # Determine if it is beyond the boundary\\n if (bound > 0): # pred > 200 # fix landing position\\n if (bound%2 == 0) : \\n pred_ball_blocker = pred_ball_blocker - bound*200 \\n else :\\n pred_ball_blocker = 200 - (pred_ball_blocker - 200*bound)\\n elif (bound < 0) : # pred < 0\\n if (bound%2 ==1) :\\n pred_ball_blocker = abs(pred_ball_blocker - (bound+1) *200)\\n else :\\n pred_ball_blocker = pred_ball_blocker + (abs(bound)*200)\\n \\n y = abs((415 - 260) // ball_vy)\\n Pred.blocker_pred_x = blocker_x + Pred.blocker_vx * y \\n if Pred.blocker_pred_x < 0: Pred.blocker_pred_x = abs(Pred.blocker_pred_x)\\n elif Pred.blocker_pred_x > 170: Pred.blocker_pred_x = 170 - (Pred.blocker_pred_x - 170)\\n \\n if pred_ball_blocker >= Pred.blocker_pred_x-10 and pred_ball_blocker < Pred.blocker_pred_x+40:\\n print(\\\"slice will hit blicker\\\")\\n # don't slice \\n # use origin ball vx to predict will hit blocker or not\\n # if will hit blicker let ball go reverse direction\\n y = abs((415 - 260) // ball_vy)\\n pred_ball_blocker = pred_ball_1P + ball_vx * y\\n bound = pred_ball_blocker // 200 # Determine if it is beyond the boundary\\n if (bound > 0): # pred > 200 # fix landing position\\n if (bound%2 == 0) : \\n pred_ball_blocker = pred_ball_blocker - bound*200 \\n else :\\n pred_ball_blocker = 200 - (pred_ball_blocker - 200*bound)\\n elif (bound < 0) : # pred < 0\\n if (bound%2 ==1) :\\n pred_ball_blocker = abs(pred_ball_blocker - (bound+1) *200)\\n else :\\n pred_ball_blocker = pred_ball_blocker + (abs(bound)*200)\\n\\n if pred_ball_blocker >= Pred.blocker_pred_x-10 and pred_ball_blocker < Pred.blocker_pred_x+40:\\n print(\\\"will hit blocker, hit reversed direction\\\")\\n if scene_info[\\\"ball_speed\\\"][0] > 0: return 2\\n else: return 1\\n else: \\n print(\\\"will not hit blicker, do nothing\\\")\\n return 0\\n else:\\n # slice\\n print(\\\"slice will not hit blocker\\\")\\n if scene_info[\\\"ball_speed\\\"][0] > 0: return 1\\n else: return 2\\n\\n elif scene_info[\\\"ball_speed\\\"][1] > 0 : # 球正在向下 # ball goes down\\n x = ( scene_info[\\\"platform_1P\\\"][1]-scene_info[\\\"ball\\\"][1] ) // scene_info[\\\"ball_speed\\\"][1] # 幾個frame以後會需要接 # x means how many frames before catch the ball\\n Pred.pred = scene_info[\\\"ball\\\"][0]+(scene_info[\\\"ball_speed\\\"][0]*x) # 預測最終位置 # pred means predict ball landing site \\n bound = Pred.pred // 200 # Determine if it is beyond the boundary\\n if (bound > 0): # pred > 200 # fix landing position\\n if (bound%2 == 0) : \\n Pred.pred = Pred.pred - bound*200 \\n else :\\n Pred.pred = 200 - (Pred.pred - 200*bound)\\n elif (bound < 0) : # pred < 0\\n if (bound%2 ==1) :\\n Pred.pred = abs(Pred.pred - (bound+1) *200)\\n else :\\n Pred.pred = Pred.pred + (abs(bound)*200)\\n return move_to(player = '1P',pred = Pred.pred)\\n \\n else : # 球正在向上 # ball goes up\\n return move_to(player = '1P',pred = 100)\\n\\n\\n\\n def ml_loop_for_2P(): # as same as 1P\\n if scene_info[\\\"ball_speed\\\"][1] > 0 : \\n return move_to(player = '2P',pred = 100)\\n else : \\n x = ( scene_info[\\\"platform_2P\\\"][1]+30-scene_info[\\\"ball\\\"][1] ) // scene_info[\\\"ball_speed\\\"][1] \\n pred = scene_info[\\\"ball\\\"][0]+(scene_info[\\\"ball_speed\\\"][0]*x) \\n bound = pred // 200 \\n if (bound > 0):\\n if (bound%2 == 0):\\n pred = pred - bound*200 \\n else :\\n pred = 200 - (pred - 200*bound)\\n elif (bound < 0) :\\n if bound%2 ==1:\\n pred = abs(pred - (bound+1) *200)\\n else :\\n pred = pred + (abs(bound)*200)\\n return move_to(player = '2P',pred = pred)\\n\\n # 2. Inform the game process that ml process is ready\\n comm.ml_ready()\\n\\n # 3. Start an endless loop\\n while True:\\n # 3.1. Receive the scene information sent from the game process\\n scene_info = comm.recv_from_game()\\n\\n # 3.2. If either of two sides wins the game, do the updating or\\n # resetting stuff and inform the game process when the ml process\\n # is ready.\\n if scene_info[\\\"status\\\"] != \\\"GAME_ALIVE\\\":\\n # Do some updating or resetting stuff\\n ball_served = False\\n\\n # 3.2.1 Inform the game process that\\n # the ml process is ready for the next round\\n comm.ml_ready()\\n continue\\n\\n # 3.3 Put the code here to handle the scene information\\n\\n # 3.4 Send the instruction for this frame to the game process\\n if not ball_served:\\n comm.send_to_game({\\\"frame\\\": scene_info[\\\"frame\\\"], \\\"command\\\": \\\"SERVE_TO_LEFT\\\"})\\n blocker_last_x = scene_info[\\\"blocker\\\"][0]\\n Pred.last_command = 0\\n ball_served = True\\n else:\\n if side == \\\"1P\\\":\\n Pred.blocker_vx = scene_info[\\\"blocker\\\"][0] - blocker_last_x\\n if scene_info[\\\"blocker\\\"][0] == 0: Pred.blocker_vx = 5\\n elif scene_info[\\\"blocker\\\"][0] == 170: Pred.blocker_vx = -5\\n command = ml_loop_for_1P()\\n blocker_last_x = scene_info[\\\"blocker\\\"][0]\\n Pred.last_command = command\\n else:\\n command = ml_loop_for_2P()\\n\\n if command == 0:\\n comm.send_to_game({\\\"frame\\\": scene_info[\\\"frame\\\"], \\\"command\\\": \\\"NONE\\\"})\\n elif command == 1:\\n comm.send_to_game({\\\"frame\\\": scene_info[\\\"frame\\\"], \\\"command\\\": \\\"MOVE_RIGHT\\\"})\\n else :\\n comm.send_to_game({\\\"frame\\\": scene_info[\\\"frame\\\"], \\\"command\\\": \\\"MOVE_LEFT\\\"})\",\n \"def test_back_fill(self):\\n self.driver.start_sampling()\\n\\n # step 2 contains 2 blocks, start with this and get both since we used them\\n # separately in other tests \\n self.clear_async_data()\\n self.create_sample_data_set_dir(\\n \\\"node59p1_step2.dat\\\",\\n TELEM_DIR,\\n \\\"node59p1.dat\\\",\\n copy_metadata=False\\n )\\n self.assert_data(\\n (DostadParserTelemeteredDataParticle, DostadParserTelemeteredMetadataDataParticle),\\n 'test_data_1-2.txt.result.yml',\\n count=3\\n )\\n\\n # This file has had a section of DO data replaced with 0s\\n self.clear_async_data()\\n self.create_sample_data_set_dir(\\n 'node59p1_step3.dat',\\n TELEM_DIR,\\n \\\"node59p1.dat\\\",\\n copy_metadata=False\\n )\\n self.assert_data(\\n DostadParserTelemeteredDataParticle,\\n 'test_data_3.txt.result.yml',\\n count=3\\n )\\n\\n # Now fill in the zeroed section from step3, this should just return the new\\n # data\\n self.clear_async_data()\\n self.create_sample_data_set_dir(\\n 'node59p1_step4.dat',\\n TELEM_DIR,\\n \\\"node59p1.dat\\\",\\n copy_metadata=False\\n )\\n self.assert_data(\\n DostadParserTelemeteredDataParticle,\\n 'test_data_4.txt.result.yml',\\n count=1\\n )\\n\\n # start over now, using step 4\\n self.driver.stop_sampling()\\n\\n # Reset the driver with no memento\\n self.memento = None\\n self.driver = MflmDOSTADDataSetDriver(\\n self._driver_config()['startup_config'],\\n self.memento,\\n self.data_callback,\\n self.state_callback,\\n self.event_callback,\\n self.exception_callback)\\n self.driver.start_sampling()\\n\\n self.clear_async_data()\\n self.create_sample_data_set_dir(\\n 'node59p1_step4.dat',\\n TELEM_DIR,\\n \\\"node59p1.dat\\\",\\n copy_metadata=False\\n )\\n self.assert_data(\\n (DostadParserTelemeteredDataParticle, DostadParserTelemeteredMetadataDataParticle),\\n 'test_data_1-4.txt.result.yml',\\n count=7\\n )\",\n \"def test_fleur_relax_continue_converged(self, run_with_cache, mock_code_factory):\\n assert False\",\n \"def _run_cycle(self):\\n pass\",\n \"def loop_run(self, loops):\\n self.loop_seek(self.num_loops + loops)\",\n \"def testPluginNoError(self):\\n schema = self.dataset.makeMinimalSchema()\\n task = lsst.meas.base.SingleFrameMeasurementTask(schema=schema, config=self.config)\\n exposure, cat = self.dataset.realize(noise=100.0, schema=schema, randomSeed=0)\\n task.run(cat, exposure)\\n source = cat[0]\\n self.assertFalse(source.get(self.algName + \\\"_flag\\\"))\\n self.assertFalse(source.get(self.algName + \\\"_flag_containsNan\\\"))\\n self.assertFalse(source.get(self.algName + \\\"_flag_edge\\\"))\",\n \"def loop(self):\\n while self.dispatch(True) is not QUIT:\\n pass\",\n \"def mainloop(self, run, *args, **kwds):\\r\\n #self.m.make()\\r\\n self.time = 0\\r\\n Dummy = things(0,0,0)\\r\\n Dummy.threadqueue.append(-1)\\r\\n Dummy.s=self\\r\\n Dummy.name = 'End of simulation.'\\r\\n heappush(self.queue, (self.timeout, (Dummy, 1000)))\\r\\n #count = 0\\r\\n while self.time < self.timeout:\\r\\n run(*args, **kwds)\\r\\n (now, (item, i)) = heappop(self.queue)\\r\\n self.CalculateResourse(now)\\r\\n self.time = now\\r\\n item.creat()\\r\\n #count += 1\\r\\n #print 'Number of loops' , count\\r\",\n \"def pauseLoop(self):\\n print('SYNC stim detected LOW')\\n self.loopRunning = False\",\n \"def test_shutdown_restart(self):\\n log.info(\\\"CONFIG: %s\\\", self._agent_config())\\n self.create_sample_data_set_dir(\\n 'node59p1_step2.dat',\\n TELEM_DIR,\\n \\\"node59p1.dat\\\",\\n copy_metadata=False\\n )\\n\\n self.assert_initialize(final_state=ResourceAgentState.COMMAND)\\n\\n # Slow down processing to 1 per second to give us time to stop\\n self.dataset_agent_client.set_resource({DriverParameter.RECORDS_PER_SECOND: 1})\\n self.assert_start_sampling()\\n\\n # Verify we get one sample\\n try:\\n # Read the first file and verify the data\\n result = self.data_subscribers.get_samples(DataParticleType.METADATA_TELEMETERED, 1)\\n result1 = self.data_subscribers.get_samples(DataParticleType.SAMPLE_TELEMETERED, 2)\\n result.extend(result1)\\n log.debug(\\\"RESULT: %s\\\", result)\\n\\n # Verify values\\n self.assert_data_values(result, 'test_data_1-2.txt.result.yml')\\n self.assert_sample_queue_size(DataParticleType.METADATA_TELEMETERED, 0)\\n self.assert_sample_queue_size(DataParticleType.SAMPLE_TELEMETERED, 0)\\n\\n self.create_sample_data_set_dir(\\n 'node59p1_step4.dat',\\n TELEM_DIR,\\n \\\"node59p1.dat\\\",\\n copy_metadata=False\\n )\\n # Now read the first records of the second file then stop\\n result1 = self.data_subscribers.get_samples(DataParticleType.SAMPLE_TELEMETERED, 2)\\n log.debug(\\\"RESULT 1: %s\\\", result1)\\n self.assert_stop_sampling()\\n self.assert_sample_queue_size(DataParticleType.METADATA_TELEMETERED, 0)\\n self.assert_sample_queue_size(DataParticleType.SAMPLE_TELEMETERED, 0)\\n\\n # stop and re-start the agent\\n self.stop_dataset_agent_client()\\n self.init_dataset_agent_client()\\n # re-initialize\\n self.assert_initialize()\\n\\n # Restart sampling and ensure we get the last 2 records of the file\\n result2 = self.data_subscribers.get_samples(DataParticleType.SAMPLE_TELEMETERED, 2)\\n log.debug(\\\"RESULT 2: %s\\\", result2)\\n result = result1\\n result.extend(result2)\\n log.debug(\\\"RESULT: %s\\\", result)\\n self.assert_sample_queue_size(DataParticleType.METADATA_TELEMETERED, 0)\\n self.assert_data_values(result, 'test_data_3-4.txt.result.yml')\\n self.assert_sample_queue_size(DataParticleType.METADATA_TELEMETERED, 0)\\n self.assert_sample_queue_size(DataParticleType.SAMPLE_TELEMETERED, 0)\\n except SampleTimeout as e:\\n log.error(\\\"Exception trapped: %s\\\", e, exc_info=True)\\n self.fail(\\\"Sample timeout.\\\")\",\n \"def block(self):\\n # I WILL RUN FOR EVER \\n # BUT WHY ARE YOU RUNNING ?\\n self.__loop.run_forever()\",\n \"def test_for_loop(self, modes, parse_input_mocked_metadata):\\n bb = parse_input_mocked_metadata(\\n \\\"for int m in {}\\\\n\\\\tMeasureFock() | m\\\".format(modes)\\n )\\n assert np.all(\\n bb._forvar[\\\"m\\\"] == np.array(modes)\\n )\\n assert bb.operations == [\\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[0]]},\\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[1]]},\\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[2]]}\\n ]\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"async def get_peak_loop(self):\\n while True:\\n try:\\n self.blockchain_state = await self.node_rpc_client.get_blockchain_state()\\n self.wallet_synced = await self.wallet_rpc_client.get_synced()\\n await asyncio.sleep(30)\\n except asyncio.CancelledError:\\n self.log.info(\\\"Cancelled get_peak_loop, closing\\\")\\n return\\n except Exception as e:\\n self.log.error(f\\\"Unexpected error in get_peak_loop: {e}\\\")\\n await asyncio.sleep(30)\",\n \"async def get_peak_loop(self):\\n while True:\\n try:\\n self.blockchain_state = await self.node_rpc_client.get_blockchain_state()\\n self.wallet_synced = await self.wallet_rpc_client.get_synced()\\n await asyncio.sleep(30)\\n except asyncio.CancelledError:\\n self.log.info(\\\"Cancelled get_peak_loop, closing\\\")\\n return\\n except Exception as e:\\n self.log.error(f\\\"Unexpected error in get_peak_loop: {e}\\\")\\n await asyncio.sleep(30)\",\n \"def run_metropolis_PBC(self):\\n\\n # Initialize the posistions for each new Monte Carlo run\\n positions = np.random.rand(self.num_p, self.num_d)\\n # Initialize the distance matrix\\n self.s.positions_distances_PBC(positions)\\n # check if the wave function is zero\\n while True:\\n test_wavefunction = self.w.wavefunction(positions)\\n if test_wavefunction**2 <= 1e-14:\\n # print ('obs')\\n # Initialize the posistions for each new Monte Carlo run\\n positions = np.random.rand(self.num_p, self.num_d)\\n # Initialize the distance matrix\\n self.s.positions_distances_PBC(positions)\\n else:\\n break\\n # Initialize sampler method for each new Monte Carlo run\\n self.sam.initialize()\\n\\n for i in range(self.mc_cycles):\\n new_positions = self.metropolis_step_PBC(positions)\\n positions = new_positions\\n self.sam.sample_values(positions)\\n\\n self.sam.average_values(self.mc_cycles)\\n energy = self.sam.local_energy\\n d_El = self.sam.derivative_energy\\n var = self.sam.variance\\n print ('w = ', self.w.wavefunction(positions))\\n self.print_averages()\\n return d_El, energy, var\",\n \"def fatal_error_processor(self):\\n while True:\\n _ = (yield)\\n self.failed = True\\n self.converged = False\\n self.solve_completed = False\",\n \"def _monitor_loop(self):\\n while self._continue_running():\\n for wl in self._workloads:\\n if not wl.running():\\n self.log.info('%-20s FAILED', wl.name())\\n self._restart_workload(wl)\\n else:\\n self.log.info('%-20s OK', wl.name())\\n\\n time.sleep(self._monitor_delay)\",\n \"def run(self):\\n\\n while not self.__done:\\n self.single_cycle()\\n\\n \\\"\\\"\\\"\\n while not self.__done:\\n self.step()\\n self.debug()\\n \\\"\\\"\\\"\",\n \"def test_shd_should_not_crash_executed_heal_info(self):\\n # pylint: disable=too-many-statements\\n bricks_list = get_all_bricks(self.mnode, self.volname)\\n # Setting options\\n g.log.info('Setting options...')\\n options = {\\\"metadata-self-heal\\\": \\\"off\\\",\\n \\\"entry-self-heal\\\": \\\"off\\\",\\n \\\"data-self-heal\\\": \\\"off\\\"}\\n ret = set_volume_options(self.mnode, self.volname, options)\\n self.assertTrue(ret, 'Failed to set options %s' % options)\\n g.log.info(\\\"Successfully set %s for volume %s\\\",\\n options, self.volname)\\n\\n # Creating files on client side\\n for mount_obj in self.mounts:\\n g.log.info(\\\"Generating data for %s:%s\\\",\\n mount_obj.client_system, mount_obj.mountpoint)\\n # Create files\\n g.log.info('Creating files...')\\n command = (\\\"python %s create_files -f 10 --fixed-file-size 1M %s\\\"\\n % (self.script_upload_path, mount_obj.mountpoint))\\n\\n proc = g.run_async(mount_obj.client_system, command,\\n user=mount_obj.user)\\n self.all_mounts_procs.append(proc)\\n self.io_validation_complete = False\\n\\n # Validate IO\\n self.assertTrue(\\n validate_io_procs(self.all_mounts_procs, self.mounts),\\n \\\"IO failed on some of the clients\\\"\\n )\\n self.io_validation_complete = True\\n\\n # Bring brick0 offline\\n g.log.info('Bringing bricks %s offline', bricks_list[0])\\n ret = bring_bricks_offline(self.volname, bricks_list[0])\\n self.assertTrue(ret, 'Failed to bring bricks %s offline'\\n % bricks_list[0])\\n\\n ret = are_bricks_offline(self.mnode, self.volname,\\n [bricks_list[0]])\\n self.assertTrue(ret, 'Bricks %s are not offline'\\n % bricks_list[0])\\n g.log.info('Bringing bricks %s offline is successful',\\n bricks_list[0])\\n\\n # Creating files on client side\\n number_of_files_one_brick_off = '1000'\\n self.all_mounts_procs = []\\n for mount_obj in self.mounts:\\n g.log.info(\\\"Generating data for %s:%s\\\",\\n mount_obj.client_system, mount_obj.mountpoint)\\n # Create files\\n g.log.info('Creating files...')\\n command = (\\\"python %s create_files \\\"\\n \\\"-f %s \\\"\\n \\\"--fixed-file-size 1k \\\"\\n \\\"--base-file-name new_file \\\"\\n \\\"%s\\\"\\n % (self.script_upload_path,\\n number_of_files_one_brick_off,\\n mount_obj.mountpoint))\\n\\n proc = g.run_async(mount_obj.client_system, command,\\n user=mount_obj.user)\\n self.all_mounts_procs.append(proc)\\n self.io_validation_complete = False\\n\\n # Validate IO\\n self.assertTrue(\\n validate_io_procs(self.all_mounts_procs, self.mounts),\\n \\\"IO failed on some of the clients\\\"\\n )\\n self.io_validation_complete = True\\n\\n # Get heal info\\n g.log.info(\\\"Getting heal info...\\\")\\n heal_info_data = get_heal_info_summary(self.mnode, self.volname)\\n self.assertIsNotNone(heal_info_data, 'Failed to get heal info.')\\n g.log.info('Success in getting heal info')\\n\\n # Check quantity of file pending heal\\n for brick in bricks_list[1:]:\\n self.assertEqual(heal_info_data[brick]['numberOfEntries'],\\n str(int(number_of_files_one_brick_off)+1),\\n 'Number of files pending heal is not correct')\\n\\n # Setting options\\n g.log.info('Setting options...')\\n options = {\\\"performance.enable-least-priority\\\": \\\"enable\\\"}\\n ret = set_volume_options(self.mnode, self.volname, options)\\n self.assertTrue(ret, 'Failed to set options %s' % options)\\n g.log.info(\\\"Successfully set %s for volume %s\\\",\\n options, self.volname)\\n\\n # Bring brick1 offline\\n g.log.info('Bringing bricks %s offline', bricks_list[1])\\n ret = bring_bricks_offline(self.volname, bricks_list[1])\\n self.assertTrue(ret, 'Failed to bring bricks %s offline'\\n % bricks_list[1])\\n\\n ret = are_bricks_offline(self.mnode, self.volname,\\n [bricks_list[1]])\\n self.assertTrue(ret, 'Bricks %s are not offline'\\n % bricks_list[1])\\n g.log.info('Bringing bricks %s offline is successful',\\n bricks_list[1])\\n\\n # Setting options\\n g.log.info('Setting options...')\\n options = {\\\"quorum-type\\\": \\\"fixed\\\"}\\n ret = set_volume_options(self.mnode, self.volname, options)\\n self.assertTrue(ret, 'Failed to set options %s' % options)\\n g.log.info(\\\"Successfully set %s for volume %s\\\",\\n options, self.volname)\\n\\n # Creating files on client side\\n number_of_files_two_brick_off = '100'\\n self.all_mounts_procs = []\\n for mount_obj in self.mounts:\\n g.log.info(\\\"Generating data for %s:%s\\\",\\n mount_obj.client_system, mount_obj.mountpoint)\\n # Create files\\n g.log.info('Creating files...')\\n command = (\\\"python %s create_files \\\"\\n \\\"-f %s \\\"\\n \\\"--fixed-file-size 1k \\\"\\n \\\"--base-file-name new_new_file \\\"\\n \\\"%s\\\"\\n % (self.script_upload_path,\\n number_of_files_two_brick_off,\\n mount_obj.mountpoint))\\n\\n proc = g.run_async(mount_obj.client_system, command,\\n user=mount_obj.user)\\n self.all_mounts_procs.append(proc)\\n self.io_validation_complete = False\\n\\n # Validate IO\\n self.assertTrue(\\n validate_io_procs(self.all_mounts_procs, self.mounts),\\n \\\"IO failed on some of the clients\\\"\\n )\\n self.io_validation_complete = True\\n\\n # Get heal info\\n g.log.info(\\\"Getting heal info...\\\")\\n heal_info_data = get_heal_info_summary(self.mnode, self.volname)\\n self.assertIsNotNone(heal_info_data, 'Failed to get heal info.')\\n g.log.info('Success in getting heal info')\\n\\n # Check quantity of file pending heal\\n number_of_files_to_check = str(int(number_of_files_one_brick_off) +\\n int(number_of_files_two_brick_off) + 1)\\n self.assertEqual(heal_info_data[bricks_list[-1]]['numberOfEntries'],\\n number_of_files_to_check,\\n 'Number of files pending heal is not correct')\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.79922223","0.79701054","0.79289037","0.74845135","0.731188","0.68929285","0.6694039","0.65099937","0.6446146","0.6183709","0.6016163","0.5998978","0.5988837","0.59473413","0.5947067","0.58972764","0.57490903","0.57089925","0.5673426","0.5634207","0.5628779","0.56102663","0.5595277","0.55746317","0.55557895","0.5486114","0.5474863","0.54724157","0.5453753","0.54351807","0.5394675","0.539147","0.5371909","0.53445137","0.53017277","0.53004","0.52939916","0.5267316","0.5265255","0.52404845","0.5224502","0.52196026","0.5210178","0.51900864","0.51802963","0.51756185","0.51362395","0.51210165","0.51122326","0.50956035","0.5090563","0.5084351","0.50814724","0.50789106","0.5076957","0.5076916","0.50753766","0.5055084","0.50522494","0.505012","0.5029237","0.50156975","0.5014751","0.50131994","0.500852","0.5002584","0.49936947","0.49815437","0.49777725","0.4976548","0.4972247","0.49626255","0.49512658","0.49441928","0.49425673","0.49374455","0.49369782","0.4936012","0.4930023","0.49265274","0.492436","0.492425","0.49127686","0.49107772","0.4906489","0.49036607","0.49024978","0.49006292","0.49005798","0.4894673","0.48885766","0.48884925","0.48860812","0.48846883","0.48846883","0.48807663","0.48745543","0.48679623","0.48612884","0.4861242"],"string":"[\n \"0.79922223\",\n \"0.79701054\",\n \"0.79289037\",\n \"0.74845135\",\n \"0.731188\",\n \"0.68929285\",\n \"0.6694039\",\n \"0.65099937\",\n \"0.6446146\",\n \"0.6183709\",\n \"0.6016163\",\n \"0.5998978\",\n \"0.5988837\",\n \"0.59473413\",\n \"0.5947067\",\n \"0.58972764\",\n \"0.57490903\",\n \"0.57089925\",\n \"0.5673426\",\n \"0.5634207\",\n \"0.5628779\",\n \"0.56102663\",\n \"0.5595277\",\n \"0.55746317\",\n \"0.55557895\",\n \"0.5486114\",\n \"0.5474863\",\n \"0.54724157\",\n \"0.5453753\",\n \"0.54351807\",\n \"0.5394675\",\n \"0.539147\",\n \"0.5371909\",\n \"0.53445137\",\n \"0.53017277\",\n \"0.53004\",\n \"0.52939916\",\n \"0.5267316\",\n \"0.5265255\",\n \"0.52404845\",\n \"0.5224502\",\n \"0.52196026\",\n \"0.5210178\",\n \"0.51900864\",\n \"0.51802963\",\n \"0.51756185\",\n \"0.51362395\",\n \"0.51210165\",\n \"0.51122326\",\n \"0.50956035\",\n \"0.5090563\",\n \"0.5084351\",\n \"0.50814724\",\n \"0.50789106\",\n \"0.5076957\",\n \"0.5076916\",\n \"0.50753766\",\n \"0.5055084\",\n \"0.50522494\",\n \"0.505012\",\n \"0.5029237\",\n \"0.50156975\",\n \"0.5014751\",\n \"0.50131994\",\n \"0.500852\",\n \"0.5002584\",\n \"0.49936947\",\n \"0.49815437\",\n \"0.49777725\",\n \"0.4976548\",\n \"0.4972247\",\n \"0.49626255\",\n \"0.49512658\",\n \"0.49441928\",\n \"0.49425673\",\n \"0.49374455\",\n \"0.49369782\",\n \"0.4936012\",\n \"0.4930023\",\n \"0.49265274\",\n \"0.492436\",\n \"0.492425\",\n \"0.49127686\",\n \"0.49107772\",\n \"0.4906489\",\n \"0.49036607\",\n \"0.49024978\",\n \"0.49006292\",\n \"0.49005798\",\n \"0.4894673\",\n \"0.48885766\",\n \"0.48884925\",\n \"0.48860812\",\n \"0.48846883\",\n \"0.48846883\",\n \"0.48807663\",\n \"0.48745543\",\n \"0.48679623\",\n \"0.48612884\",\n \"0.4861242\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.88965213"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81491,"cells":{"query":{"kind":"string","value":"Test the proper operation of the molecule loop when no data pipe is present. The function tested is pipe_control.mol_res_spin.molecule_loop()."},"document":{"kind":"string","value":"def test_molecule_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for molecule in mol_res_spin.molecule_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_spin_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for spin in mol_res_spin.spin_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_molecule_loop_no_selection(self):\n\n # Molecule data.\n name = ['Ap4Aase', 'RNA']\n\n # Loop over the molecules.\n i = 0\n for mol in mol_res_spin.molecule_loop():\n # Test the molecule names.\n self.assertEqual(mol.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)","def test_residue_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for residue in mol_res_spin.residue_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_molecule_loop(self):\n\n # Loop over the molecules.\n for mol in mol_res_spin.molecule_loop('#RNA'):\n # Test the molecule name.\n self.assertEqual(mol.name, 'RNA')\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def test_return_molecule_pipe_fail(self):\n\n # Try to get a molecule from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')","def test_spin_loop_no_selection(self):\n\n # Spin data.\n select = [0, 1, 0, 0, 1, 1, 0, 1]\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 8)","def test_spin_loop(self):\n\n # Spin data.\n select = [1, 0]\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, 'N5')\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 2)","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def test_circularloop(self):\n cmd = f\"{SRC_LISTER} -i {PWD}/main\"\n with subprocess.Popen(\n shlex.split(cmd), stdout=subprocess.PIPE, stderr=subprocess.PIPE\n ) as proc:\n try:\n out, err = proc.communicate(timeout=5)\n assert len(err.strip()) > 0, \"Expected a circular reference error\"\n except subprocess.TimeoutExpired as te:\n print(\"Unexpected parser timeout during infinite loop test\")","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_spin_loop_multiatom(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_run_loop_success(self):\n found = False\n pyint = Interpreter(limit=15)\n try:\n pyint.run(code=BF_CODE_LOOP_TWICE)\n except SystemExit: \n found = True\n self.assertFalse(found)","def test_spin_loop_wildcard(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N*'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_run_molecule_not_selected(self, single_mol_system):\n sequence = \"ABCDE\"\n processor = dssp.AnnotateResidues(\n \"test\", sequence, molecule_selector=lambda mol: False\n )\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert vermouth.utils.are_all_equal(found)\n assert found[0] is None","def test_return_spin_pipe_fail(self):\n\n # Try to get a spin from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')","def test_no_immediate_stop(self):\n script = ControlScript()\n options = ControlOptions()\n options.parseOptions([b\"--data-path\", self.mktemp()])\n self.assertNoResult(script.main(MemoryCoreReactor(), options))","def run(self):\n while True:\n if self.job_q.empty():\n self.message_q.put(False)\n return\n try:\n smolecule = self.job_q.get()\n self.data_pointer[smolecule].get_adp(self.Temp)\n except IndexError:\n self.message_q.put((smolecule, None))\n try:\n self.message_q.put((smolecule, [j.adp['cart_int'] for j in self.data_pointer[smolecule].atoms]))\n except KeyError:\n # =======================================================\n # self.message_q.put((molecule,[0 for i in self.data_pointer[molecule].atoms]))\n #=======================================================\n pass","def test_count_spins_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Test for the error.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.count_spins)","def loop(self):\n raise NotImplementedError()","async def checkNewLoop(self):\n pass","def test_multi_molecules_cycle_one(self, multi_mol_system_irregular):\n sequence = \"A\"\n expected = [sequence] * (15 * 3)\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_irregular)\n found = self.sequence_from_system(multi_mol_system_irregular, \"test\")\n assert found == expected","def _run(self):\n while(self._loop):\n pass","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_reset(self):\n ran = []\n def foo():\n ran.append(None)\n\n c = task.Clock()\n lc = TestableLoopingCall(c, foo)\n lc.start(2, now=False)\n c.advance(1)\n lc.reset()\n c.advance(1)\n self.assertEqual(ran, [])\n c.advance(1)\n self.assertEqual(ran, [None])","def test_return_residue_pipe_fail(self):\n\n # Try to get a residue from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')","def test_multi_molecules_cycle(self, multi_mol_system_regular, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n expected = expected * 3\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_regular)\n found = self.sequence_from_system(multi_mol_system_regular, \"test\")\n assert found == expected","def loop(self):\n pass","def test_return_molecule(self):\n\n # Ask for a few molecules.\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\n\n # Test the data of molecule 1.\n self.assertEqual(mol1.name, 'Ap4Aase')\n\n # Test the data of molecule 2.\n self.assertEqual(mol2.name, 'RNA')","def test_chunk_pauli(self, method, device):\n opts_no_chunk = {\"fusion_enable\": False}\n opts_chunk = copy.copy(opts_no_chunk)\n opts_chunk[\"blocking_enable\"] = True\n opts_chunk[\"blocking_qubits\"] = 3\n\n backend = self.backend(method=method, device=device, **opts_chunk)\n backend_no_chunk = self.backend(method=method, device=device, **opts_no_chunk)\n\n shots = 100\n\n qr = QuantumRegister(5)\n cr = ClassicalRegister(5)\n regs = (qr, cr)\n circuit = QuantumCircuit(*regs)\n circuit.h(qr[0])\n circuit.h(qr[1])\n circuit.h(qr[2])\n circuit.h(qr[3])\n circuit.h(qr[4])\n circuit.pauli(\"YXZYX\", qr)\n circuit.measure_all()\n\n result = backend.run(circuit, shots=shots, memory=True).result()\n counts = result.get_counts(circuit)\n result_no_chunk = backend_no_chunk.run(circuit, shots=shots, memory=True).result()\n counts_no_chunk = result_no_chunk.get_counts(circuit)\n\n self.assertEqual(counts_no_chunk, counts)","def testPipeFound(self):\n safeFoundHelper(self)\n self.assertCurrentState(safe.Seeking)","async def hold_loop(self, *args) -> bool:\n raise NotImplementedError","def test_single_molecules_cycle_one(self, single_mol_system):\n sequence = \"A\"\n expected = [sequence] * (5 * 3)\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def _while_loop(pd, nmax, max_loop, ncore, outfile):\n \n # make sure the random seed is different for every processor\n random_number_seeds = [3456789, 7654321, 2435467, 8273645,\n 1085712, 4154712, 1248291, 8415917,\n 2345161, 5710916, 5718601, 7516234,\n 9235161, 4917519, 1111245, 8167834] \n \n # get the processor ID (1 - Ncore) and convert to single integer\n current = multiprocessing.current_process()\n pid = current._identity\n pid = pid[0]\n \n #\n # choose a different seed for each processor from the list so each processor has\n # a different randum number seed. Then, fiddle with each seed a little so \n # the seeds aren't the same every time the code is run\n seed = np.int(random_number_seeds[pid] * (np.random.rand()*(10.0 - 0.01) + 0.01))\n \n np.random.seed(seed)\n \n #print 'id and seed', pid, seed\n \n n_particles = 0\n loop_counter = 0\n fmin_scale = 1.0E-100 # -16 -> -32 -> -100\n F_max = np.max(pd.DF.f) #; F_min = np.min(pd.DF.f);\n F_min = np.min(pd.DF.f) * fmin_scale\n # F_max = np.max(pd.DF.f[:-1])#; F_max = 1.0E-88\n #print F_min, F_max\n if pd.optimize:\n relative_potential = pd._interpolate_relative_potential\n else:\n relative_potential = pd.DF.relative_potential\n \n \n pos = np.zeros((nmax, 3))\n vel = np.zeros((nmax, 3)) \n \n while (( n_particles < nmax) and (loop_counter < max_loop)):\n \n r = pd._choose_position()\n Psi = relative_potential(r) \n \n v = pd._choose_velocity(r, Psi)\n \n E = Psi - 0.5 * v * v\n \n f_E = pd.DF.interpolate_f(E)\n \n logF = ( np.random.rand()*(np.log10(F_max) - np.log10(F_min)) + np.log10(F_min) )\n \n # if choosing random F in log F, might be good to do the comparison in logspace as well\n #.... i.e log(F) <= log(f_E) \n #\n # 0 FOR F_E MEANS THAT E < E_min of the potential. THis happens when Psi - KE is smaller\n # than the value of the potential at large_r... should this be considered unbound \n # even though it isn't zero? Is this effectively zero? This has been adjusted in the velocity\n # picking routine but needs verification to make sure it works.... but regardless, I doubt\n # that this is the reason why the particles are failing for NFW but working for hernquist....\n #\n if np.abs(np.log10(f_E)) == np.inf:\n keep_particle = False\n _my_print('log value error... throwing out particle')\n else:\n keep_particle = (logF <= np.log10(f_E))\n\n \n if keep_particle: \n index = n_particles \n \n # \n # need to sample in cosine theta NOT theta!!!!! WTF!!!!!\n #\n #\n \n theta = np.arccos( np.random.rand() * (2.0) - 1.0)\n \n # convert position to cartesian using random theta and phi\n phi = np.random.rand() * 2.0 * np.pi\n \n x = np.sin(theta) * np.cos(phi)\n y = np.sin(theta) * np.sin(phi)\n z = np.cos(theta)\n \n pos[index] = r * np.array([x,y,z])\n\n # repeat for velocity using new random numbersw\n theta = np.arccos( np.random.rand() * (2.0) - 1.0)\n phi = np.random.rand() * 2.0 * np.pi\n \n vx = np.sin(theta) * np.cos(phi)\n vy = np.sin(theta) * np.sin(phi)\n vz = np.cos(theta)\n \n vel[index] = v * np.array([vx,vy,vz])\n \"\"\" \n #else: # do strict cartesian ... slower.... less attractive\n # \n # axis_list = [0, 1, 2]\n # random.shuffle(axis_list)\n \n # #axis_index = np.random.randint(3)\n # first_axis = axis_list[0]\n #\n # pos[index, first_axis] = np.random.rand() * (2.0*r) - r\n #del axis_list[axis_index]\n \n #axis_index = np.random.randint(2)\n # second_axis = axis_list[1]\n \n max_r = np.sqrt(r*r - pos[index,first_axis]**2)\n \n pos[index, second_axis] = np.random.rand()*(2.0 * max_r) - max_r\n #del axis_list[axis_index]\n \n max_r = np.sqrt(r*r - pos[index,first_axis]**2 - pos[index,second_axis]**2)\n \n third_axis = axis_list[2]\n pos[index, third_axis] = np.random.rand() * (2.0 * max_r) - max_r\n \n if np.sqrt(pos[index,0]**2 + pos[index,1]**2 + pos[index,2]**2) > r:\n _my_print('R IS TOO LARGE')\n \n ###\n axis_list = [0, 1, 2]\n random.shuffle(axis_list)\n \n #axis_index = np.random.randint(3)\n first_axis = axis_list[0]\n \n vel[index, first_axis] = np.random.rand() * (2.0*v) - v\n #del axis_list[axis_index]\n \n #axis_index = np.random.randint(2)\n second_axis = axis_list[1]\n \n max_v = np.sqrt(v*v - vel[index,first_axis]**2)\n \n vel[index, second_axis] = np.random.rand()*(2.0 * max_v) - max_v\n #del axis_list[axis_index]\n \n max_v = np.sqrt(v*v - vel[index,first_axis]**2 - vel[index,second_axis]**2)\n \n third_axis = axis_list[2]\n vel[index, third_axis] = np.random.rand() * (2.0 * max_v) - max_v \n \n \n \"\"\"\n n_particles = n_particles + 1\n \n if (loop_counter % 5000) == 0:\n _my_print(\"Have %4i particles. On loop %6i\"%(n_particles, loop_counter))\n loop_counter = loop_counter + 1\n \n # now write out to a temporary file\n f = open(outfile + \"_%02i_\"%(pid) + \".temp\", 'w')\n fmt = \"%12.12E %12.12E %12.12E %12.12E %12.12E %12.12E %12.12E\\n\"\n \n \n for i in np.arange(nmax):\n f.write(fmt%(pd.M_part, pos[i,0], pos[i,1], pos[i,2], \n vel[i,0], vel[i,1], vel[i,2]))\n \n \n f.close() \n \n return pos, vel","def test_control_loop_example():\n example.control.print_error_measurement()\n matplotlib.use('agg')\n example.control.visualise_error_measurement(fig_file='cs_compare.pdf')\n assert path.isfile('cs_compare.pdf')\n example.control.sil_comparison()","def run_one_test_cycle(self):\n logging.info(\n \"{0} operations remaining: {1}\".format(\n self.args.pm_operation, self.args.repetitions\n )\n )\n\n self.check_last_cycle_duration()\n if self.args.repetitions > 0:\n self.run_pm_command()\n else:\n self.summary()","def run(self):\n # Define our components entry point\n while True:\n\n # for each packet waiting on our input port\n for packet in self.receive_all('in'):\n try:\n image = packet.get(\"data\")\n log.debug(\"%s received %s %s\",\n self.__class__.__name__, image.shape, image)\n mask = np.zeros_like(image, dtype=np.bool)\n for i, line in enumerate(image):\n minimum = np.min(image[i])\n factor = 1.1\n threshold = factor * minimum\n mask[i] = image[i] < threshold\n packet.set(\"data\", mask)\n except:\n log.error('Component Failed: %s',\n self.__class__.__name__, exc_info=True)\n\n # send the packet to the next component\n self.send('out', packet)\n\n # yield the CPU, allowing another component to run\n self.yield_ctrl()","def test_empty_with_filter(multi_mol_system_irregular):\n sequence = \"not empty\"\n processor = dssp.AnnotateResidues(\n \"test\", sequence, molecule_selector=lambda mol: False\n )\n with pytest.raises(ValueError):\n processor.run_system(multi_mol_system_irregular)","def run(self):\n while True:\n try:\n self.check_value()\n except Exception as e:\n print(f\"[ERROR]: Error running the continuous run loop on sample_module: {e}\")\n continue","def test_residue_loop(self):\n\n # Loop over the residues.\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\n # Test the selection.\n self.assertEqual(res.num, 2)\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)","def test_io_in_out_loop(self):\n self.l.output(conf_io=0x1, state_io=0x0)\n for i in range(10):\n state_d, state_io, count = self.l.output(state_io=0x1)\n self.assertTrue(state_io & 0x2)\n state_d, state_io, count = self.l.output(state_io=0x0)\n self.assertTrue(not state_io & 0x2)","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_fifo_sync_random():\n pass","def test_io_counter_loop(self):\n self.l.output(conf_io=0x8, state_io=0x0)\n self.l.count(reset=True)\n for i in range(10):\n self.l.output(state_io=0x8)\n self.l.output(state_io=0x0)\n c, t = self.l.count()\n self.assertEqual(c, 9,\n \"counted %g pulses\" % c)","def run_until_stop(self):\n while self.commands[self.pointer] != END:\n # Get the cmd\n cmd = self.commands[self.pointer]\n opcode = cmd % 100\n modes = cmd // 100\n \n vals, locs, self.pointer = get_vals_and_locs(opcode, modes, self.pointer, self.commands)\n \n if opcode == ADD:\n self.commands[locs[2]] = vals[0] + vals[1]\n elif opcode == MUL:\n self.commands[locs[2]] = vals[0] * vals[1]\n elif opcode == INP:\n if self.inputs:\n self.commands[locs[0]] = self.inputs.pop(0)\n else:\n # Put the pointer back, so we run this opcode again\n self.pointer -= 2\n return False\n elif opcode == OUT:\n self.outputs.append(vals[0])\n elif opcode == JIT:\n if vals[0] != 0:\n self.pointer = vals[1]\n elif opcode == JIF:\n if vals[0] == 0:\n self.pointer = vals[1]\n elif opcode == LT:\n self.commands[locs[2]] = 1 if vals[0] < vals[1] else 0\n elif opcode == EQ:\n self.commands[locs[2]] = 1 if vals[0] == vals[1] else 0\n else:\n print(\"FAIL????\")\n\n return True","def test_run_molecule(self, single_mol_system):\n sequence = \"ABCDE\"\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def _loop_raw(raw):\n raise NotImplemented","def test_run_loop_exc(self):\n with self.assertRaises(ExecutionException):\n pyint = Interpreter(limit=1)\n pyint.run(code=BF_CODE_LOOP_TWICE)","def check_pipe_setup(pipe=None, sequence=False, j=False):\n\n # The data pipe.\n if pipe == None:\n pipe = pipes.cdp_name()\n\n # Get the data pipe.\n dp = pipes.get_pipe(pipe)\n\n # Test if the current data pipe exists.\n check_pipe(pipe)\n\n # Test if sequence data exists.\n if sequence and not exists_mol_res_spin_data(pipe):\n raise RelaxNoSequenceError(pipe)\n\n # Test if J coupling data exists.\n if j:\n # Search for interatomic data.\n data = False\n for interatom in interatomic_loop():\n if hasattr(interatom, 'j_coupling'):\n data = True\n break\n\n # No data.\n if not data:\n raise RelaxNoJError()","def test_start_analysis_pipeline_not_multiplexed(self, mock_popen, mock_is_multiplexed, mock_get_fc_code):\n mock_get_fc_code.return_value = 'FLO-FLG001'\n mock_is_multiplexed.return_value = False\n run_dir = 'data/nanopore_data/run4/done_demuxing/20200104_1412_MN19414_AAU644_68125dc2'\n sample_sheet = 'data/nanopore_data/run4/done_demuxing/20200104_1412_MN19414_AAU644_68125dc2/SQK-LSK109_sample_sheet.csv'\n run = MinIONqc(run_dir, sample_sheet, None)\n run.start_nanoseq()\n expected_parameters = ('nextflow run nf-core/nanoseq'\n + ' -r ' + CONFIG.get('nanopore_analysis').get('minion_qc_run').get('nanoseq_version')\n + ' --input ' + sample_sheet\n + ' --protocol DNA'\n + ' --input_path ' + os.path.join(run_dir, 'fast5')\n + ' --outdir ' + os.path.join(run_dir, 'nanoseq_output')\n + ' --flowcell FLO-FLG001'\n + ' --guppy_gpu'\n + ' --skip_alignment'\n + ' --skip_quantification'\n + ' --kit SQK-LSK109'\n + ' --max_cpus 6'\n + ' --max_memory 20.GB'\n + ' -profile singularity; echo $? > .exitcode_for_nanoseq')\n mock_popen.assert_called_once_with(expected_parameters, stdout=subprocess.PIPE, shell=True, cwd=run_dir)","def test_stream_loop(self):\n chans, gains, scans, rate = (10,10,10,10), (1,2,4,5), 1024, 500\n v = [v[0] for v in self.l.stream_sync(\n channels=chans, gains=gains,\n num_scans=scans, rate=rate)]\n for vi in v:\n for r in vi:\n self.assertTrue(abs(r-2.5) < .1,\n \"%s should be cal, 2.5v\" % vi[0])","def test_test(self):\n\n # The following should do nothing as the pipes exist.\n pipes.check_pipe()\n pipes.check_pipe('orig')\n pipes.check_pipe('empty')\n\n # Assert that a RelaxNoPipeError occurs when the pipe doesn't exist.\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe, 'x')\n\n # Reset relax.\n reset()\n\n # Now none of the following pipes exist, hence errors should be thrown.\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe)\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe, 'orig')\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe, 'empty')","def test_count_no_spins(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 0)","def setUp(self):\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Name the first molecule.\n cdp.mol[0].name = 'Ap4Aase'\n\n # Add a second molecule to the system.\n cdp.mol.add_item(mol_name='RNA')\n\n # Add two more residues to the first molecule (and set the residue number of the first).\n cdp.mol[0].res[0].num = 1\n cdp.mol[0].res.add_item(res_num=2, res_name='Glu')\n cdp.mol[0].res.add_item(res_num=4, res_name='Pro')\n\n # Add some spin info to this molecule.\n cdp.mol[0].res[0].spin[0].name = 'NH'\n cdp.mol[0].res[0].spin[0].num = 60\n cdp.mol[0].res[1].spin[0].name = 'NH'\n cdp.mol[0].res[1].spin[0].num = 63\n\n # Add one more residue to the second molecule (and set the residue number of the first).\n cdp.mol[1].res[0].num = -5\n cdp.mol[1].res.add_item(res_num=-4)\n\n # Add a second set of spins to the second molecule (naming the first set first).\n cdp.mol[1].res[0].spin[0].name = 'C8'\n cdp.mol[1].res[1].spin[0].name = 'C8'\n cdp.mol[1].res[0].spin.add_item(spin_name='N5')\n cdp.mol[1].res[1].spin.add_item(spin_name='N5')\n cdp.mol[1].res[1].spin.add_item(spin_name='2H', spin_num=132)\n\n # Deselect a number of spins.\n cdp.mol[0].res[0].spin[0].select = 0\n cdp.mol[0].res[2].spin[0].select = 0\n cdp.mol[1].res[0].spin[0].select = 0\n cdp.mol[1].res[1].spin[1].select = 0\n\n # Update the metadata.\n mol_res_spin.metadata_update()","def test_invoke_pipe_not_found():\n\n testapp = holocron.Application()\n\n with pytest.raises(ValueError) as excinfo:\n next(testapp.invoke(\"test\"))\n\n assert str(excinfo.value) == \"no such pipe: 'test'\"","def _handle_loop(self):\n pass","def infinite_loop():\n return True","def test_noFailure(self):\n for i in range(10):\n self.assertTrue(self.circuit_breaker.available())","def run_no_input(self, initial=None, context=None):\n for _ in self.run(initial, context):\n raise RuntimeError(\"Machine requires input to continue!\")","def handle_stop(_):\n loop.force_unmute()","def test_readiness(self):\n self.command.package = self.input_ovf\n ready, reason = self.command.ready_to_run()\n self.assertFalse(ready)\n self.assertRegex(reason, \"No file information\")\n self.assertRaises(InvalidInputError, self.command.run)\n\n self.command.file_path = \"input.vmdk\"\n ready, reason = self.command.ready_to_run()\n self.assertTrue(ready)\n\n self.command.file_path = None\n self.command.file_id = \"file1\"\n ready, reason = self.command.ready_to_run()\n self.assertTrue(ready)","def test_halts_if_halt_on_next(self, get_pipe_manager, raise_error):\n pm = get_pipe_manager(name=\"TestPM\")\n pm.halt_on_next = True\n if raise_error:\n with pytest.raises(PipelineHalt):\n pm.timestamp(\"testing\")\n else:\n pm.timestamp(\"testing\", raise_error=False)\n assert pm.halted","def do_simulation_loop(self) -> tuple[bool, bool]:\n running, reset = True, False\n for event in pygame.event.get():\n if check_for_quit(event):\n running = False\n elif check_for_reset(event):\n running = False\n reset = True\n self.simulation.do_step()\n self.update_visualization()\n self.simple_pygame.loop()\n return running, reset","def nanny(self): \n while not self.started and not self.failed:\n eventlet.sleep(.1)\n return not self.failed","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","async def get_peak_loop(self):\n while True:\n try:\n self.blockchain_state = await self.node_rpc_client.get_blockchain_state()\n self.wallet_synced = await self.wallet_rpc_client.get_synced()\n await asyncio.sleep(30)\n except asyncio.CancelledError:\n self.log.info(\"Cancelled get_peak_loop, closing\")\n return\n except Exception as e:\n self.log.error(f\"Unexpected error in get_peak_loop: {e}\")\n await asyncio.sleep(30)","async def get_peak_loop(self):\n while True:\n try:\n self.blockchain_state = await self.node_rpc_client.get_blockchain_state()\n self.wallet_synced = await self.wallet_rpc_client.get_synced()\n await asyncio.sleep(30)\n except asyncio.CancelledError:\n self.log.info(\"Cancelled get_peak_loop, closing\")\n return\n except Exception as e:\n self.log.error(f\"Unexpected error in get_peak_loop: {e}\")\n await asyncio.sleep(30)","def test_close():\n while True:\n yield","def wait_for_data(receiver):\n\n while not receiver.available(pipes[1]):\n time.sleep(0.01)","def run(self):\n while self.container.process(): pass","def test_runsUntilSyncCallback(self):\n def main(reactor):\n return defer.succeed(None)\n r = _FakeReactor()\n exitError = self.assertRaises(\n SystemExit, task.react, main, _reactor=r)\n self.assertEqual(0, exitError.code)\n self.assertEqual(r.seconds(), 0)","def test_sync_task_no_server(comm):\n run_server, server_args, run_client, client_args = helper_config(comm, \"sync\")\n client = run_client(**client_args)\n try:\n client.connect()\n except Exception as exc: # pylint: disable=broad-except\n assert False, f\"unexpected exception: {exc}\"\n sleep(0.1)\n if comm == \"udp\":\n rr = client.read_coils(1, 1, slave=0x01)\n assert isinstance(rr, ModbusIOException)\n else:\n with pytest.raises((asyncio.exceptions.TimeoutError, ConnectionException)):\n client.read_coils(1, 1, slave=0x01)\n client.close()","def _run(self):\n global _iom_instance\n self.__logger.info(\"IOManager started\")\n timeout = 0\n while self.__running:\n # Poll for events\n if self.__et:\n self.__poll_et()\n else:\n self.__poll_lt()\n\n # Perform IOWrapper checking on the actual\n # frequency of the ticker, not each time\n # there is data to read or write\n if time.time() >= self.__next_tick:\n self.__next_tick += self.__ticker.get_ticktime()\n # Call the handle loop function of each connected wrapper\n self.__handle_loop()\n # Attempt to connect all IOWrappers\n self.__attempt_wrappers()\n # Check if IOManager should keep running\n self.__check_stop()\n # Allow for control to be interrupted if other threads require\n # attention. Do not waste time on this so use a very short sleep\n time.sleep(0.0001)\n\n self.__cleanup()\n clear_IOM()\n self.__logger.debug(\"Savings of wakeup pipe: %f seconds\" % self.__saved_time)\n self.__logger.info(\"IOManager stopped\")","def algorithm_loop(self):","def test_start_analysis_pipeline_multiplexed(self, mock_popen, mock_is_multiplexed, mock_get_fc_code):\n mock_get_fc_code.return_value = 'FLO-FLG001'\n mock_is_multiplexed.return_value = True\n run_dir = 'data/nanopore_data/run4/done_demuxing/20200104_1412_MN19414_AAU644_68125dc2'\n sample_sheet = 'data/nanopore_data/run4/done_demuxing/20200104_1412_MN19414_AAU644_68125dc2/SQK-LSK109_sample_sheet.csv'\n run = MinIONqc(run_dir, sample_sheet, None)\n run.start_nanoseq()\n expected_parameters = ('nextflow run nf-core/nanoseq'\n + ' -r ' + CONFIG.get('nanopore_analysis').get('minion_qc_run').get('nanoseq_version')\n + ' --input ' + sample_sheet\n + ' --protocol DNA'\n + ' --input_path ' + os.path.join(run_dir, 'fast5')\n + ' --outdir ' + os.path.join(run_dir, 'nanoseq_output')\n + ' --flowcell FLO-FLG001'\n + ' --guppy_gpu'\n + ' --skip_alignment'\n + ' --skip_quantification'\n + ' --kit SQK-LSK109'\n + ' --max_cpus 6'\n + ' --max_memory 20.GB'\n + ' --barcode_kit EXP-NBD104'\n + ' -profile singularity; echo $? > .exitcode_for_nanoseq')\n mock_popen.assert_called_once_with(expected_parameters, stdout=subprocess.PIPE, shell=True, cwd=run_dir)","def pauseLoop(self):\n print('SYNC stim detected LOW')\n self.loopRunning = False","def test_modul1(self):\n\n self.delayDisplay(\"Starting the test\")\n #\n # first, get some data\n #\n import urllib\n downloads = (\n ('http://slicer.kitware.com/midas3/download?items=5767', 'FA.nrrd', slicer.util.loadVolume),\n )\n\n for url,name,loader in downloads:\n filePath = slicer.app.temporaryPath + '/' + name\n if not os.path.exists(filePath) or os.stat(filePath).st_size == 0:\n logging.info('Requesting download %s from %s...\\n' % (name, url))\n urllib.urlretrieve(url, filePath)\n if loader:\n logging.info('Loading %s...' % (name,))\n loader(filePath)\n self.delayDisplay('Finished with download and loading')\n\n volumeNode = slicer.util.getNode(pattern=\"FA\")\n logic = modulLogic()\n self.assertTrue( logic.hasImageData(volumeNode) )\n self.delayDisplay('Test passed!')","def test_pump_bypass_on_reverse_flow(use_numba):\n net = pandapipes.create_empty_network(\"net\", add_stdtypes=True)\n\n j1 = pandapipes.create_junction(net, pn_bar=5, tfluid_k=283.15)\n j2 = pandapipes.create_junction(net, pn_bar=5, tfluid_k=283.15)\n j3 = pandapipes.create_junction(net, pn_bar=5, tfluid_k=283.15)\n j4 = pandapipes.create_junction(net, pn_bar=5, tfluid_k=283.15)\n\n pandapipes.create_pipe(net, j1, j2, std_type='125_PE_80_SDR_11', k_mm=1., length_km=10)\n pandapipes.create_pipe(net, j3, j4, std_type='125_PE_80_SDR_11', k_mm=1., length_km=12)\n pandapipes.create_ext_grid(net, j1, 5, 283.15, type=\"p\")\n pandapipes.create_pump(net, j2, j3, std_type='P1')\n pandapipes.create_source(net, j4, 0.02333)\n\n pandapipes.create_fluid_from_lib(net, \"hgas\", overwrite=True)\n\n pandapipes.pipeflow(net, stop_condition=\"tol\", iter=3, friction_model=\"nikuradse\",\n mode=\"hydraulics\", transient=False, nonlinear_method=\"automatic\",\n tol_p=1e-4, tol_v=1e-4, use_numba=use_numba)\n\n assert net.res_pump.deltap_bar.isin([0]).all()\n assert np.isclose(net.res_junction.loc[1, \"p_bar\"], net.res_junction.loc[2, \"p_bar\"])","def test_block_missing_batch(self):\n pass","def test_chunk_QuantumVolume(self, method, device):\n opts = {\"blocking_enable\": True, \"blocking_qubits\": 2}\n\n backend = self.backend(method=method, device=device, **opts)\n backend_no_chunk = self.backend(method=method, device=device)\n\n shots = 100\n num_qubits = 4\n depth = 10\n circuit = transpile(\n QuantumVolume(num_qubits, depth, seed=0), backend=backend, optimization_level=0\n )\n circuit.measure_all()\n\n result = backend.run(circuit, shots=shots, memory=True).result()\n counts = result.get_counts(circuit)\n result_no_chunk = backend_no_chunk.run(circuit, shots=shots, memory=True).result()\n counts_no_chunk = result_no_chunk.get_counts(circuit)\n\n self.assertEqual(counts_no_chunk, counts)","def test_analog_in_out_loop(self):\n for v in range(0, 6, 1):\n self.l.output(ao0=v, ao1=v)\n r = self.l.input(channels=(8,8,9,9), gains=(1,4,1,4))[0]\n for i in r:\n self.assertTrue(abs(v-i) < .1,\n \"measured %g for %g\" % (i, v))","def has_loop(self) -> bool:\n try:\n list(self)\n return False\n except ContainsLoopError:\n return True","def checkDone(self):\n # checks if the instructions in the pipeline are nop are not\n # if all nop then we are done\n self.__done = True\n for pi in self.pipeline:\n if pi.instr is not None:\n self.__done = False","def loop_run(self):\n super(HasLoops, self).loop_run()\n for loop in getattr(self, \"_loops\", []):\n loop.loop_remove_from_parent = weak_method(self.remove_loop)\n loop.loop_run()","def test_notRunning_pump_noValve(self):\n\t\tdef mock_def(uri, *args):\n\t\t\tif(uri == u\"ch.db.getdevicedata\"):\n\t\t\t\treturn {'name':'testPump', 'type':'pump', 'group':-1, 'id':1, 'description': ''}\n\t\t\telif(uri == u\"ch.gpio.isrunning\"):\n\t\t\t\treturn False\n\t\t\telif(uri == u\"ch.db.getdevicegroup\"):\n\t\t\t\treturn([])\n\t\t\telse:\n\t\t\t\traise ValueError(\"Given URI does not exist ({})\".format(uri))\n\n\t\tdm = DeviceManager()\n\t\tdm.sessionID = None\n\t\tdm.call=MagicMock(side_effect=mock_def)\n\t\tdm.publish=MagicMock()\n\t\tself.failureResultOf(dm.switchIfAllowed('testPump', None), ApplicationError)","def test_for_loop(self, modes, parse_input_mocked_metadata):\n bb = parse_input_mocked_metadata(\n \"for int m in {}\\n\\tMeasureFock() | m\".format(modes)\n )\n assert np.all(\n bb._forvar[\"m\"] == np.array(modes)\n )\n assert bb.operations == [\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[0]]},\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[1]]},\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[2]]}\n ]","async def main(dut):\n # Create a 10us period clock on port clk\n clock = Clock(dut.clk_i, 10, units=\"us\")\n cocotb.fork(clock.start())\n\n # Reset system\n await FallingEdge(dut.clk_i)\n dut.rst_n_i <= 0\n dut.en_i <= 0\n dut.data_i <= 0\n dut.valid_i <= 0\n\n # reset\n await FallingEdge(dut.clk_i)\n dut.rst_n_i <= 1\n\n # test 1\n dut.en_i <= 1\n x, y = get_test_vector()\n cocotb.fork(write_input(dut, x))\n await check_output(dut, y)\n\n # test 2\n dut.en_i <= 0\n await check_output_no_en(dut)\n\n # test 3\n dut.en_i <= 1\n x, y = get_test_vector()\n cocotb.fork(write_input(dut, x))\n await check_output(dut, y)","def startLoop():\n patchAsyncio()","def timeout_loop(self):\r\n\r\n while not done:\r\n\r\n if (softwareInterfaceTimeout != -1) and (interfaceNotUsed > softwareInterfaceTimeout):\r\n\r\n stop(False)\r\n\r\n \r\n\r\n time.sleep(MONITOR_INTERVAL/1000000.0)\r\n\r\n self.interfaceNotUsed = self.interfaceNotUsed + 1","def testReset(self):\n \n clk = Signal(0)\n rst = Signal(1)\n clock_gen = ClkDriver(clk, period=4)\n \n out = Signal(intbv(0)[4:])\n counter = Counter(out, clk, rst)\n \n def test():\n for i in range(200):\n # count up to 9 then reset\n if int(out) == 9:\n rst.next = 0\n yield delay(1)\n self.assertEqual(int(out), 0)\n # turn off reset next time\n else:\n rst.next = 1\n yield delay(1)\n \n check = test()\n sim = Simulation(counter, clock_gen, check)\n sim.run(400, quiet=1)","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_halts_if_hitting_exclusive_halt_point(self, get_pipe_manager, raise_error):\n\n # Create manager, set halt point, and check that it's running.\n halt_name = \"phase3\"\n pm = get_pipe_manager(name=\"TestPM\")\n pm.stop_before = halt_name\n\n # Make non-halting checkpointed timestamp calls.\n pm.timestamp(checkpoint=\"phase1\")\n assert not pm.halted\n pm.timestamp(checkpoint=\"phase2\")\n assert not pm.halted\n\n # Make the halt-inducing checkpointed timestamp call.\n if raise_error:\n with pytest.raises(PipelineHalt):\n pm.timestamp(checkpoint=halt_name, raise_error=True)\n else:\n pm.timestamp(checkpoint=halt_name, raise_error=False)\n # Verify that we've halted.\n try:\n assert pm.halted\n except AssertionError:\n print(\"STATUS: {}\".format(pm.status))\n raise","def run(self):\n\n if self.success and not self.running:\n self.log.info(\"Humidity and temp control started...\")\n self.running = True\n elif self.testmode and not self.running:\n self.log.critical(\"Humidity and temp TEST MODE started!!!\")\n self.running = True\n elif not self.running:\n self.log.info(\"Humidity and temp control NOT started...\")\n return\n\n if not self.stop_measurement_loop and self.success:\n try:\n # Query the environemnt etc from Brandbox\n envvalues = self.vcw.query(\n self.resource, self.resource[\"get_environment\"]\n )\n envvalues = envvalues.split(\",\")\n\n # Get dewpoint\n boxvalues = self.vcw.query(\n self.resource, self.resource[\"get_box_environment\"]\n )\n boxvalues = boxvalues.split(\",\")\n\n vacuumvalues = self.vcw.query(\n self.resource, self.resource[\"get_vacuum\"]\n )\n\n # get light\n luxvalues = self.vcw.query(self.resource, self.resource[\"get_lux\"])\n luxvalues = luxvalues.split(\",\")[0]\n\n # if an error happen, as so often with the brandbox read the queue\n if self.readqueue:\n try:\n ans = self.vcw.read(self.resource)\n if ans:\n self.log.critical(\"Brandbox had an non empty queue: {}\".format(ans))\n except:\n self.log.info(\"Brandbox indicated an non empty queue, reading queue yielded no queue...\", exc_info=True)\n\n\n try:\n if float(luxvalues) >= 0.5:\n self.framework[\"Configs\"][\"config\"][\"settings\"][\"lights\"] = True\n else:\n self.framework[\"Configs\"][\"config\"][\"settings\"][\"lights\"] = False\n\n # get door\n # doorvalues = self.vcw.query(self.resource, self.resource[\"get_door\"])\n # doorvalues = doorvalues.split(\",\")[0]\n # if doorvalues == \"1\":\n # self.framework[\"Configs\"][\"config\"][\"settings\"][\"door\"] = False\n # else:\n # self.framework[\"Configs\"][\"config\"][\"settings\"][\"door\"] = True\n\n # get light\n vacuumvalues = vacuumvalues.split(\",\")[0]\n if vacuumvalues == \"1\":\n self.framework[\"Configs\"][\"config\"][\"settings\"][\"vacuum\"] = True\n else:\n self.framework[\"Configs\"][\"config\"][\"settings\"][\"vacuum\"] = False\n\n # Here a list\n self.main.humidity_history = np.append(\n self.main.humidity_history, float(envvalues[1])\n ) # todo: memory leak since no values will be deleted\n self.main.temperatur_history = np.append(\n self.main.humidity_history, float(envvalues[3])\n )\n\n # Write the pt100 and light status and environement in the box to the global variables\n self.framework[\"Configs\"][\"config\"][\"settings\"][\n \"chuck_temperature\"\n ] = float(envvalues[3])\n self.framework[\"Configs\"][\"config\"][\"settings\"][\n \"air_temperature\"\n ] = float(envvalues[0])\n self.framework[\"Configs\"][\"config\"][\"settings\"][\"dew_point\"] = float(\n boxvalues[3]\n )\n\n # Send data to main\n self.queue_to_main.put(\n {\n \"temperature_air\": [float(time()), float(envvalues[0])],\n \"temperature_chuck\": [float(time()), float(envvalues[3])],\n \"dew_point\": [float(time()), float(boxvalues[3])],\n \"humidity\": [float(time()), float(envvalues[1])],\n }\n )\n except:\n self.readqueue = True\n\n except Exception as err:\n self.log.error(\n \"The temperature and humidity controller seems not to be responding. Error: {!s}\".format(\n err\n ),\n exc_info=True,\n )\n\n elif self.testmode:\n self.log.critical(\"Testmode sends message to main!\")\n self.queue_to_main.put(\n {\n \"temperature\": [float(time()), float(random.randint(1, 10))],\n \"humidity\": [float(time()), float(random.randint(1, 10))],\n }\n )\n\n if not self.main.stop_measurement_loop:\n self.start_timer(self.run)\n else:\n self.log.info(\n \"Shutting down environment control due to stop of measurement loop\"\n )","def _readloop(self):\r\n\r\n while self._ll_alive:\r\n with self._rx_lock:\r\n data = self._Random(1)\r\n if len(data) != 0: # check for timeout\r\n self._uart_rx_queue.put(data)","def test_shutdown_restart(self):\n log.info(\"CONFIG: %s\", self._agent_config())\n self.create_sample_data_set_dir('node59p1_step2.dat', TELEM_DIR, \"node59p1.dat\")\n\n self.assert_initialize(final_state=ResourceAgentState.COMMAND)\n\n # Slow down processing to 1 per second to give us time to stop\n self.dataset_agent_client.set_resource({DriverParameter.RECORDS_PER_SECOND: 1})\n self.assert_start_sampling()\n\n # Verify we get one sample\n try:\n # Read the first file and verify the data\n result = self.data_subscribers.get_samples(DataParticleType.CONTROL, 1)\n result1 = self.data_subscribers.get_samples(DataParticleType.SAMPLE, 3)\n result.extend(result1)\n log.debug(\"RESULT: %s\", result)\n\n # Verify values\n self.assert_data_values(result, 'test_data_1-2.txt.result.yml')\n self.assert_sample_queue_size(DataParticleType.CONTROL, 0)\n self.assert_sample_queue_size(DataParticleType.SAMPLE, 0)\n\n self.create_sample_data_set_dir('node59p1_step4.dat', TELEM_DIR, \"node59p1.dat\")\n # Now read the first record of the second file then stop\n result = self.data_subscribers.get_samples(DataParticleType.SAMPLE, 3)\n log.debug(\"RESULT 1: %s\", result)\n self.assert_stop_sampling()\n self.assert_sample_queue_size(DataParticleType.CONTROL, 0)\n self.assert_sample_queue_size(DataParticleType.SAMPLE, 0)\n\n # stop and re-start the agent\n self.stop_dataset_agent_client()\n self.init_dataset_agent_client()\n # re-initialize\n self.assert_initialize()\n\n result2 = self.data_subscribers.get_samples(DataParticleType.SAMPLE, 3)\n log.debug(\"RESULT 2: %s\", result2)\n result.extend(result2)\n log.debug(\"RESULT: %s\", result)\n self.assert_data_values(result, 'test_data_3-4.txt.result.yml')\n self.assert_sample_queue_size(DataParticleType.CONTROL, 0)\n self.assert_sample_queue_size(DataParticleType.SAMPLE, 0)\n except SampleTimeout as e:\n log.error(\"Exception trapped: %s\", e, exc_info=True)\n self.fail(\"Sample timeout.\")","def test_init_done():\n with pytest.raises(MLOpsException):\n pm.set_stat(\"st1\", 5.5)\n\n with pytest.raises(MLOpsException):\n pm.done()\n\n pm.init(ctx=None, mlops_mode=MLOpsMode.STAND_ALONE)\n pm.done()"],"string":"[\n \"def test_molecule_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the molecules.\\n i = 0\\n for molecule in mol_res_spin.molecule_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_spin_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for spin in mol_res_spin.spin_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_molecule_loop_no_selection(self):\\n\\n # Molecule data.\\n name = ['Ap4Aase', 'RNA']\\n\\n # Loop over the molecules.\\n i = 0\\n for mol in mol_res_spin.molecule_loop():\\n # Test the molecule names.\\n self.assertEqual(mol.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)\",\n \"def test_residue_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for residue in mol_res_spin.residue_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_molecule_loop(self):\\n\\n # Loop over the molecules.\\n for mol in mol_res_spin.molecule_loop('#RNA'):\\n # Test the molecule name.\\n self.assertEqual(mol.name, 'RNA')\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def test_return_molecule_pipe_fail(self):\\n\\n # Try to get a molecule from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')\",\n \"def test_spin_loop_no_selection(self):\\n\\n # Spin data.\\n select = [0, 1, 0, 0, 1, 1, 0, 1]\\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 8)\",\n \"def test_spin_loop(self):\\n\\n # Spin data.\\n select = [1, 0]\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, 'N5')\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 2)\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_circularloop(self):\\n cmd = f\\\"{SRC_LISTER} -i {PWD}/main\\\"\\n with subprocess.Popen(\\n shlex.split(cmd), stdout=subprocess.PIPE, stderr=subprocess.PIPE\\n ) as proc:\\n try:\\n out, err = proc.communicate(timeout=5)\\n assert len(err.strip()) > 0, \\\"Expected a circular reference error\\\"\\n except subprocess.TimeoutExpired as te:\\n print(\\\"Unexpected parser timeout during infinite loop test\\\")\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_spin_loop_multiatom(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_run_loop_success(self):\\n found = False\\n pyint = Interpreter(limit=15)\\n try:\\n pyint.run(code=BF_CODE_LOOP_TWICE)\\n except SystemExit: \\n found = True\\n self.assertFalse(found)\",\n \"def test_spin_loop_wildcard(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N*'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_run_molecule_not_selected(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\", sequence, molecule_selector=lambda mol: False\\n )\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert vermouth.utils.are_all_equal(found)\\n assert found[0] is None\",\n \"def test_return_spin_pipe_fail(self):\\n\\n # Try to get a spin from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')\",\n \"def test_no_immediate_stop(self):\\n script = ControlScript()\\n options = ControlOptions()\\n options.parseOptions([b\\\"--data-path\\\", self.mktemp()])\\n self.assertNoResult(script.main(MemoryCoreReactor(), options))\",\n \"def run(self):\\n while True:\\n if self.job_q.empty():\\n self.message_q.put(False)\\n return\\n try:\\n smolecule = self.job_q.get()\\n self.data_pointer[smolecule].get_adp(self.Temp)\\n except IndexError:\\n self.message_q.put((smolecule, None))\\n try:\\n self.message_q.put((smolecule, [j.adp['cart_int'] for j in self.data_pointer[smolecule].atoms]))\\n except KeyError:\\n # =======================================================\\n # self.message_q.put((molecule,[0 for i in self.data_pointer[molecule].atoms]))\\n #=======================================================\\n pass\",\n \"def test_count_spins_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Test for the error.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.count_spins)\",\n \"def loop(self):\\n raise NotImplementedError()\",\n \"async def checkNewLoop(self):\\n pass\",\n \"def test_multi_molecules_cycle_one(self, multi_mol_system_irregular):\\n sequence = \\\"A\\\"\\n expected = [sequence] * (15 * 3)\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_irregular)\\n found = self.sequence_from_system(multi_mol_system_irregular, \\\"test\\\")\\n assert found == expected\",\n \"def _run(self):\\n while(self._loop):\\n pass\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_reset(self):\\n ran = []\\n def foo():\\n ran.append(None)\\n\\n c = task.Clock()\\n lc = TestableLoopingCall(c, foo)\\n lc.start(2, now=False)\\n c.advance(1)\\n lc.reset()\\n c.advance(1)\\n self.assertEqual(ran, [])\\n c.advance(1)\\n self.assertEqual(ran, [None])\",\n \"def test_return_residue_pipe_fail(self):\\n\\n # Try to get a residue from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')\",\n \"def test_multi_molecules_cycle(self, multi_mol_system_regular, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n expected = expected * 3\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_regular)\\n found = self.sequence_from_system(multi_mol_system_regular, \\\"test\\\")\\n assert found == expected\",\n \"def loop(self):\\n pass\",\n \"def test_return_molecule(self):\\n\\n # Ask for a few molecules.\\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\\n\\n # Test the data of molecule 1.\\n self.assertEqual(mol1.name, 'Ap4Aase')\\n\\n # Test the data of molecule 2.\\n self.assertEqual(mol2.name, 'RNA')\",\n \"def test_chunk_pauli(self, method, device):\\n opts_no_chunk = {\\\"fusion_enable\\\": False}\\n opts_chunk = copy.copy(opts_no_chunk)\\n opts_chunk[\\\"blocking_enable\\\"] = True\\n opts_chunk[\\\"blocking_qubits\\\"] = 3\\n\\n backend = self.backend(method=method, device=device, **opts_chunk)\\n backend_no_chunk = self.backend(method=method, device=device, **opts_no_chunk)\\n\\n shots = 100\\n\\n qr = QuantumRegister(5)\\n cr = ClassicalRegister(5)\\n regs = (qr, cr)\\n circuit = QuantumCircuit(*regs)\\n circuit.h(qr[0])\\n circuit.h(qr[1])\\n circuit.h(qr[2])\\n circuit.h(qr[3])\\n circuit.h(qr[4])\\n circuit.pauli(\\\"YXZYX\\\", qr)\\n circuit.measure_all()\\n\\n result = backend.run(circuit, shots=shots, memory=True).result()\\n counts = result.get_counts(circuit)\\n result_no_chunk = backend_no_chunk.run(circuit, shots=shots, memory=True).result()\\n counts_no_chunk = result_no_chunk.get_counts(circuit)\\n\\n self.assertEqual(counts_no_chunk, counts)\",\n \"def testPipeFound(self):\\n safeFoundHelper(self)\\n self.assertCurrentState(safe.Seeking)\",\n \"async def hold_loop(self, *args) -> bool:\\n raise NotImplementedError\",\n \"def test_single_molecules_cycle_one(self, single_mol_system):\\n sequence = \\\"A\\\"\\n expected = [sequence] * (5 * 3)\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def _while_loop(pd, nmax, max_loop, ncore, outfile):\\n \\n # make sure the random seed is different for every processor\\n random_number_seeds = [3456789, 7654321, 2435467, 8273645,\\n 1085712, 4154712, 1248291, 8415917,\\n 2345161, 5710916, 5718601, 7516234,\\n 9235161, 4917519, 1111245, 8167834] \\n \\n # get the processor ID (1 - Ncore) and convert to single integer\\n current = multiprocessing.current_process()\\n pid = current._identity\\n pid = pid[0]\\n \\n #\\n # choose a different seed for each processor from the list so each processor has\\n # a different randum number seed. Then, fiddle with each seed a little so \\n # the seeds aren't the same every time the code is run\\n seed = np.int(random_number_seeds[pid] * (np.random.rand()*(10.0 - 0.01) + 0.01))\\n \\n np.random.seed(seed)\\n \\n #print 'id and seed', pid, seed\\n \\n n_particles = 0\\n loop_counter = 0\\n fmin_scale = 1.0E-100 # -16 -> -32 -> -100\\n F_max = np.max(pd.DF.f) #; F_min = np.min(pd.DF.f);\\n F_min = np.min(pd.DF.f) * fmin_scale\\n # F_max = np.max(pd.DF.f[:-1])#; F_max = 1.0E-88\\n #print F_min, F_max\\n if pd.optimize:\\n relative_potential = pd._interpolate_relative_potential\\n else:\\n relative_potential = pd.DF.relative_potential\\n \\n \\n pos = np.zeros((nmax, 3))\\n vel = np.zeros((nmax, 3)) \\n \\n while (( n_particles < nmax) and (loop_counter < max_loop)):\\n \\n r = pd._choose_position()\\n Psi = relative_potential(r) \\n \\n v = pd._choose_velocity(r, Psi)\\n \\n E = Psi - 0.5 * v * v\\n \\n f_E = pd.DF.interpolate_f(E)\\n \\n logF = ( np.random.rand()*(np.log10(F_max) - np.log10(F_min)) + np.log10(F_min) )\\n \\n # if choosing random F in log F, might be good to do the comparison in logspace as well\\n #.... i.e log(F) <= log(f_E) \\n #\\n # 0 FOR F_E MEANS THAT E < E_min of the potential. THis happens when Psi - KE is smaller\\n # than the value of the potential at large_r... should this be considered unbound \\n # even though it isn't zero? Is this effectively zero? This has been adjusted in the velocity\\n # picking routine but needs verification to make sure it works.... but regardless, I doubt\\n # that this is the reason why the particles are failing for NFW but working for hernquist....\\n #\\n if np.abs(np.log10(f_E)) == np.inf:\\n keep_particle = False\\n _my_print('log value error... throwing out particle')\\n else:\\n keep_particle = (logF <= np.log10(f_E))\\n\\n \\n if keep_particle: \\n index = n_particles \\n \\n # \\n # need to sample in cosine theta NOT theta!!!!! WTF!!!!!\\n #\\n #\\n \\n theta = np.arccos( np.random.rand() * (2.0) - 1.0)\\n \\n # convert position to cartesian using random theta and phi\\n phi = np.random.rand() * 2.0 * np.pi\\n \\n x = np.sin(theta) * np.cos(phi)\\n y = np.sin(theta) * np.sin(phi)\\n z = np.cos(theta)\\n \\n pos[index] = r * np.array([x,y,z])\\n\\n # repeat for velocity using new random numbersw\\n theta = np.arccos( np.random.rand() * (2.0) - 1.0)\\n phi = np.random.rand() * 2.0 * np.pi\\n \\n vx = np.sin(theta) * np.cos(phi)\\n vy = np.sin(theta) * np.sin(phi)\\n vz = np.cos(theta)\\n \\n vel[index] = v * np.array([vx,vy,vz])\\n \\\"\\\"\\\" \\n #else: # do strict cartesian ... slower.... less attractive\\n # \\n # axis_list = [0, 1, 2]\\n # random.shuffle(axis_list)\\n \\n # #axis_index = np.random.randint(3)\\n # first_axis = axis_list[0]\\n #\\n # pos[index, first_axis] = np.random.rand() * (2.0*r) - r\\n #del axis_list[axis_index]\\n \\n #axis_index = np.random.randint(2)\\n # second_axis = axis_list[1]\\n \\n max_r = np.sqrt(r*r - pos[index,first_axis]**2)\\n \\n pos[index, second_axis] = np.random.rand()*(2.0 * max_r) - max_r\\n #del axis_list[axis_index]\\n \\n max_r = np.sqrt(r*r - pos[index,first_axis]**2 - pos[index,second_axis]**2)\\n \\n third_axis = axis_list[2]\\n pos[index, third_axis] = np.random.rand() * (2.0 * max_r) - max_r\\n \\n if np.sqrt(pos[index,0]**2 + pos[index,1]**2 + pos[index,2]**2) > r:\\n _my_print('R IS TOO LARGE')\\n \\n ###\\n axis_list = [0, 1, 2]\\n random.shuffle(axis_list)\\n \\n #axis_index = np.random.randint(3)\\n first_axis = axis_list[0]\\n \\n vel[index, first_axis] = np.random.rand() * (2.0*v) - v\\n #del axis_list[axis_index]\\n \\n #axis_index = np.random.randint(2)\\n second_axis = axis_list[1]\\n \\n max_v = np.sqrt(v*v - vel[index,first_axis]**2)\\n \\n vel[index, second_axis] = np.random.rand()*(2.0 * max_v) - max_v\\n #del axis_list[axis_index]\\n \\n max_v = np.sqrt(v*v - vel[index,first_axis]**2 - vel[index,second_axis]**2)\\n \\n third_axis = axis_list[2]\\n vel[index, third_axis] = np.random.rand() * (2.0 * max_v) - max_v \\n \\n \\n \\\"\\\"\\\"\\n n_particles = n_particles + 1\\n \\n if (loop_counter % 5000) == 0:\\n _my_print(\\\"Have %4i particles. On loop %6i\\\"%(n_particles, loop_counter))\\n loop_counter = loop_counter + 1\\n \\n # now write out to a temporary file\\n f = open(outfile + \\\"_%02i_\\\"%(pid) + \\\".temp\\\", 'w')\\n fmt = \\\"%12.12E %12.12E %12.12E %12.12E %12.12E %12.12E %12.12E\\\\n\\\"\\n \\n \\n for i in np.arange(nmax):\\n f.write(fmt%(pd.M_part, pos[i,0], pos[i,1], pos[i,2], \\n vel[i,0], vel[i,1], vel[i,2]))\\n \\n \\n f.close() \\n \\n return pos, vel\",\n \"def test_control_loop_example():\\n example.control.print_error_measurement()\\n matplotlib.use('agg')\\n example.control.visualise_error_measurement(fig_file='cs_compare.pdf')\\n assert path.isfile('cs_compare.pdf')\\n example.control.sil_comparison()\",\n \"def run_one_test_cycle(self):\\n logging.info(\\n \\\"{0} operations remaining: {1}\\\".format(\\n self.args.pm_operation, self.args.repetitions\\n )\\n )\\n\\n self.check_last_cycle_duration()\\n if self.args.repetitions > 0:\\n self.run_pm_command()\\n else:\\n self.summary()\",\n \"def run(self):\\n # Define our components entry point\\n while True:\\n\\n # for each packet waiting on our input port\\n for packet in self.receive_all('in'):\\n try:\\n image = packet.get(\\\"data\\\")\\n log.debug(\\\"%s received %s %s\\\",\\n self.__class__.__name__, image.shape, image)\\n mask = np.zeros_like(image, dtype=np.bool)\\n for i, line in enumerate(image):\\n minimum = np.min(image[i])\\n factor = 1.1\\n threshold = factor * minimum\\n mask[i] = image[i] < threshold\\n packet.set(\\\"data\\\", mask)\\n except:\\n log.error('Component Failed: %s',\\n self.__class__.__name__, exc_info=True)\\n\\n # send the packet to the next component\\n self.send('out', packet)\\n\\n # yield the CPU, allowing another component to run\\n self.yield_ctrl()\",\n \"def test_empty_with_filter(multi_mol_system_irregular):\\n sequence = \\\"not empty\\\"\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\", sequence, molecule_selector=lambda mol: False\\n )\\n with pytest.raises(ValueError):\\n processor.run_system(multi_mol_system_irregular)\",\n \"def run(self):\\n while True:\\n try:\\n self.check_value()\\n except Exception as e:\\n print(f\\\"[ERROR]: Error running the continuous run loop on sample_module: {e}\\\")\\n continue\",\n \"def test_residue_loop(self):\\n\\n # Loop over the residues.\\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\\n # Test the selection.\\n self.assertEqual(res.num, 2)\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)\",\n \"def test_io_in_out_loop(self):\\n self.l.output(conf_io=0x1, state_io=0x0)\\n for i in range(10):\\n state_d, state_io, count = self.l.output(state_io=0x1)\\n self.assertTrue(state_io & 0x2)\\n state_d, state_io, count = self.l.output(state_io=0x0)\\n self.assertTrue(not state_io & 0x2)\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_fifo_sync_random():\\n pass\",\n \"def test_io_counter_loop(self):\\n self.l.output(conf_io=0x8, state_io=0x0)\\n self.l.count(reset=True)\\n for i in range(10):\\n self.l.output(state_io=0x8)\\n self.l.output(state_io=0x0)\\n c, t = self.l.count()\\n self.assertEqual(c, 9,\\n \\\"counted %g pulses\\\" % c)\",\n \"def run_until_stop(self):\\n while self.commands[self.pointer] != END:\\n # Get the cmd\\n cmd = self.commands[self.pointer]\\n opcode = cmd % 100\\n modes = cmd // 100\\n \\n vals, locs, self.pointer = get_vals_and_locs(opcode, modes, self.pointer, self.commands)\\n \\n if opcode == ADD:\\n self.commands[locs[2]] = vals[0] + vals[1]\\n elif opcode == MUL:\\n self.commands[locs[2]] = vals[0] * vals[1]\\n elif opcode == INP:\\n if self.inputs:\\n self.commands[locs[0]] = self.inputs.pop(0)\\n else:\\n # Put the pointer back, so we run this opcode again\\n self.pointer -= 2\\n return False\\n elif opcode == OUT:\\n self.outputs.append(vals[0])\\n elif opcode == JIT:\\n if vals[0] != 0:\\n self.pointer = vals[1]\\n elif opcode == JIF:\\n if vals[0] == 0:\\n self.pointer = vals[1]\\n elif opcode == LT:\\n self.commands[locs[2]] = 1 if vals[0] < vals[1] else 0\\n elif opcode == EQ:\\n self.commands[locs[2]] = 1 if vals[0] == vals[1] else 0\\n else:\\n print(\\\"FAIL????\\\")\\n\\n return True\",\n \"def test_run_molecule(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def _loop_raw(raw):\\n raise NotImplemented\",\n \"def test_run_loop_exc(self):\\n with self.assertRaises(ExecutionException):\\n pyint = Interpreter(limit=1)\\n pyint.run(code=BF_CODE_LOOP_TWICE)\",\n \"def check_pipe_setup(pipe=None, sequence=False, j=False):\\n\\n # The data pipe.\\n if pipe == None:\\n pipe = pipes.cdp_name()\\n\\n # Get the data pipe.\\n dp = pipes.get_pipe(pipe)\\n\\n # Test if the current data pipe exists.\\n check_pipe(pipe)\\n\\n # Test if sequence data exists.\\n if sequence and not exists_mol_res_spin_data(pipe):\\n raise RelaxNoSequenceError(pipe)\\n\\n # Test if J coupling data exists.\\n if j:\\n # Search for interatomic data.\\n data = False\\n for interatom in interatomic_loop():\\n if hasattr(interatom, 'j_coupling'):\\n data = True\\n break\\n\\n # No data.\\n if not data:\\n raise RelaxNoJError()\",\n \"def test_start_analysis_pipeline_not_multiplexed(self, mock_popen, mock_is_multiplexed, mock_get_fc_code):\\n mock_get_fc_code.return_value = 'FLO-FLG001'\\n mock_is_multiplexed.return_value = False\\n run_dir = 'data/nanopore_data/run4/done_demuxing/20200104_1412_MN19414_AAU644_68125dc2'\\n sample_sheet = 'data/nanopore_data/run4/done_demuxing/20200104_1412_MN19414_AAU644_68125dc2/SQK-LSK109_sample_sheet.csv'\\n run = MinIONqc(run_dir, sample_sheet, None)\\n run.start_nanoseq()\\n expected_parameters = ('nextflow run nf-core/nanoseq'\\n + ' -r ' + CONFIG.get('nanopore_analysis').get('minion_qc_run').get('nanoseq_version')\\n + ' --input ' + sample_sheet\\n + ' --protocol DNA'\\n + ' --input_path ' + os.path.join(run_dir, 'fast5')\\n + ' --outdir ' + os.path.join(run_dir, 'nanoseq_output')\\n + ' --flowcell FLO-FLG001'\\n + ' --guppy_gpu'\\n + ' --skip_alignment'\\n + ' --skip_quantification'\\n + ' --kit SQK-LSK109'\\n + ' --max_cpus 6'\\n + ' --max_memory 20.GB'\\n + ' -profile singularity; echo $? > .exitcode_for_nanoseq')\\n mock_popen.assert_called_once_with(expected_parameters, stdout=subprocess.PIPE, shell=True, cwd=run_dir)\",\n \"def test_stream_loop(self):\\n chans, gains, scans, rate = (10,10,10,10), (1,2,4,5), 1024, 500\\n v = [v[0] for v in self.l.stream_sync(\\n channels=chans, gains=gains,\\n num_scans=scans, rate=rate)]\\n for vi in v:\\n for r in vi:\\n self.assertTrue(abs(r-2.5) < .1,\\n \\\"%s should be cal, 2.5v\\\" % vi[0])\",\n \"def test_test(self):\\n\\n # The following should do nothing as the pipes exist.\\n pipes.check_pipe()\\n pipes.check_pipe('orig')\\n pipes.check_pipe('empty')\\n\\n # Assert that a RelaxNoPipeError occurs when the pipe doesn't exist.\\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe, 'x')\\n\\n # Reset relax.\\n reset()\\n\\n # Now none of the following pipes exist, hence errors should be thrown.\\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe)\\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe, 'orig')\\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe, 'empty')\",\n \"def test_count_no_spins(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Test the number of spins counted.\\n self.assertEqual(mol_res_spin.count_spins(), 0)\",\n \"def setUp(self):\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Name the first molecule.\\n cdp.mol[0].name = 'Ap4Aase'\\n\\n # Add a second molecule to the system.\\n cdp.mol.add_item(mol_name='RNA')\\n\\n # Add two more residues to the first molecule (and set the residue number of the first).\\n cdp.mol[0].res[0].num = 1\\n cdp.mol[0].res.add_item(res_num=2, res_name='Glu')\\n cdp.mol[0].res.add_item(res_num=4, res_name='Pro')\\n\\n # Add some spin info to this molecule.\\n cdp.mol[0].res[0].spin[0].name = 'NH'\\n cdp.mol[0].res[0].spin[0].num = 60\\n cdp.mol[0].res[1].spin[0].name = 'NH'\\n cdp.mol[0].res[1].spin[0].num = 63\\n\\n # Add one more residue to the second molecule (and set the residue number of the first).\\n cdp.mol[1].res[0].num = -5\\n cdp.mol[1].res.add_item(res_num=-4)\\n\\n # Add a second set of spins to the second molecule (naming the first set first).\\n cdp.mol[1].res[0].spin[0].name = 'C8'\\n cdp.mol[1].res[1].spin[0].name = 'C8'\\n cdp.mol[1].res[0].spin.add_item(spin_name='N5')\\n cdp.mol[1].res[1].spin.add_item(spin_name='N5')\\n cdp.mol[1].res[1].spin.add_item(spin_name='2H', spin_num=132)\\n\\n # Deselect a number of spins.\\n cdp.mol[0].res[0].spin[0].select = 0\\n cdp.mol[0].res[2].spin[0].select = 0\\n cdp.mol[1].res[0].spin[0].select = 0\\n cdp.mol[1].res[1].spin[1].select = 0\\n\\n # Update the metadata.\\n mol_res_spin.metadata_update()\",\n \"def test_invoke_pipe_not_found():\\n\\n testapp = holocron.Application()\\n\\n with pytest.raises(ValueError) as excinfo:\\n next(testapp.invoke(\\\"test\\\"))\\n\\n assert str(excinfo.value) == \\\"no such pipe: 'test'\\\"\",\n \"def _handle_loop(self):\\n pass\",\n \"def infinite_loop():\\n return True\",\n \"def test_noFailure(self):\\n for i in range(10):\\n self.assertTrue(self.circuit_breaker.available())\",\n \"def run_no_input(self, initial=None, context=None):\\n for _ in self.run(initial, context):\\n raise RuntimeError(\\\"Machine requires input to continue!\\\")\",\n \"def handle_stop(_):\\n loop.force_unmute()\",\n \"def test_readiness(self):\\n self.command.package = self.input_ovf\\n ready, reason = self.command.ready_to_run()\\n self.assertFalse(ready)\\n self.assertRegex(reason, \\\"No file information\\\")\\n self.assertRaises(InvalidInputError, self.command.run)\\n\\n self.command.file_path = \\\"input.vmdk\\\"\\n ready, reason = self.command.ready_to_run()\\n self.assertTrue(ready)\\n\\n self.command.file_path = None\\n self.command.file_id = \\\"file1\\\"\\n ready, reason = self.command.ready_to_run()\\n self.assertTrue(ready)\",\n \"def test_halts_if_halt_on_next(self, get_pipe_manager, raise_error):\\n pm = get_pipe_manager(name=\\\"TestPM\\\")\\n pm.halt_on_next = True\\n if raise_error:\\n with pytest.raises(PipelineHalt):\\n pm.timestamp(\\\"testing\\\")\\n else:\\n pm.timestamp(\\\"testing\\\", raise_error=False)\\n assert pm.halted\",\n \"def do_simulation_loop(self) -> tuple[bool, bool]:\\n running, reset = True, False\\n for event in pygame.event.get():\\n if check_for_quit(event):\\n running = False\\n elif check_for_reset(event):\\n running = False\\n reset = True\\n self.simulation.do_step()\\n self.update_visualization()\\n self.simple_pygame.loop()\\n return running, reset\",\n \"def nanny(self): \\n while not self.started and not self.failed:\\n eventlet.sleep(.1)\\n return not self.failed\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"async def get_peak_loop(self):\\n while True:\\n try:\\n self.blockchain_state = await self.node_rpc_client.get_blockchain_state()\\n self.wallet_synced = await self.wallet_rpc_client.get_synced()\\n await asyncio.sleep(30)\\n except asyncio.CancelledError:\\n self.log.info(\\\"Cancelled get_peak_loop, closing\\\")\\n return\\n except Exception as e:\\n self.log.error(f\\\"Unexpected error in get_peak_loop: {e}\\\")\\n await asyncio.sleep(30)\",\n \"async def get_peak_loop(self):\\n while True:\\n try:\\n self.blockchain_state = await self.node_rpc_client.get_blockchain_state()\\n self.wallet_synced = await self.wallet_rpc_client.get_synced()\\n await asyncio.sleep(30)\\n except asyncio.CancelledError:\\n self.log.info(\\\"Cancelled get_peak_loop, closing\\\")\\n return\\n except Exception as e:\\n self.log.error(f\\\"Unexpected error in get_peak_loop: {e}\\\")\\n await asyncio.sleep(30)\",\n \"def test_close():\\n while True:\\n yield\",\n \"def wait_for_data(receiver):\\n\\n while not receiver.available(pipes[1]):\\n time.sleep(0.01)\",\n \"def run(self):\\n while self.container.process(): pass\",\n \"def test_runsUntilSyncCallback(self):\\n def main(reactor):\\n return defer.succeed(None)\\n r = _FakeReactor()\\n exitError = self.assertRaises(\\n SystemExit, task.react, main, _reactor=r)\\n self.assertEqual(0, exitError.code)\\n self.assertEqual(r.seconds(), 0)\",\n \"def test_sync_task_no_server(comm):\\n run_server, server_args, run_client, client_args = helper_config(comm, \\\"sync\\\")\\n client = run_client(**client_args)\\n try:\\n client.connect()\\n except Exception as exc: # pylint: disable=broad-except\\n assert False, f\\\"unexpected exception: {exc}\\\"\\n sleep(0.1)\\n if comm == \\\"udp\\\":\\n rr = client.read_coils(1, 1, slave=0x01)\\n assert isinstance(rr, ModbusIOException)\\n else:\\n with pytest.raises((asyncio.exceptions.TimeoutError, ConnectionException)):\\n client.read_coils(1, 1, slave=0x01)\\n client.close()\",\n \"def _run(self):\\n global _iom_instance\\n self.__logger.info(\\\"IOManager started\\\")\\n timeout = 0\\n while self.__running:\\n # Poll for events\\n if self.__et:\\n self.__poll_et()\\n else:\\n self.__poll_lt()\\n\\n # Perform IOWrapper checking on the actual\\n # frequency of the ticker, not each time\\n # there is data to read or write\\n if time.time() >= self.__next_tick:\\n self.__next_tick += self.__ticker.get_ticktime()\\n # Call the handle loop function of each connected wrapper\\n self.__handle_loop()\\n # Attempt to connect all IOWrappers\\n self.__attempt_wrappers()\\n # Check if IOManager should keep running\\n self.__check_stop()\\n # Allow for control to be interrupted if other threads require\\n # attention. Do not waste time on this so use a very short sleep\\n time.sleep(0.0001)\\n\\n self.__cleanup()\\n clear_IOM()\\n self.__logger.debug(\\\"Savings of wakeup pipe: %f seconds\\\" % self.__saved_time)\\n self.__logger.info(\\\"IOManager stopped\\\")\",\n \"def algorithm_loop(self):\",\n \"def test_start_analysis_pipeline_multiplexed(self, mock_popen, mock_is_multiplexed, mock_get_fc_code):\\n mock_get_fc_code.return_value = 'FLO-FLG001'\\n mock_is_multiplexed.return_value = True\\n run_dir = 'data/nanopore_data/run4/done_demuxing/20200104_1412_MN19414_AAU644_68125dc2'\\n sample_sheet = 'data/nanopore_data/run4/done_demuxing/20200104_1412_MN19414_AAU644_68125dc2/SQK-LSK109_sample_sheet.csv'\\n run = MinIONqc(run_dir, sample_sheet, None)\\n run.start_nanoseq()\\n expected_parameters = ('nextflow run nf-core/nanoseq'\\n + ' -r ' + CONFIG.get('nanopore_analysis').get('minion_qc_run').get('nanoseq_version')\\n + ' --input ' + sample_sheet\\n + ' --protocol DNA'\\n + ' --input_path ' + os.path.join(run_dir, 'fast5')\\n + ' --outdir ' + os.path.join(run_dir, 'nanoseq_output')\\n + ' --flowcell FLO-FLG001'\\n + ' --guppy_gpu'\\n + ' --skip_alignment'\\n + ' --skip_quantification'\\n + ' --kit SQK-LSK109'\\n + ' --max_cpus 6'\\n + ' --max_memory 20.GB'\\n + ' --barcode_kit EXP-NBD104'\\n + ' -profile singularity; echo $? > .exitcode_for_nanoseq')\\n mock_popen.assert_called_once_with(expected_parameters, stdout=subprocess.PIPE, shell=True, cwd=run_dir)\",\n \"def pauseLoop(self):\\n print('SYNC stim detected LOW')\\n self.loopRunning = False\",\n \"def test_modul1(self):\\n\\n self.delayDisplay(\\\"Starting the test\\\")\\n #\\n # first, get some data\\n #\\n import urllib\\n downloads = (\\n ('http://slicer.kitware.com/midas3/download?items=5767', 'FA.nrrd', slicer.util.loadVolume),\\n )\\n\\n for url,name,loader in downloads:\\n filePath = slicer.app.temporaryPath + '/' + name\\n if not os.path.exists(filePath) or os.stat(filePath).st_size == 0:\\n logging.info('Requesting download %s from %s...\\\\n' % (name, url))\\n urllib.urlretrieve(url, filePath)\\n if loader:\\n logging.info('Loading %s...' % (name,))\\n loader(filePath)\\n self.delayDisplay('Finished with download and loading')\\n\\n volumeNode = slicer.util.getNode(pattern=\\\"FA\\\")\\n logic = modulLogic()\\n self.assertTrue( logic.hasImageData(volumeNode) )\\n self.delayDisplay('Test passed!')\",\n \"def test_pump_bypass_on_reverse_flow(use_numba):\\n net = pandapipes.create_empty_network(\\\"net\\\", add_stdtypes=True)\\n\\n j1 = pandapipes.create_junction(net, pn_bar=5, tfluid_k=283.15)\\n j2 = pandapipes.create_junction(net, pn_bar=5, tfluid_k=283.15)\\n j3 = pandapipes.create_junction(net, pn_bar=5, tfluid_k=283.15)\\n j4 = pandapipes.create_junction(net, pn_bar=5, tfluid_k=283.15)\\n\\n pandapipes.create_pipe(net, j1, j2, std_type='125_PE_80_SDR_11', k_mm=1., length_km=10)\\n pandapipes.create_pipe(net, j3, j4, std_type='125_PE_80_SDR_11', k_mm=1., length_km=12)\\n pandapipes.create_ext_grid(net, j1, 5, 283.15, type=\\\"p\\\")\\n pandapipes.create_pump(net, j2, j3, std_type='P1')\\n pandapipes.create_source(net, j4, 0.02333)\\n\\n pandapipes.create_fluid_from_lib(net, \\\"hgas\\\", overwrite=True)\\n\\n pandapipes.pipeflow(net, stop_condition=\\\"tol\\\", iter=3, friction_model=\\\"nikuradse\\\",\\n mode=\\\"hydraulics\\\", transient=False, nonlinear_method=\\\"automatic\\\",\\n tol_p=1e-4, tol_v=1e-4, use_numba=use_numba)\\n\\n assert net.res_pump.deltap_bar.isin([0]).all()\\n assert np.isclose(net.res_junction.loc[1, \\\"p_bar\\\"], net.res_junction.loc[2, \\\"p_bar\\\"])\",\n \"def test_block_missing_batch(self):\\n pass\",\n \"def test_chunk_QuantumVolume(self, method, device):\\n opts = {\\\"blocking_enable\\\": True, \\\"blocking_qubits\\\": 2}\\n\\n backend = self.backend(method=method, device=device, **opts)\\n backend_no_chunk = self.backend(method=method, device=device)\\n\\n shots = 100\\n num_qubits = 4\\n depth = 10\\n circuit = transpile(\\n QuantumVolume(num_qubits, depth, seed=0), backend=backend, optimization_level=0\\n )\\n circuit.measure_all()\\n\\n result = backend.run(circuit, shots=shots, memory=True).result()\\n counts = result.get_counts(circuit)\\n result_no_chunk = backend_no_chunk.run(circuit, shots=shots, memory=True).result()\\n counts_no_chunk = result_no_chunk.get_counts(circuit)\\n\\n self.assertEqual(counts_no_chunk, counts)\",\n \"def test_analog_in_out_loop(self):\\n for v in range(0, 6, 1):\\n self.l.output(ao0=v, ao1=v)\\n r = self.l.input(channels=(8,8,9,9), gains=(1,4,1,4))[0]\\n for i in r:\\n self.assertTrue(abs(v-i) < .1,\\n \\\"measured %g for %g\\\" % (i, v))\",\n \"def has_loop(self) -> bool:\\n try:\\n list(self)\\n return False\\n except ContainsLoopError:\\n return True\",\n \"def checkDone(self):\\n # checks if the instructions in the pipeline are nop are not\\n # if all nop then we are done\\n self.__done = True\\n for pi in self.pipeline:\\n if pi.instr is not None:\\n self.__done = False\",\n \"def loop_run(self):\\n super(HasLoops, self).loop_run()\\n for loop in getattr(self, \\\"_loops\\\", []):\\n loop.loop_remove_from_parent = weak_method(self.remove_loop)\\n loop.loop_run()\",\n \"def test_notRunning_pump_noValve(self):\\n\\t\\tdef mock_def(uri, *args):\\n\\t\\t\\tif(uri == u\\\"ch.db.getdevicedata\\\"):\\n\\t\\t\\t\\treturn {'name':'testPump', 'type':'pump', 'group':-1, 'id':1, 'description': ''}\\n\\t\\t\\telif(uri == u\\\"ch.gpio.isrunning\\\"):\\n\\t\\t\\t\\treturn False\\n\\t\\t\\telif(uri == u\\\"ch.db.getdevicegroup\\\"):\\n\\t\\t\\t\\treturn([])\\n\\t\\t\\telse:\\n\\t\\t\\t\\traise ValueError(\\\"Given URI does not exist ({})\\\".format(uri))\\n\\n\\t\\tdm = DeviceManager()\\n\\t\\tdm.sessionID = None\\n\\t\\tdm.call=MagicMock(side_effect=mock_def)\\n\\t\\tdm.publish=MagicMock()\\n\\t\\tself.failureResultOf(dm.switchIfAllowed('testPump', None), ApplicationError)\",\n \"def test_for_loop(self, modes, parse_input_mocked_metadata):\\n bb = parse_input_mocked_metadata(\\n \\\"for int m in {}\\\\n\\\\tMeasureFock() | m\\\".format(modes)\\n )\\n assert np.all(\\n bb._forvar[\\\"m\\\"] == np.array(modes)\\n )\\n assert bb.operations == [\\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[0]]},\\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[1]]},\\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[2]]}\\n ]\",\n \"async def main(dut):\\n # Create a 10us period clock on port clk\\n clock = Clock(dut.clk_i, 10, units=\\\"us\\\")\\n cocotb.fork(clock.start())\\n\\n # Reset system\\n await FallingEdge(dut.clk_i)\\n dut.rst_n_i <= 0\\n dut.en_i <= 0\\n dut.data_i <= 0\\n dut.valid_i <= 0\\n\\n # reset\\n await FallingEdge(dut.clk_i)\\n dut.rst_n_i <= 1\\n\\n # test 1\\n dut.en_i <= 1\\n x, y = get_test_vector()\\n cocotb.fork(write_input(dut, x))\\n await check_output(dut, y)\\n\\n # test 2\\n dut.en_i <= 0\\n await check_output_no_en(dut)\\n\\n # test 3\\n dut.en_i <= 1\\n x, y = get_test_vector()\\n cocotb.fork(write_input(dut, x))\\n await check_output(dut, y)\",\n \"def startLoop():\\n patchAsyncio()\",\n \"def timeout_loop(self):\\r\\n\\r\\n while not done:\\r\\n\\r\\n if (softwareInterfaceTimeout != -1) and (interfaceNotUsed > softwareInterfaceTimeout):\\r\\n\\r\\n stop(False)\\r\\n\\r\\n \\r\\n\\r\\n time.sleep(MONITOR_INTERVAL/1000000.0)\\r\\n\\r\\n self.interfaceNotUsed = self.interfaceNotUsed + 1\",\n \"def testReset(self):\\n \\n clk = Signal(0)\\n rst = Signal(1)\\n clock_gen = ClkDriver(clk, period=4)\\n \\n out = Signal(intbv(0)[4:])\\n counter = Counter(out, clk, rst)\\n \\n def test():\\n for i in range(200):\\n # count up to 9 then reset\\n if int(out) == 9:\\n rst.next = 0\\n yield delay(1)\\n self.assertEqual(int(out), 0)\\n # turn off reset next time\\n else:\\n rst.next = 1\\n yield delay(1)\\n \\n check = test()\\n sim = Simulation(counter, clock_gen, check)\\n sim.run(400, quiet=1)\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_halts_if_hitting_exclusive_halt_point(self, get_pipe_manager, raise_error):\\n\\n # Create manager, set halt point, and check that it's running.\\n halt_name = \\\"phase3\\\"\\n pm = get_pipe_manager(name=\\\"TestPM\\\")\\n pm.stop_before = halt_name\\n\\n # Make non-halting checkpointed timestamp calls.\\n pm.timestamp(checkpoint=\\\"phase1\\\")\\n assert not pm.halted\\n pm.timestamp(checkpoint=\\\"phase2\\\")\\n assert not pm.halted\\n\\n # Make the halt-inducing checkpointed timestamp call.\\n if raise_error:\\n with pytest.raises(PipelineHalt):\\n pm.timestamp(checkpoint=halt_name, raise_error=True)\\n else:\\n pm.timestamp(checkpoint=halt_name, raise_error=False)\\n # Verify that we've halted.\\n try:\\n assert pm.halted\\n except AssertionError:\\n print(\\\"STATUS: {}\\\".format(pm.status))\\n raise\",\n \"def run(self):\\n\\n if self.success and not self.running:\\n self.log.info(\\\"Humidity and temp control started...\\\")\\n self.running = True\\n elif self.testmode and not self.running:\\n self.log.critical(\\\"Humidity and temp TEST MODE started!!!\\\")\\n self.running = True\\n elif not self.running:\\n self.log.info(\\\"Humidity and temp control NOT started...\\\")\\n return\\n\\n if not self.stop_measurement_loop and self.success:\\n try:\\n # Query the environemnt etc from Brandbox\\n envvalues = self.vcw.query(\\n self.resource, self.resource[\\\"get_environment\\\"]\\n )\\n envvalues = envvalues.split(\\\",\\\")\\n\\n # Get dewpoint\\n boxvalues = self.vcw.query(\\n self.resource, self.resource[\\\"get_box_environment\\\"]\\n )\\n boxvalues = boxvalues.split(\\\",\\\")\\n\\n vacuumvalues = self.vcw.query(\\n self.resource, self.resource[\\\"get_vacuum\\\"]\\n )\\n\\n # get light\\n luxvalues = self.vcw.query(self.resource, self.resource[\\\"get_lux\\\"])\\n luxvalues = luxvalues.split(\\\",\\\")[0]\\n\\n # if an error happen, as so often with the brandbox read the queue\\n if self.readqueue:\\n try:\\n ans = self.vcw.read(self.resource)\\n if ans:\\n self.log.critical(\\\"Brandbox had an non empty queue: {}\\\".format(ans))\\n except:\\n self.log.info(\\\"Brandbox indicated an non empty queue, reading queue yielded no queue...\\\", exc_info=True)\\n\\n\\n try:\\n if float(luxvalues) >= 0.5:\\n self.framework[\\\"Configs\\\"][\\\"config\\\"][\\\"settings\\\"][\\\"lights\\\"] = True\\n else:\\n self.framework[\\\"Configs\\\"][\\\"config\\\"][\\\"settings\\\"][\\\"lights\\\"] = False\\n\\n # get door\\n # doorvalues = self.vcw.query(self.resource, self.resource[\\\"get_door\\\"])\\n # doorvalues = doorvalues.split(\\\",\\\")[0]\\n # if doorvalues == \\\"1\\\":\\n # self.framework[\\\"Configs\\\"][\\\"config\\\"][\\\"settings\\\"][\\\"door\\\"] = False\\n # else:\\n # self.framework[\\\"Configs\\\"][\\\"config\\\"][\\\"settings\\\"][\\\"door\\\"] = True\\n\\n # get light\\n vacuumvalues = vacuumvalues.split(\\\",\\\")[0]\\n if vacuumvalues == \\\"1\\\":\\n self.framework[\\\"Configs\\\"][\\\"config\\\"][\\\"settings\\\"][\\\"vacuum\\\"] = True\\n else:\\n self.framework[\\\"Configs\\\"][\\\"config\\\"][\\\"settings\\\"][\\\"vacuum\\\"] = False\\n\\n # Here a list\\n self.main.humidity_history = np.append(\\n self.main.humidity_history, float(envvalues[1])\\n ) # todo: memory leak since no values will be deleted\\n self.main.temperatur_history = np.append(\\n self.main.humidity_history, float(envvalues[3])\\n )\\n\\n # Write the pt100 and light status and environement in the box to the global variables\\n self.framework[\\\"Configs\\\"][\\\"config\\\"][\\\"settings\\\"][\\n \\\"chuck_temperature\\\"\\n ] = float(envvalues[3])\\n self.framework[\\\"Configs\\\"][\\\"config\\\"][\\\"settings\\\"][\\n \\\"air_temperature\\\"\\n ] = float(envvalues[0])\\n self.framework[\\\"Configs\\\"][\\\"config\\\"][\\\"settings\\\"][\\\"dew_point\\\"] = float(\\n boxvalues[3]\\n )\\n\\n # Send data to main\\n self.queue_to_main.put(\\n {\\n \\\"temperature_air\\\": [float(time()), float(envvalues[0])],\\n \\\"temperature_chuck\\\": [float(time()), float(envvalues[3])],\\n \\\"dew_point\\\": [float(time()), float(boxvalues[3])],\\n \\\"humidity\\\": [float(time()), float(envvalues[1])],\\n }\\n )\\n except:\\n self.readqueue = True\\n\\n except Exception as err:\\n self.log.error(\\n \\\"The temperature and humidity controller seems not to be responding. Error: {!s}\\\".format(\\n err\\n ),\\n exc_info=True,\\n )\\n\\n elif self.testmode:\\n self.log.critical(\\\"Testmode sends message to main!\\\")\\n self.queue_to_main.put(\\n {\\n \\\"temperature\\\": [float(time()), float(random.randint(1, 10))],\\n \\\"humidity\\\": [float(time()), float(random.randint(1, 10))],\\n }\\n )\\n\\n if not self.main.stop_measurement_loop:\\n self.start_timer(self.run)\\n else:\\n self.log.info(\\n \\\"Shutting down environment control due to stop of measurement loop\\\"\\n )\",\n \"def _readloop(self):\\r\\n\\r\\n while self._ll_alive:\\r\\n with self._rx_lock:\\r\\n data = self._Random(1)\\r\\n if len(data) != 0: # check for timeout\\r\\n self._uart_rx_queue.put(data)\",\n \"def test_shutdown_restart(self):\\n log.info(\\\"CONFIG: %s\\\", self._agent_config())\\n self.create_sample_data_set_dir('node59p1_step2.dat', TELEM_DIR, \\\"node59p1.dat\\\")\\n\\n self.assert_initialize(final_state=ResourceAgentState.COMMAND)\\n\\n # Slow down processing to 1 per second to give us time to stop\\n self.dataset_agent_client.set_resource({DriverParameter.RECORDS_PER_SECOND: 1})\\n self.assert_start_sampling()\\n\\n # Verify we get one sample\\n try:\\n # Read the first file and verify the data\\n result = self.data_subscribers.get_samples(DataParticleType.CONTROL, 1)\\n result1 = self.data_subscribers.get_samples(DataParticleType.SAMPLE, 3)\\n result.extend(result1)\\n log.debug(\\\"RESULT: %s\\\", result)\\n\\n # Verify values\\n self.assert_data_values(result, 'test_data_1-2.txt.result.yml')\\n self.assert_sample_queue_size(DataParticleType.CONTROL, 0)\\n self.assert_sample_queue_size(DataParticleType.SAMPLE, 0)\\n\\n self.create_sample_data_set_dir('node59p1_step4.dat', TELEM_DIR, \\\"node59p1.dat\\\")\\n # Now read the first record of the second file then stop\\n result = self.data_subscribers.get_samples(DataParticleType.SAMPLE, 3)\\n log.debug(\\\"RESULT 1: %s\\\", result)\\n self.assert_stop_sampling()\\n self.assert_sample_queue_size(DataParticleType.CONTROL, 0)\\n self.assert_sample_queue_size(DataParticleType.SAMPLE, 0)\\n\\n # stop and re-start the agent\\n self.stop_dataset_agent_client()\\n self.init_dataset_agent_client()\\n # re-initialize\\n self.assert_initialize()\\n\\n result2 = self.data_subscribers.get_samples(DataParticleType.SAMPLE, 3)\\n log.debug(\\\"RESULT 2: %s\\\", result2)\\n result.extend(result2)\\n log.debug(\\\"RESULT: %s\\\", result)\\n self.assert_data_values(result, 'test_data_3-4.txt.result.yml')\\n self.assert_sample_queue_size(DataParticleType.CONTROL, 0)\\n self.assert_sample_queue_size(DataParticleType.SAMPLE, 0)\\n except SampleTimeout as e:\\n log.error(\\\"Exception trapped: %s\\\", e, exc_info=True)\\n self.fail(\\\"Sample timeout.\\\")\",\n \"def test_init_done():\\n with pytest.raises(MLOpsException):\\n pm.set_stat(\\\"st1\\\", 5.5)\\n\\n with pytest.raises(MLOpsException):\\n pm.done()\\n\\n pm.init(ctx=None, mlops_mode=MLOpsMode.STAND_ALONE)\\n pm.done()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.85301226","0.79059464","0.7656533","0.73368526","0.7248419","0.70627767","0.69679505","0.6318001","0.63044786","0.6154404","0.61035573","0.5977854","0.5860056","0.5848514","0.5847035","0.5795445","0.56938887","0.55405074","0.5520122","0.5514679","0.5450438","0.54080737","0.538907","0.53474224","0.5340997","0.53271973","0.53244764","0.53181565","0.5231122","0.522612","0.52186763","0.52086425","0.5195952","0.51888484","0.5179227","0.51692593","0.5167664","0.5161395","0.5151157","0.5134897","0.5133081","0.51249355","0.5117732","0.5114734","0.51042753","0.5082435","0.50802046","0.50752646","0.5067741","0.5067564","0.50594","0.50586665","0.50570416","0.5053759","0.5049699","0.50308913","0.50131327","0.5004361","0.49518797","0.4944131","0.49428377","0.4934639","0.49343818","0.49323067","0.49264574","0.49242207","0.4907968","0.4894182","0.4891643","0.4891426","0.4891426","0.4881961","0.48764354","0.48720303","0.48658538","0.48651075","0.48636228","0.48602316","0.48570204","0.4856761","0.48532748","0.48487923","0.48376134","0.48202538","0.48146993","0.48129192","0.4812787","0.48120558","0.4810253","0.48097548","0.4805082","0.480026","0.47979203","0.47884578","0.4786451","0.47852114","0.47819835","0.4779802","0.47729158","0.47724476"],"string":"[\n \"0.85301226\",\n \"0.79059464\",\n \"0.7656533\",\n \"0.73368526\",\n \"0.7248419\",\n \"0.70627767\",\n \"0.69679505\",\n \"0.6318001\",\n \"0.63044786\",\n \"0.6154404\",\n \"0.61035573\",\n \"0.5977854\",\n \"0.5860056\",\n \"0.5848514\",\n \"0.5847035\",\n \"0.5795445\",\n \"0.56938887\",\n \"0.55405074\",\n \"0.5520122\",\n \"0.5514679\",\n \"0.5450438\",\n \"0.54080737\",\n \"0.538907\",\n \"0.53474224\",\n \"0.5340997\",\n \"0.53271973\",\n \"0.53244764\",\n \"0.53181565\",\n \"0.5231122\",\n \"0.522612\",\n \"0.52186763\",\n \"0.52086425\",\n \"0.5195952\",\n \"0.51888484\",\n \"0.5179227\",\n \"0.51692593\",\n \"0.5167664\",\n \"0.5161395\",\n \"0.5151157\",\n \"0.5134897\",\n \"0.5133081\",\n \"0.51249355\",\n \"0.5117732\",\n \"0.5114734\",\n \"0.51042753\",\n \"0.5082435\",\n \"0.50802046\",\n \"0.50752646\",\n \"0.5067741\",\n \"0.5067564\",\n \"0.50594\",\n \"0.50586665\",\n \"0.50570416\",\n \"0.5053759\",\n \"0.5049699\",\n \"0.50308913\",\n \"0.50131327\",\n \"0.5004361\",\n \"0.49518797\",\n \"0.4944131\",\n \"0.49428377\",\n \"0.4934639\",\n \"0.49343818\",\n \"0.49323067\",\n \"0.49264574\",\n \"0.49242207\",\n \"0.4907968\",\n \"0.4894182\",\n \"0.4891643\",\n \"0.4891426\",\n \"0.4891426\",\n \"0.4881961\",\n \"0.48764354\",\n \"0.48720303\",\n \"0.48658538\",\n \"0.48651075\",\n \"0.48636228\",\n \"0.48602316\",\n \"0.48570204\",\n \"0.4856761\",\n \"0.48532748\",\n \"0.48487923\",\n \"0.48376134\",\n \"0.48202538\",\n \"0.48146993\",\n \"0.48129192\",\n \"0.4812787\",\n \"0.48120558\",\n \"0.4810253\",\n \"0.48097548\",\n \"0.4805082\",\n \"0.480026\",\n \"0.47979203\",\n \"0.47884578\",\n \"0.4786451\",\n \"0.47852114\",\n \"0.47819835\",\n \"0.4779802\",\n \"0.47729158\",\n \"0.47724476\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.84358346"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":81492,"cells":{"query":{"kind":"string","value":"Test the proper operation of the molecule loop when no selection is present. The function tested is pipe_control.mol_res_spin.molecule_loop()."},"document":{"kind":"string","value":"def test_molecule_loop_no_selection(self):\n\n # Molecule data.\n name = ['Ap4Aase', 'RNA']\n\n # Loop over the molecules.\n i = 0\n for mol in mol_res_spin.molecule_loop():\n # Test the molecule names.\n self.assertEqual(mol.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_spin_loop_no_selection(self):\n\n # Spin data.\n select = [0, 1, 0, 0, 1, 1, 0, 1]\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 8)","def test_molecule_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for molecule in mol_res_spin.molecule_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_molecule_loop(self):\n\n # Loop over the molecules.\n for mol in mol_res_spin.molecule_loop('#RNA'):\n # Test the molecule name.\n self.assertEqual(mol.name, 'RNA')\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)","def test_spin_loop(self):\n\n # Spin data.\n select = [1, 0]\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, 'N5')\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 2)","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_run_molecule_not_selected(self, single_mol_system):\n sequence = \"ABCDE\"\n processor = dssp.AnnotateResidues(\n \"test\", sequence, molecule_selector=lambda mol: False\n )\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert vermouth.utils.are_all_equal(found)\n assert found[0] is None","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_spin_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for spin in mol_res_spin.spin_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_spin_loop_multiatom(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_residue_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for residue in mol_res_spin.residue_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_spin_loop_wildcard(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N*'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_residue_loop(self):\n\n # Loop over the residues.\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\n # Test the selection.\n self.assertEqual(res.num, 2)\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)","def test_run_loop_success(self):\n found = False\n pyint = Interpreter(limit=15)\n try:\n pyint.run(code=BF_CODE_LOOP_TWICE)\n except SystemExit: \n found = True\n self.assertFalse(found)","def test_multi_molecules_cycle_one(self, multi_mol_system_irregular):\n sequence = \"A\"\n expected = [sequence] * (15 * 3)\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_irregular)\n found = self.sequence_from_system(multi_mol_system_irregular, \"test\")\n assert found == expected","def test_multi_molecules_cycle(self, multi_mol_system_regular, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n expected = expected * 3\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_regular)\n found = self.sequence_from_system(multi_mol_system_regular, \"test\")\n assert found == expected","def test_return_molecule(self):\n\n # Ask for a few molecules.\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\n\n # Test the data of molecule 1.\n self.assertEqual(mol1.name, 'Ap4Aase')\n\n # Test the data of molecule 2.\n self.assertEqual(mol2.name, 'RNA')","def ROOMSELECTION_LOOP():\n pass","def test_single_molecules_cycle_one(self, single_mol_system):\n sequence = \"A\"\n expected = [sequence] * (5 * 3)\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def loop(self):\n raise NotImplementedError()","def test_run_molecule(self, single_mol_system):\n sequence = \"ABCDE\"\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def test_return_molecule_pipe_fail(self):\n\n # Try to get a molecule from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')","def test_boolean_and_selection(self):\n\n # The selection loop:\n sel = list(mol_res_spin.residue_loop(\"#Ap4Aase:4 & :Pro\"))\n\n # Test:\n self.assertEqual(len(sel), 1)\n for res in sel:\n self.assert_(res.name == \"Pro\" and res.num == 4)","def loop(self):\n pass","async def checkNewLoop(self):\n pass","def _run(self):\n while(self._loop):\n pass","def do_simulation_loop(self) -> tuple[bool, bool]:\n running, reset = True, False\n for event in pygame.event.get():\n if check_for_quit(event):\n running = False\n elif check_for_reset(event):\n running = False\n reset = True\n self.simulation.do_step()\n self.update_visualization()\n self.simple_pygame.loop()\n return running, reset","async def hold_loop(self, *args) -> bool:\n raise NotImplementedError","def testNoMatchingMasses(self):\n mc = nigel.MassSelection(nb, mlow = 10, mhigh = 10.101)\n self.assertIsNone(mc)","def PLAYERSELECTION_LOOP():\n pass","def test_run_loop_exc(self):\n with self.assertRaises(ExecutionException):\n pyint = Interpreter(limit=1)\n pyint.run(code=BF_CODE_LOOP_TWICE)","def MULTIPLAYER_LOOP():\n pass","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_control_loop_example():\n example.control.print_error_measurement()\n matplotlib.use('agg')\n example.control.visualise_error_measurement(fig_file='cs_compare.pdf')\n assert path.isfile('cs_compare.pdf')\n example.control.sil_comparison()","def algorithm_loop(self):","def test_empty_with_filter(multi_mol_system_irregular):\n sequence = \"not empty\"\n processor = dssp.AnnotateResidues(\n \"test\", sequence, molecule_selector=lambda mol: False\n )\n with pytest.raises(ValueError):\n processor.run_system(multi_mol_system_irregular)","def test_simulate(self):\n sut = gireactor.PortableGIReactor(useGtk=False)\n # Double check that reactor has no sleep period.\n self.assertIs(None, sut.timeout())\n\n sut.simulate()","def run_test(dut):\n tb = MyTB(dut,int(os.environ['SIM_LEN']))\n cocotb.fork(Clock(dut.clk, 10).start())\n stim_thread = cocotb.fork(tb.stim_mux())\n read_thread = cocotb.fork(tb.read_mux())\n yield stim_thread.join()\n yield read_thread.join()\n if tb.sim_mux_sel != tb.py_sel_input:\n raise TestFailure(\"Mux selection failed.\")\n else:\n raise TestSuccess(\"Mux sel successful\")","def test_boolean_complex_selection(self):\n\n # The residue selection loop.\n sel = list(mol_res_spin.residue_loop(\"#Ap4Aase:4 & :Pro | #RNA\"))\n\n # Residue names and numbers.\n names = ['Pro', None, None]\n numbers = [4, -5, -4]\n\n # The residues.\n self.assertEqual(len(sel), 3)\n for i in range(3):\n self.assertEqual(sel[i].name, names[i])\n self.assertEqual(sel[i].num, numbers[i])","def run_one_test_cycle(self):\n logging.info(\n \"{0} operations remaining: {1}\".format(\n self.args.pm_operation, self.args.repetitions\n )\n )\n\n self.check_last_cycle_duration()\n if self.args.repetitions > 0:\n self.run_pm_command()\n else:\n self.summary()","def test_no_immediate_stop(self):\n script = ControlScript()\n options = ControlOptions()\n options.parseOptions([b\"--data-path\", self.mktemp()])\n self.assertNoResult(script.main(MemoryCoreReactor(), options))","def run_no_input(self, initial=None, context=None):\n for _ in self.run(initial, context):\n raise RuntimeError(\"Machine requires input to continue!\")","def test_single_molecule(self, single_mol_system, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def loop(self, loop: bool=None):\n self._select_interface(self._rc_loop, self._http_loop, loop)","def test_circularloop(self):\n cmd = f\"{SRC_LISTER} -i {PWD}/main\"\n with subprocess.Popen(\n shlex.split(cmd), stdout=subprocess.PIPE, stderr=subprocess.PIPE\n ) as proc:\n try:\n out, err = proc.communicate(timeout=5)\n assert len(err.strip()) > 0, \"Expected a circular reference error\"\n except subprocess.TimeoutExpired as te:\n print(\"Unexpected parser timeout during infinite loop test\")","def runSingleTest(cube, instructions, interval):\n root = Tk()\n interface = Interface(root, cube)\n root.after(0, interface.runInstructions, instructions, interval)\n root.mainloop()","def test_reset(self):\n ran = []\n def foo():\n ran.append(None)\n\n c = task.Clock()\n lc = TestableLoopingCall(c, foo)\n lc.start(2, now=False)\n c.advance(1)\n lc.reset()\n c.advance(1)\n self.assertEqual(ran, [])\n c.advance(1)\n self.assertEqual(ran, [None])","def watch_loop(self):\n # Double threaded function that allows to stop the loop mid execution\n def repeatIt():\n # reset UI and flag before starting loop\n self.resetLabels()\n self.reset_scrollbar()\n # enable stop button\n self.btnStop.config(state=\"normal\")\n # disable button while loop is running\n self.btnStart.config(state=\"disabled\")\n self.txtLoop.config(state=\"disabled\", textvariable=self.loopCounterUI)\n self.labelLoop.config(text=\"Loop Count: \")\n\n while self.loopCount.get() > 0:\n # move scrollbar to bottom\n self.testCanvas.yview_moveto(0)\n # count the loop\n self.loopCounterUI.set(self.loopCounterUI.get() + 1)\n\n # Run the test cases\n self.runThis()\n\n # Below are just to reset the UI\n if not self.stopLoop:\n print(\"loop not stopped so proceed\")\n # let user know script is stopping\n x = Label(\n self.testFrame, text=f'End of Loop',\n background=self.bgChooser(),\n foreground=\"#630984\",\n font=self.boldFont)\n x.pack(fill=X)\n # flag gor BG and labels\n self.bgCounter += 1\n self.LabelLists.append(x)\n # allow window to catch up\n self.tkRoot.update()\n self.update_scrollbar()\n else:\n print(\"loop has been stopped so not gonna print End of Loop\")\n\n # pause before restarting loop\n self.loopCount.set(self.loopCount.get()-1)\n time.sleep(1)\n\n # disable stop button\n self.btnStop.config(state=\"disabled\")\n # re-enable button after loop is done\n self.btnStart.config(state=\"normal\")\n self.txtLoop.config(state=\"normal\", textvariable=self.loopCount)\n self.labelLoop.config(text=\"Enter Loop Count: \")\n # self.testCanvas.yview_moveto(0)\n # Let user know the script is done\n if not self.stopLoop:\n # loop did not stopped\n x = Label(\n self.testFrame, text=f'Test is done!',\n background=self.bgChooser(),\n foreground=\"#057224\",\n font=self.boldFont)\n x.pack(fill=X)\n self.bgCounter += 1\n else:\n x = Label(\n self.testFrame, text=f'Test stopped!',\n background=self.bgChooser(),\n foreground=\"#057224\",\n font=self.boldFont)\n x.pack(fill=X)\n self.bgCounter += 1\n self.btnStart.config(state=\"normal\")\n self.txtLoop.config(state=\"normal\", textvariable=self.loopCount)\n self.labelLoop.config(text=\"Enter Loop count: \")\n self.loopCount.set(50000)\n self.LabelLists.append(x)\n # allow window to catch up\n self.tkRoot.update()\n self.update_scrollbar()\n thread = threading.Thread(target=repeatIt)\n thread.start()","def _run_cycle(self):\n pass","def infinite_loop():\n return True","def pauseLoop(self):\n print('SYNC stim detected LOW')\n self.loopRunning = False","def run(self):\n while True:\n try:\n self.check_value()\n except Exception as e:\n print(f\"[ERROR]: Error running the continuous run loop on sample_module: {e}\")\n continue","def test_select_pdb_conformation(self):\n with mmtools.utils.temporary_directory() as tmp_dir:\n yaml_content = \"\"\"\n ---\n options:\n output_dir: {}\n setup_dir: .\n molecules:\n selected:\n filepath: {}\n leap: {{parameters: oldff/leaprc.ff14SB}}\n select: 1\n \"\"\".format(tmp_dir, self.pdb_path)\n yaml_content = textwrap.dedent(yaml_content)\n exp_builder = ExperimentBuilder(yaml_content)\n\n # The molecule now is neither set up nor processed\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\n assert is_setup is False\n assert is_processed is False\n\n # The setup of the molecule must isolate the frame in a single-frame PDB\n exp_builder._db._setup_molecules('selected')\n selected_pdb_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\n 'selected', 'selected.pdb')\n assert os.path.exists(os.path.join(selected_pdb_path))\n assert os.path.getsize(os.path.join(selected_pdb_path)) > 0\n\n # The positions must be the ones of the second frame\n selected_pdb = PDBFile(selected_pdb_path)\n selected_pos = selected_pdb.getPositions(asNumpy=True)\n second_pos = PDBFile(self.pdb_path).getPositions(asNumpy=True, frame=1)\n assert selected_pdb.getNumFrames() == 1\n assert (selected_pos == second_pos).all()\n\n # The description of the molecule is now updated\n assert os.path.normpath(exp_builder._db.molecules['selected']['filepath']) == selected_pdb_path\n\n # The molecule now both set up and processed\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\n assert is_setup is True\n assert is_processed is True\n\n # A new instance of ExperimentBuilder is able to resume with correct molecule\n exp_builder = ExperimentBuilder(yaml_content)\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\n assert is_setup is True\n assert is_processed is True","def _handle_loop(self):\n pass","def test_simulationRun(self):\n self.opt = { 'temperature' : 300.0, 'friction' : 1, 'dt' : 0.00002,\n 'nIter' : 2, 'nstepsNC' : 2, 'nstepsMD' : 1, 'nprop' : 1,\n 'nonbondedMethod' : 'NoCutoff', 'constraints': 'HBonds',\n 'trajectory_interval' : 1, 'reporter_interval' : 1,\n 'outfname' : 'mc-test',\n 'platform' : None,\n 'constraints' : 'HBonds',\n 'mc_per_iter' : 2 }\n\n structure = self.full_struct\n class SetRotationMove(RandomLigandRotationMove):\n def __init__(self, structure, resname='LIG'):\n super(SetRotationMove, self).__init__(structure, resname)\n\n def move(self, context):\n \"\"\"Function that performs a random rotation about the\n center of mass of the ligand.\n \"\"\"\n #TODO: check if we need to deepcopy\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\n\n self.positions = positions[self.atom_indices]\n self.center_of_mass = self.getCenterOfMass(self.positions, self.masses)\n reduced_pos = self.positions - self.center_of_mass\n\n # Define random rotational move on the ligand\n #set rotation so that test is reproducible\n set_rotation_matrix = np.array([[-0.62297988, -0.17349253, 0.7627558 ],\n [ 0.55082352, -0.78964857, 0.27027502],\n [ 0.55541834, 0.58851973, 0.58749893]])\n\n\n #set_rotation_matrix = np.array([[1, 0, 0],\n # [0, 1, 0],\n # [0, 0, 1]])\n\n #multiply lig coordinates by rot matrix and add back COM translation from origin\n rot_move = np.dot(reduced_pos, set_rotation_matrix) * positions.unit + self.center_of_mass\n\n # Update ligand positions in nc_sim\n for index, atomidx in enumerate(self.atom_indices):\n positions[atomidx] = rot_move[index]\n context.setPositions(positions)\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\n self.positions = positions[self.atom_indices]\n return context\n\n\n self.model = SetRotationMove(structure, resname='ALA')\n #self.model = RandomLigandRotationMove(structure, resname='ALA')\n\n self.model.atom_indices = range(22)\n self.model.topology = structure[self.model.atom_indices].topology\n self.model.positions = structure[self.model.atom_indices].positions\n self.model.calculateProperties()\n\n self.mover = MoveEngine(self.model)\n #Initialize the SimulationFactory object\n sims = SimulationFactory(structure, self.mover, **self.opt)\n #print(sims)\n system = sims.generateSystem(structure, **self.opt)\n simdict = sims.createSimulationSet()\n alch_system = sims.generateAlchSystem(system, self.model.atom_indices)\n self.nc_sim = sims.generateSimFromStruct(structure, self.mover, alch_system, ncmc=True, **self.opt)\n self.model.calculateProperties()\n self.initial_positions = self.nc_sim.context.getState(getPositions=True).getPositions(asNumpy=True)\n mc_sim = Simulation(sims, self.mover, **self.opt)\n #monkeypatch to access acceptance value\n def nacceptRejectMC(self, temperature=300, **opt):\n \"\"\"Function that chooses to accept or reject the proposed move.\n \"\"\"\n md_state0 = self.current_state['md']['state0']\n md_state1 = self.current_state['md']['state1']\n log_mc = (md_state1['potential_energy'] - md_state0['potential_energy']) * (-1.0/self.nc_sim.context._integrator.kT)\n randnum = math.log(np.random.random())\n\n if log_mc > randnum:\n self.accept += 1\n print('MC MOVE ACCEPTED: log_mc {} > randnum {}'.format(log_mc, randnum) )\n self.md_sim.context.setPositions(md_state1['positions'])\n else:\n self.reject += 1\n print('MC MOVE REJECTED: log_mc {} < {}'.format(log_mc, randnum) )\n self.md_sim.context.setPositions(md_state0['positions'])\n self.log_mc = log_mc\n self.md_sim.context.setVelocitiesToTemperature(self.opt['temperature'])\n mc_sim.acceptRejectMC = nacceptRejectMC\n nacceptRejectMC.__get__(mc_sim)\n mc_sim.acceptRejectMC = types.MethodType(nacceptRejectMC, mc_sim)\n mc_sim.runMC(self.opt['nIter'])\n #get log acceptance\n print(mc_sim.log_mc)\n #if mc is working, should be around -24.1\n assert mc_sim.log_mc <= -23.8 and mc_sim.log_mc >= -24.3","def loop(self):\n while self.dispatch(True) is not QUIT:\n pass","def runMasking(self,roiNode,inputVolumes,inPlace):\n\n self.delayDisplay('Running the algorithm')\n\n for vol in inputVolumes:\n self.maskVolume(vol, roiNode, inPlace)\n\n return True\n\n self.delayDisplay('Running the aglorithm')","def run(self):\n while True:\n if self.job_q.empty():\n self.message_q.put(False)\n return\n try:\n smolecule = self.job_q.get()\n self.data_pointer[smolecule].get_adp(self.Temp)\n except IndexError:\n self.message_q.put((smolecule, None))\n try:\n self.message_q.put((smolecule, [j.adp['cart_int'] for j in self.data_pointer[smolecule].atoms]))\n except KeyError:\n # =======================================================\n # self.message_q.put((molecule,[0 for i in self.data_pointer[molecule].atoms]))\n #=======================================================\n pass","def ml_loop(side: str):\n\n # === Here is the execution order of the loop === #\n # 1. Put the initialization code here\n ball_served = False\n blocker_last_x = 0\n\n class Pred:\n pred = 100\n blocker_pred_x = 0\n last_command = 0\n blocker_vx = 0\n\n \n def move_to(player, pred) : #move platform to predicted position to catch ball \n if player == '1P':\n if scene_info[\"platform_1P\"][0]+20 > (pred-10) and scene_info[\"platform_1P\"][0]+20 < (pred+10): return 0 # NONE\n elif scene_info[\"platform_1P\"][0]+20 <= (pred-10) : return 1 # goes right\n else : return 2 # goes left\n else :\n if scene_info[\"platform_2P\"][0]+20 > (pred-10) and scene_info[\"platform_2P\"][0]+20 < (pred+10): return 0 # NONE\n elif scene_info[\"platform_2P\"][0]+20 <= (pred-10) : return 1 # goes right\n else : return 2 # goes left\n\n def ml_loop_for_1P(): \n # ball slicing\n if scene_info[\"ball_speed\"][1] > 0 and (scene_info[\"ball\"][1]+scene_info[\"ball_speed\"][1]) >= 415 and Pred.last_command == 0:\n print(\"------\")\n ball_x = scene_info[\"ball\"][0]\n ball_y = scene_info[\"ball\"][1]\n ball_vx = scene_info[\"ball_speed\"][0]\n ball_slice_vx = scene_info[\"ball_speed\"][0]+np.sign(scene_info[\"ball_speed\"][0])*3\n ball_vy = scene_info[\"ball_speed\"][1] \n blocker_x = scene_info['blocker'][0] + Pred.blocker_vx\n \n y = abs((415 - ball_y) // ball_vy)\n pred_ball_1P = ball_x + ball_vx * y\n\n y = abs((415 - 260) // ball_vy)\n pred_ball_blocker = pred_ball_1P + ball_slice_vx * y\n bound = pred_ball_blocker // 200 # Determine if it is beyond the boundary\n if (bound > 0): # pred > 200 # fix landing position\n if (bound%2 == 0) : \n pred_ball_blocker = pred_ball_blocker - bound*200 \n else :\n pred_ball_blocker = 200 - (pred_ball_blocker - 200*bound)\n elif (bound < 0) : # pred < 0\n if (bound%2 ==1) :\n pred_ball_blocker = abs(pred_ball_blocker - (bound+1) *200)\n else :\n pred_ball_blocker = pred_ball_blocker + (abs(bound)*200)\n \n y = abs((415 - 260) // ball_vy)\n Pred.blocker_pred_x = blocker_x + Pred.blocker_vx * y \n if Pred.blocker_pred_x < 0: Pred.blocker_pred_x = abs(Pred.blocker_pred_x)\n elif Pred.blocker_pred_x > 170: Pred.blocker_pred_x = 170 - (Pred.blocker_pred_x - 170)\n \n if pred_ball_blocker >= Pred.blocker_pred_x-10 and pred_ball_blocker < Pred.blocker_pred_x+40:\n print(\"slice will hit blicker\")\n # don't slice \n # use origin ball vx to predict will hit blocker or not\n # if will hit blicker let ball go reverse direction\n y = abs((415 - 260) // ball_vy)\n pred_ball_blocker = pred_ball_1P + ball_vx * y\n bound = pred_ball_blocker // 200 # Determine if it is beyond the boundary\n if (bound > 0): # pred > 200 # fix landing position\n if (bound%2 == 0) : \n pred_ball_blocker = pred_ball_blocker - bound*200 \n else :\n pred_ball_blocker = 200 - (pred_ball_blocker - 200*bound)\n elif (bound < 0) : # pred < 0\n if (bound%2 ==1) :\n pred_ball_blocker = abs(pred_ball_blocker - (bound+1) *200)\n else :\n pred_ball_blocker = pred_ball_blocker + (abs(bound)*200)\n\n if pred_ball_blocker >= Pred.blocker_pred_x-10 and pred_ball_blocker < Pred.blocker_pred_x+40:\n print(\"will hit blocker, hit reversed direction\")\n if scene_info[\"ball_speed\"][0] > 0: return 2\n else: return 1\n else: \n print(\"will not hit blicker, do nothing\")\n return 0\n else:\n # slice\n print(\"slice will not hit blocker\")\n if scene_info[\"ball_speed\"][0] > 0: return 1\n else: return 2\n\n elif scene_info[\"ball_speed\"][1] > 0 : # 球正在向下 # ball goes down\n x = ( scene_info[\"platform_1P\"][1]-scene_info[\"ball\"][1] ) // scene_info[\"ball_speed\"][1] # 幾個frame以後會需要接 # x means how many frames before catch the ball\n Pred.pred = scene_info[\"ball\"][0]+(scene_info[\"ball_speed\"][0]*x) # 預測最終位置 # pred means predict ball landing site \n bound = Pred.pred // 200 # Determine if it is beyond the boundary\n if (bound > 0): # pred > 200 # fix landing position\n if (bound%2 == 0) : \n Pred.pred = Pred.pred - bound*200 \n else :\n Pred.pred = 200 - (Pred.pred - 200*bound)\n elif (bound < 0) : # pred < 0\n if (bound%2 ==1) :\n Pred.pred = abs(Pred.pred - (bound+1) *200)\n else :\n Pred.pred = Pred.pred + (abs(bound)*200)\n return move_to(player = '1P',pred = Pred.pred)\n \n else : # 球正在向上 # ball goes up\n return move_to(player = '1P',pred = 100)\n\n\n\n def ml_loop_for_2P(): # as same as 1P\n if scene_info[\"ball_speed\"][1] > 0 : \n return move_to(player = '2P',pred = 100)\n else : \n x = ( scene_info[\"platform_2P\"][1]+30-scene_info[\"ball\"][1] ) // scene_info[\"ball_speed\"][1] \n pred = scene_info[\"ball\"][0]+(scene_info[\"ball_speed\"][0]*x) \n bound = pred // 200 \n if (bound > 0):\n if (bound%2 == 0):\n pred = pred - bound*200 \n else :\n pred = 200 - (pred - 200*bound)\n elif (bound < 0) :\n if bound%2 ==1:\n pred = abs(pred - (bound+1) *200)\n else :\n pred = pred + (abs(bound)*200)\n return move_to(player = '2P',pred = pred)\n\n # 2. Inform the game process that ml process is ready\n comm.ml_ready()\n\n # 3. Start an endless loop\n while True:\n # 3.1. Receive the scene information sent from the game process\n scene_info = comm.recv_from_game()\n\n # 3.2. If either of two sides wins the game, do the updating or\n # resetting stuff and inform the game process when the ml process\n # is ready.\n if scene_info[\"status\"] != \"GAME_ALIVE\":\n # Do some updating or resetting stuff\n ball_served = False\n\n # 3.2.1 Inform the game process that\n # the ml process is ready for the next round\n comm.ml_ready()\n continue\n\n # 3.3 Put the code here to handle the scene information\n\n # 3.4 Send the instruction for this frame to the game process\n if not ball_served:\n comm.send_to_game({\"frame\": scene_info[\"frame\"], \"command\": \"SERVE_TO_LEFT\"})\n blocker_last_x = scene_info[\"blocker\"][0]\n Pred.last_command = 0\n ball_served = True\n else:\n if side == \"1P\":\n Pred.blocker_vx = scene_info[\"blocker\"][0] - blocker_last_x\n if scene_info[\"blocker\"][0] == 0: Pred.blocker_vx = 5\n elif scene_info[\"blocker\"][0] == 170: Pred.blocker_vx = -5\n command = ml_loop_for_1P()\n blocker_last_x = scene_info[\"blocker\"][0]\n Pred.last_command = command\n else:\n command = ml_loop_for_2P()\n\n if command == 0:\n comm.send_to_game({\"frame\": scene_info[\"frame\"], \"command\": \"NONE\"})\n elif command == 1:\n comm.send_to_game({\"frame\": scene_info[\"frame\"], \"command\": \"MOVE_RIGHT\"})\n else :\n comm.send_to_game({\"frame\": scene_info[\"frame\"], \"command\": \"MOVE_LEFT\"})","def handle_stop(_):\n loop.force_unmute()","def get_loop(self) -> bool:\n return self._select_interface(self._rc_get_loop, self._http_get_loop)","def test_sync_task_no_server(comm):\n run_server, server_args, run_client, client_args = helper_config(comm, \"sync\")\n client = run_client(**client_args)\n try:\n client.connect()\n except Exception as exc: # pylint: disable=broad-except\n assert False, f\"unexpected exception: {exc}\"\n sleep(0.1)\n if comm == \"udp\":\n rr = client.read_coils(1, 1, slave=0x01)\n assert isinstance(rr, ModbusIOException)\n else:\n with pytest.raises((asyncio.exceptions.TimeoutError, ConnectionException)):\n client.read_coils(1, 1, slave=0x01)\n client.close()","def _loop_raw(raw):\n raise NotImplemented","def test_noFailure(self):\n for i in range(10):\n self.assertTrue(self.circuit_breaker.available())","async def hold_loop(self):\n pass","def temp_mainloop(self, cycles_to_respond=1000):\n\n if self.com_port_select.count() > 0:\n report = \"Begin measuring\"\n self.go_button.setEnabled(False) # don't allow to create new threads\n self.state_temp_loop(True)\n self.append_msg_box(report)\n\n while self.temp_loop_actiator:\n for num in range(self.com_port_select.count()):\n # self.MainWindow_exec_thread(lambda: self.sample_devices(cycles_to_respond, num))\n self.sample_devices(cycles_to_respond, num)\n self.temp_repr.plot_tc_temp(self.temp_log)\n timeo = float(self.timeout.text()) # timeout\n sleep(timeo)\n # -------- record data once in msg box --------\n\n self.go_button.setEnabled(True)\n self.led_light.setPixmap(QtGui.QPixmap(img[\"red_led\"]))\n else:\n self.append_msg_box(\"No device is connected\")","def testReset(self):\n \n clk = Signal(0)\n rst = Signal(1)\n clock_gen = ClkDriver(clk, period=4)\n \n out = Signal(intbv(0)[4:])\n counter = Counter(out, clk, rst)\n \n def test():\n for i in range(200):\n # count up to 9 then reset\n if int(out) == 9:\n rst.next = 0\n yield delay(1)\n self.assertEqual(int(out), 0)\n # turn off reset next time\n else:\n rst.next = 1\n yield delay(1)\n \n check = test()\n sim = Simulation(counter, clock_gen, check)\n sim.run(400, quiet=1)","def test_play_again_no(self):\n # Prepare test\n choice = random.choice(i18n.IN_NO_LIST)\n self.console.out_farewell = MagicMock()\n self.console.input = MagicMock(side_effect=[choice, StopIteration])\n\n # Run test\n self.console.ask_play_again()\n\n # Evaluate test\n calls = [call(FORMAT_NEWLINE_END(i18n.IN_MSG_REPLAY))]\n self.console.input.assert_has_calls(calls)\n self.console.out_farewell.assert_called_once()","def test_for_loop(self, modes, parse_input_mocked_metadata):\n bb = parse_input_mocked_metadata(\n \"for int m in {}\\n\\tMeasureFock() | m\".format(modes)\n )\n assert np.all(\n bb._forvar[\"m\"] == np.array(modes)\n )\n assert bb.operations == [\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[0]]},\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[1]]},\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[2]]}\n ]","def nanny(self): \n while not self.started and not self.failed:\n eventlet.sleep(.1)\n return not self.failed","def config_loop(self):\n loop_label = ['Loop OFF', 'Loop ON']\n group = self.make_ui_group(False, loop_label[self.loop])\n orig_loop = self.loop\n\n while True:\n action_left, action_right = (self.button_left.action(),\n self.button_right.action())\n if action_left is RichButton.HOLD:\n return self.loop is not orig_loop, False # Resume config\n if action_right is RichButton.HOLD:\n return self.loop is not orig_loop, True # Resume paint\n if RichButton.TAP in {action_left, action_right}:\n self.loop = not self.loop\n group.pop()\n group.append(centered_label(loop_label[self.loop], 40, 3))","def has_loop(self) -> bool:\n try:\n list(self)\n return False\n except ContainsLoopError:\n return True","def run(self):\n self.cmdloop()","def check_for_barrierless_reaction(self):\n # Check for barrierless reaction leading to new graphs\n if self.rc_opt_system_name not in self.systems: # Skip if already done\n print(\"Running Reactive Complex Optimization\")\n print(\"Settings:\")\n print(self.settings[self.rc_opt_system_name], \"\\n\")\n self.systems, success = self.observed_readuct_call(\n 'run_opt_task', self.systems, [self.rc_key], **self.settings[self.rc_opt_system_name]\n )\n self.throw_if_not_successful(\n success,\n self.systems,\n [self.rc_opt_system_name],\n [],\n \"Reactive complex optimization failed.\\n\",\n )\n _, rc_opt_graph, _, _, rc_opt_decision_lists = \\\n self.get_graph_charges_multiplicities(self.rc_opt_system_name, sum(self.start_charges))\n\n if not masm.JsonSerialization.equal_molecules(self.start_graph, rc_opt_graph):\n return rc_opt_graph, rc_opt_decision_lists\n return None, None","def ios_test_loop(self) -> Optional[pulumi.Input['IosTestLoopArgs']]:\n return pulumi.get(self, \"ios_test_loop\")","def block(self):\n # I WILL RUN FOR EVER \n # BUT WHY ARE YOU RUNNING ?\n self.__loop.run_forever()","def test_timeout_loop(self):\n\n self.assertIsNone(self.state.becomeCandidateTimeout)\n # This should do nothing\n self.state.cancelBecomeCandidateTimeout()\n self.assertIsNone(self.state.becomeCandidateTimeout)\n\n results = self.state.begin()\n\n self.state.resetElectionTimeout()\n self.assertTrue(self.state.electionTimeout > 0.150)\n self.assertTrue(self.state.electionTimeout < 0.350)\n self.assertTrue(isinstance(self.state.becomeCandidateTimeout,\n base.DelayedCall))","def test_readiness(self):\n self.command.package = self.input_ovf\n ready, reason = self.command.ready_to_run()\n self.assertFalse(ready)\n self.assertRegex(reason, \"No file information\")\n self.assertRaises(InvalidInputError, self.command.run)\n\n self.command.file_path = \"input.vmdk\"\n ready, reason = self.command.ready_to_run()\n self.assertTrue(ready)\n\n self.command.file_path = None\n self.command.file_id = \"file1\"\n ready, reason = self.command.ready_to_run()\n self.assertTrue(ready)","def timeout_loop(self):\r\n\r\n while not done:\r\n\r\n if (softwareInterfaceTimeout != -1) and (interfaceNotUsed > softwareInterfaceTimeout):\r\n\r\n stop(False)\r\n\r\n \r\n\r\n time.sleep(MONITOR_INTERVAL/1000000.0)\r\n\r\n self.interfaceNotUsed = self.interfaceNotUsed + 1","def loop_run(self):\n super(HasLoops, self).loop_run()\n for loop in getattr(self, \"_loops\", []):\n loop.loop_remove_from_parent = weak_method(self.remove_loop)\n loop.loop_run()","def loop(self):\n\n print(self.id + \" needs an overridden loop method\")","def test_shared_wires(self):\n wires = range(2)\n estimation_wires = range(1, 3)\n\n with pytest.raises(ValueError, match=\"No wires can be shared between the wires\"):\n quantum_monte_carlo(\n lambda: None, wires=wires, target_wire=0, estimation_wires=estimation_wires\n )","def test_selection():\n pdb_inp = iotbx.pdb.input(source_info=None, lines=pdb_answer_0)\n ncs_obj_phil = ncs.input(\n hierarchy=pdb_inp.construct_hierarchy())\n nrg = ncs_obj_phil.get_ncs_restraints_group_list()\n\n m1 = list(nrg[0].master_iselection)\n c1 = list(nrg[0].copies[0].iselection)\n c2 = list(nrg[0].copies[1].iselection)\n\n assert len(m1) == len(c1) # renumbering\n assert m1 == [0, 1, 2, 3, 4, 5, 6] # 0, 1, X, 3, X, 5, X | 0, 1, 3\n assert c1 == [7, 8, 9, 10, 11, 12, 13] # 7, 8, 9, X, X, 12, X | 4, 5, 7\n assert c2 == [14, 15, 16, 17, 18, 19, 20] # 14, 15, X, 17, X, 19, X | 8, 9, 11\n\n selection1 = flex.size_t([0,1,5,3,100,101])\n selection2 = flex.size_t([0,1,5,3,7,8,9,12,100,101])\n selection3 = flex.size_t([0,1,5,3,7,8,9,12,14,15,19,17,100,101])\n # gone iseqs for selection3: 2,4,6,10,11,13,16,18,20-99\n\n new_nrg = nrg.select(flex.bool(102, selection1))\n # only atoms in master are selected\n mt = list(new_nrg[0].master_iselection)\n c1t = list(new_nrg[0].copies[0].iselection)\n\n assert mt == []\n assert c1t == []\n\n # atoms selected in both master and copies\n new_nrg = nrg.select(flex.bool(102, selection2))\n # only atoms in master are selected\n mt = list(new_nrg[0].master_iselection)\n c1t = list(new_nrg[0].copies[0].iselection)\n\n assert mt == []\n assert c1t == []\n\n new_nrg = nrg.select(flex.bool(102, selection3))\n # only atoms in master are selected\n mt = list(new_nrg[0].master_iselection)\n c1t = list(new_nrg[0].copies[0].iselection)\n c2t = list(new_nrg[0].copies[1].iselection)\n\n assert mt == [0, 1, 3], list(mt)\n assert c1t == [4, 5, 7], list(c1t)\n assert c2t == [8, 9, 11], list(c2t)","def loop_run(self, loops):\n self.loop_seek(self.num_loops + loops)","def is_loop(*args):\n return _ida_hexrays.is_loop(*args)","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def run_until_stop(self):\n while self.commands[self.pointer] != END:\n # Get the cmd\n cmd = self.commands[self.pointer]\n opcode = cmd % 100\n modes = cmd // 100\n \n vals, locs, self.pointer = get_vals_and_locs(opcode, modes, self.pointer, self.commands)\n \n if opcode == ADD:\n self.commands[locs[2]] = vals[0] + vals[1]\n elif opcode == MUL:\n self.commands[locs[2]] = vals[0] * vals[1]\n elif opcode == INP:\n if self.inputs:\n self.commands[locs[0]] = self.inputs.pop(0)\n else:\n # Put the pointer back, so we run this opcode again\n self.pointer -= 2\n return False\n elif opcode == OUT:\n self.outputs.append(vals[0])\n elif opcode == JIT:\n if vals[0] != 0:\n self.pointer = vals[1]\n elif opcode == JIF:\n if vals[0] == 0:\n self.pointer = vals[1]\n elif opcode == LT:\n self.commands[locs[2]] = 1 if vals[0] < vals[1] else 0\n elif opcode == EQ:\n self.commands[locs[2]] = 1 if vals[0] == vals[1] else 0\n else:\n print(\"FAIL????\")\n\n return True","def _while_loop(pd, nmax, max_loop, ncore, outfile):\n \n # make sure the random seed is different for every processor\n random_number_seeds = [3456789, 7654321, 2435467, 8273645,\n 1085712, 4154712, 1248291, 8415917,\n 2345161, 5710916, 5718601, 7516234,\n 9235161, 4917519, 1111245, 8167834] \n \n # get the processor ID (1 - Ncore) and convert to single integer\n current = multiprocessing.current_process()\n pid = current._identity\n pid = pid[0]\n \n #\n # choose a different seed for each processor from the list so each processor has\n # a different randum number seed. Then, fiddle with each seed a little so \n # the seeds aren't the same every time the code is run\n seed = np.int(random_number_seeds[pid] * (np.random.rand()*(10.0 - 0.01) + 0.01))\n \n np.random.seed(seed)\n \n #print 'id and seed', pid, seed\n \n n_particles = 0\n loop_counter = 0\n fmin_scale = 1.0E-100 # -16 -> -32 -> -100\n F_max = np.max(pd.DF.f) #; F_min = np.min(pd.DF.f);\n F_min = np.min(pd.DF.f) * fmin_scale\n # F_max = np.max(pd.DF.f[:-1])#; F_max = 1.0E-88\n #print F_min, F_max\n if pd.optimize:\n relative_potential = pd._interpolate_relative_potential\n else:\n relative_potential = pd.DF.relative_potential\n \n \n pos = np.zeros((nmax, 3))\n vel = np.zeros((nmax, 3)) \n \n while (( n_particles < nmax) and (loop_counter < max_loop)):\n \n r = pd._choose_position()\n Psi = relative_potential(r) \n \n v = pd._choose_velocity(r, Psi)\n \n E = Psi - 0.5 * v * v\n \n f_E = pd.DF.interpolate_f(E)\n \n logF = ( np.random.rand()*(np.log10(F_max) - np.log10(F_min)) + np.log10(F_min) )\n \n # if choosing random F in log F, might be good to do the comparison in logspace as well\n #.... i.e log(F) <= log(f_E) \n #\n # 0 FOR F_E MEANS THAT E < E_min of the potential. THis happens when Psi - KE is smaller\n # than the value of the potential at large_r... should this be considered unbound \n # even though it isn't zero? Is this effectively zero? This has been adjusted in the velocity\n # picking routine but needs verification to make sure it works.... but regardless, I doubt\n # that this is the reason why the particles are failing for NFW but working for hernquist....\n #\n if np.abs(np.log10(f_E)) == np.inf:\n keep_particle = False\n _my_print('log value error... throwing out particle')\n else:\n keep_particle = (logF <= np.log10(f_E))\n\n \n if keep_particle: \n index = n_particles \n \n # \n # need to sample in cosine theta NOT theta!!!!! WTF!!!!!\n #\n #\n \n theta = np.arccos( np.random.rand() * (2.0) - 1.0)\n \n # convert position to cartesian using random theta and phi\n phi = np.random.rand() * 2.0 * np.pi\n \n x = np.sin(theta) * np.cos(phi)\n y = np.sin(theta) * np.sin(phi)\n z = np.cos(theta)\n \n pos[index] = r * np.array([x,y,z])\n\n # repeat for velocity using new random numbersw\n theta = np.arccos( np.random.rand() * (2.0) - 1.0)\n phi = np.random.rand() * 2.0 * np.pi\n \n vx = np.sin(theta) * np.cos(phi)\n vy = np.sin(theta) * np.sin(phi)\n vz = np.cos(theta)\n \n vel[index] = v * np.array([vx,vy,vz])\n \"\"\" \n #else: # do strict cartesian ... slower.... less attractive\n # \n # axis_list = [0, 1, 2]\n # random.shuffle(axis_list)\n \n # #axis_index = np.random.randint(3)\n # first_axis = axis_list[0]\n #\n # pos[index, first_axis] = np.random.rand() * (2.0*r) - r\n #del axis_list[axis_index]\n \n #axis_index = np.random.randint(2)\n # second_axis = axis_list[1]\n \n max_r = np.sqrt(r*r - pos[index,first_axis]**2)\n \n pos[index, second_axis] = np.random.rand()*(2.0 * max_r) - max_r\n #del axis_list[axis_index]\n \n max_r = np.sqrt(r*r - pos[index,first_axis]**2 - pos[index,second_axis]**2)\n \n third_axis = axis_list[2]\n pos[index, third_axis] = np.random.rand() * (2.0 * max_r) - max_r\n \n if np.sqrt(pos[index,0]**2 + pos[index,1]**2 + pos[index,2]**2) > r:\n _my_print('R IS TOO LARGE')\n \n ###\n axis_list = [0, 1, 2]\n random.shuffle(axis_list)\n \n #axis_index = np.random.randint(3)\n first_axis = axis_list[0]\n \n vel[index, first_axis] = np.random.rand() * (2.0*v) - v\n #del axis_list[axis_index]\n \n #axis_index = np.random.randint(2)\n second_axis = axis_list[1]\n \n max_v = np.sqrt(v*v - vel[index,first_axis]**2)\n \n vel[index, second_axis] = np.random.rand()*(2.0 * max_v) - max_v\n #del axis_list[axis_index]\n \n max_v = np.sqrt(v*v - vel[index,first_axis]**2 - vel[index,second_axis]**2)\n \n third_axis = axis_list[2]\n vel[index, third_axis] = np.random.rand() * (2.0 * max_v) - max_v \n \n \n \"\"\"\n n_particles = n_particles + 1\n \n if (loop_counter % 5000) == 0:\n _my_print(\"Have %4i particles. On loop %6i\"%(n_particles, loop_counter))\n loop_counter = loop_counter + 1\n \n # now write out to a temporary file\n f = open(outfile + \"_%02i_\"%(pid) + \".temp\", 'w')\n fmt = \"%12.12E %12.12E %12.12E %12.12E %12.12E %12.12E %12.12E\\n\"\n \n \n for i in np.arange(nmax):\n f.write(fmt%(pd.M_part, pos[i,0], pos[i,1], pos[i,2], \n vel[i,0], vel[i,1], vel[i,2]))\n \n \n f.close() \n \n return pos, vel","def basic_noisy_selfloop_subsystem():\n net = basic_noisy_selfloop_network()\n state = basic_state()\n return Subsystem(net, state)","def takeControl(self):\n mainloop()","def takeControl(self):\n mainloop()","def while_loop(self):\n if self._loop is None:\n self._loop = self._while_loop()\n return self._loop\n return self._loop","def running_loop(self, run_check_ms=None):\r\n if self.board.area.down_click_call is None:\r\n raise SelectError(\"board.area.down_click_call is not set\")\r\n if self.numgame is not None and self.ngame >= self.numgame:\r\n SlTrace.lg(f\"running_loop: ngame={self.ngame} > numgame {self.numgame}\")\r\n self.running = False\r\n self.run = False\r\n return\r\n \r\n self.running = True # Still in game\r\n self.run = True # progressing (not paused)\r\n self.first_time = True \r\n self.game_start_ts = SlTrace.getTs(6)\r\n self.game_control_updates()\r\n if run_check_ms is not None:\r\n self.run_check_ms = run_check_ms\r\n BlinkerMultiState.enable()\r\n \r\n while self.running:\r\n SlTrace.lg(\"running_loop\", \"running_loop\")\r\n self.mw.update()\r\n if ActiveCheck.not_active():\r\n break\r\n SlTrace.lg(\"running_loop active\", \"running_loop\")\r\n self.mw.update_idletasks()\r\n if self.event_check():\r\n continue # Gobble up pending events\r\n \r\n if (self.cmd_stream is not None\r\n and not self.cmd_stream.is_eof()):\r\n self.run_file()\r\n self.first_time = False # Assume file did that\r\n continue # Check if more\r\n else:\r\n if self.first_time:\r\n if not self.start_game():\r\n break\r\n self.first_time = False\r\n if not self.make_move():\r\n break \r\n \r\n SlTrace.lg(\"running_loop after loop\", \"running_loop\")\r\n BlinkerMultiState.disable()\r\n \r\n if self.on_end is not None:\r\n SlTrace.lg(\"running_loop doing on_end\", \"running_loop\")\r\n self.mw.after(0, self.on_end) # After run processing\r","def test_compute_partial_charges(self):\n # TODO: Test only one molecule for speed?\n # TODO: Do we need to deepcopy each molecule, or is setUp called separately for each test method?\n import numpy as np\n from simtk import unit\n\n # Do not modify original molecules.\n molecules = copy.deepcopy(mini_drug_bank())\n\n # Test a single toolkit at a time\n # Removed ['amber', 'amberff94'] from OE list, as those won't find the residue types they're expecting\n toolkit_to_charge_method = {\n OpenEyeToolkitWrapper: [\n \"mmff\",\n \"mmff94\",\n \"am1bcc\",\n \"am1bccnosymspt\",\n \"am1bccelf10\",\n ],\n AmberToolsToolkitWrapper: [\"bcc\", \"gas\", \"mul\"],\n }\n\n manual_skips = []\n\n manual_skips.append(\n \"ZINC1564378\"\n ) # Warning: OEMMFF94Charges: assigning OEMMFFAtomTypes failed on mol .\n manual_skips.append(\n \"ZINC00265517\"\n ) # Warning: OEMMFF94Charges: assigning OEMMFFAtomTypes failed on mol .\n\n for toolkit in list(toolkit_to_charge_method.keys()):\n toolkit_registry = ToolkitRegistry(toolkit_precedence=[toolkit])\n for charge_model in toolkit_to_charge_method[toolkit]:\n c = 0\n for molecule in molecules[:1]: # Just test first molecule to save time\n c += 1\n if molecule.name in manual_skips: # Manual skips, hopefully rare\n continue\n molecule.compute_partial_charges(\n charge_model=charge_model, toolkit_registry=toolkit_registry\n )\n charges1 = molecule._partial_charges\n # Make sure everything isn't 0s\n assert (abs(charges1 / unit.elementary_charge) > 0.01).any()\n # Check total charge\n charges_sum_unitless = charges1.sum() / unit.elementary_charge\n # if abs(charges_sum_unitless - float(molecule.total_charge)) > 0.0001:\n # print('c {} molecule {} charge_sum {} molecule.total_charge {}'.format(c, molecule.name,\n # charges_sum_unitless,\n # molecule.total_charge))\n # assert_almost_equal(charges_sum_unitless, molecule.total_charge, decimal=4)\n\n # Call should be faster second time due to caching\n # TODO: Implement caching\n molecule.compute_partial_charges(\n charge_model=charge_model, toolkit_registry=toolkit_registry\n )\n charges2 = molecule._partial_charges\n assert np.allclose(charges1, charges2, atol=0.002)","def main_loop(self):\n center_point = self.mot.center_point\n\n screen_width = center_point[0] * 2\n screen_height = center_point[1] * 2\n\n time.sleep(1)\n pretty_progress_bar(\n 3,\n )\n\n # while int(time.time()) - start <= 10:\n while not self.mot.abort:\n object1_position = self.mot.position(self.color1)[0]\n object2_velocity = self.mot.speed(self.color2)\n # print(object2_velocity)\n\n self.compare(object1_position[0] < 0.25 * screen_width, 'left')\n self.compare(object1_position[0] > 0.75 * screen_width, 'right')\n self.compare(object1_position[1] < 0.25 * screen_height, 'jump')\n self.burst_compare(object2_velocity > 150, 'fire')\n\n # print('KEYBOARD ABORT')","async def loop(self, ctx: commands.Context) -> Optional[bool]:\n\n self.queue[ctx.guild.id].loop = (\n Loops.LOOP if self.queue[ctx.guild.id].loop != Loops.LOOP else Loops.NO_LOOP\n )\n return self.queue[ctx.guild.id].loop == Loops.LOOP","def test_select_sdf_mol2(self):\n with mmtools.utils.temporary_directory() as tmp_dir:\n yaml_content = \"\"\"\n ---\n options:\n output_dir: {}\n setup_dir: .\n molecules:\n sdf_0:\n filepath: {}\n antechamber: {{charge_method: bcc}}\n leap: {{parameters: leaprc.gaff}}\n select: 0\n sdf_1:\n filepath: {}\n antechamber: {{charge_method: bcc}}\n leap: {{parameters: leaprc.gaff}}\n select: 1\n mol2_0:\n filepath: {}\n antechamber: {{charge_method: bcc}}\n leap: {{parameters: leaprc.gaff}}\n select: 0\n mol2_1:\n filepath: {}\n antechamber: {{charge_method: bcc}}\n leap: {{parameters: leaprc.gaff}}\n select: 1\n \"\"\".format(tmp_dir, self.sdf_path, self.sdf_path, self.mol2_path, self.mol2_path)\n yaml_content = textwrap.dedent(yaml_content)\n exp_builder = ExperimentBuilder(yaml_content)\n\n for extension in ['sdf', 'mol2']:\n multi_path = getattr(self, extension + '_path')\n for model_idx in [0, 1]:\n mol_id = extension + '_' + str(model_idx)\n\n # The molecule now is neither set up nor processed\n is_setup, is_processed = exp_builder._db.is_molecule_setup(mol_id)\n assert is_setup is False\n assert is_processed is False\n\n exp_builder._db._setup_molecules(mol_id)\n\n # The setup of the molecule must isolate the frame in a single-frame PDB\n single_mol_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\n mol_id, mol_id + '.' + extension)\n assert os.path.exists(os.path.join(single_mol_path))\n assert os.path.getsize(os.path.join(single_mol_path)) > 0\n if extension == 'mol2':\n # OpenEye loses the resname when writing a mol2 file.\n mol2_file = utils.Mol2File(single_mol_path)\n assert len(list(mol2_file.resnames)) == 1\n assert mol2_file.resname != '<0>'\n\n # sdf files must be converted to mol2 to be fed to antechamber\n if extension == 'sdf':\n single_mol_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\n mol_id, mol_id + '.mol2')\n assert os.path.exists(os.path.join(single_mol_path))\n assert os.path.getsize(os.path.join(single_mol_path)) > 0\n\n # Check antechamber parametrization\n single_mol_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\n mol_id, mol_id + '.gaff.mol2')\n assert os.path.exists(os.path.join(single_mol_path))\n assert os.path.getsize(os.path.join(single_mol_path)) > 0\n\n # The positions must be approximately correct (antechamber move the molecule)\n selected_oe_mol = utils.load_oe_molecules(single_mol_path, molecule_idx=0)\n selected_pos = utils.get_oe_mol_positions(selected_oe_mol)\n second_oe_mol = utils.load_oe_molecules(multi_path, molecule_idx=model_idx)\n second_pos = utils.get_oe_mol_positions(second_oe_mol)\n assert selected_oe_mol.NumConfs() == 1\n assert np.allclose(selected_pos, second_pos, atol=1e-1)\n\n # The molecule now both set up and processed\n is_setup, is_processed = exp_builder._db.is_molecule_setup(mol_id)\n assert is_setup is True\n assert is_processed is True\n\n # A new instance of ExperimentBuilder is able to resume with correct molecule\n exp_builder = ExperimentBuilder(yaml_content)\n is_setup, is_processed = exp_builder._db.is_molecule_setup(mol_id)\n assert is_setup is True\n assert is_processed is True","async def _do_if_possible(self, coroutine: Awaitable[None]) -> None:\n try:\n await coroutine\n except IncorrectStateException:\n pass","def run1():\n #Reseting motors\n ResetRobot.reset_wheel_motors()\n ResetRobot.reset_attachment_motors()\n CalibrateRobot.calibrate_gyro()\n\n #mission M01 and M02 - space travel and solar panel\n M01_M02()\n \n #Mission M05- Extraction \n M05_M14()\n\n #Back to base before Gerhard (Remove comment if necessary)\n return_to_base1()\n\n # Must delete for competition.. This is to set up forklift to repeat run.\n Robot.attachment_left.on_for_rotations(-100, 8) #Raises Forklift "],"string":"[\n \"def test_molecule_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the molecules.\\n i = 0\\n for molecule in mol_res_spin.molecule_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_spin_loop_no_selection(self):\\n\\n # Spin data.\\n select = [0, 1, 0, 0, 1, 1, 0, 1]\\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 8)\",\n \"def test_molecule_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for molecule in mol_res_spin.molecule_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_molecule_loop(self):\\n\\n # Loop over the molecules.\\n for mol in mol_res_spin.molecule_loop('#RNA'):\\n # Test the molecule name.\\n self.assertEqual(mol.name, 'RNA')\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)\",\n \"def test_spin_loop(self):\\n\\n # Spin data.\\n select = [1, 0]\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, 'N5')\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 2)\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_run_molecule_not_selected(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\", sequence, molecule_selector=lambda mol: False\\n )\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert vermouth.utils.are_all_equal(found)\\n assert found[0] is None\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_spin_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for spin in mol_res_spin.spin_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_spin_loop_multiatom(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_residue_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for residue in mol_res_spin.residue_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_spin_loop_wildcard(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N*'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_residue_loop(self):\\n\\n # Loop over the residues.\\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\\n # Test the selection.\\n self.assertEqual(res.num, 2)\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)\",\n \"def test_run_loop_success(self):\\n found = False\\n pyint = Interpreter(limit=15)\\n try:\\n pyint.run(code=BF_CODE_LOOP_TWICE)\\n except SystemExit: \\n found = True\\n self.assertFalse(found)\",\n \"def test_multi_molecules_cycle_one(self, multi_mol_system_irregular):\\n sequence = \\\"A\\\"\\n expected = [sequence] * (15 * 3)\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_irregular)\\n found = self.sequence_from_system(multi_mol_system_irregular, \\\"test\\\")\\n assert found == expected\",\n \"def test_multi_molecules_cycle(self, multi_mol_system_regular, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n expected = expected * 3\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_regular)\\n found = self.sequence_from_system(multi_mol_system_regular, \\\"test\\\")\\n assert found == expected\",\n \"def test_return_molecule(self):\\n\\n # Ask for a few molecules.\\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\\n\\n # Test the data of molecule 1.\\n self.assertEqual(mol1.name, 'Ap4Aase')\\n\\n # Test the data of molecule 2.\\n self.assertEqual(mol2.name, 'RNA')\",\n \"def ROOMSELECTION_LOOP():\\n pass\",\n \"def test_single_molecules_cycle_one(self, single_mol_system):\\n sequence = \\\"A\\\"\\n expected = [sequence] * (5 * 3)\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def loop(self):\\n raise NotImplementedError()\",\n \"def test_run_molecule(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def test_return_molecule_pipe_fail(self):\\n\\n # Try to get a molecule from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')\",\n \"def test_boolean_and_selection(self):\\n\\n # The selection loop:\\n sel = list(mol_res_spin.residue_loop(\\\"#Ap4Aase:4 & :Pro\\\"))\\n\\n # Test:\\n self.assertEqual(len(sel), 1)\\n for res in sel:\\n self.assert_(res.name == \\\"Pro\\\" and res.num == 4)\",\n \"def loop(self):\\n pass\",\n \"async def checkNewLoop(self):\\n pass\",\n \"def _run(self):\\n while(self._loop):\\n pass\",\n \"def do_simulation_loop(self) -> tuple[bool, bool]:\\n running, reset = True, False\\n for event in pygame.event.get():\\n if check_for_quit(event):\\n running = False\\n elif check_for_reset(event):\\n running = False\\n reset = True\\n self.simulation.do_step()\\n self.update_visualization()\\n self.simple_pygame.loop()\\n return running, reset\",\n \"async def hold_loop(self, *args) -> bool:\\n raise NotImplementedError\",\n \"def testNoMatchingMasses(self):\\n mc = nigel.MassSelection(nb, mlow = 10, mhigh = 10.101)\\n self.assertIsNone(mc)\",\n \"def PLAYERSELECTION_LOOP():\\n pass\",\n \"def test_run_loop_exc(self):\\n with self.assertRaises(ExecutionException):\\n pyint = Interpreter(limit=1)\\n pyint.run(code=BF_CODE_LOOP_TWICE)\",\n \"def MULTIPLAYER_LOOP():\\n pass\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_control_loop_example():\\n example.control.print_error_measurement()\\n matplotlib.use('agg')\\n example.control.visualise_error_measurement(fig_file='cs_compare.pdf')\\n assert path.isfile('cs_compare.pdf')\\n example.control.sil_comparison()\",\n \"def algorithm_loop(self):\",\n \"def test_empty_with_filter(multi_mol_system_irregular):\\n sequence = \\\"not empty\\\"\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\", sequence, molecule_selector=lambda mol: False\\n )\\n with pytest.raises(ValueError):\\n processor.run_system(multi_mol_system_irregular)\",\n \"def test_simulate(self):\\n sut = gireactor.PortableGIReactor(useGtk=False)\\n # Double check that reactor has no sleep period.\\n self.assertIs(None, sut.timeout())\\n\\n sut.simulate()\",\n \"def run_test(dut):\\n tb = MyTB(dut,int(os.environ['SIM_LEN']))\\n cocotb.fork(Clock(dut.clk, 10).start())\\n stim_thread = cocotb.fork(tb.stim_mux())\\n read_thread = cocotb.fork(tb.read_mux())\\n yield stim_thread.join()\\n yield read_thread.join()\\n if tb.sim_mux_sel != tb.py_sel_input:\\n raise TestFailure(\\\"Mux selection failed.\\\")\\n else:\\n raise TestSuccess(\\\"Mux sel successful\\\")\",\n \"def test_boolean_complex_selection(self):\\n\\n # The residue selection loop.\\n sel = list(mol_res_spin.residue_loop(\\\"#Ap4Aase:4 & :Pro | #RNA\\\"))\\n\\n # Residue names and numbers.\\n names = ['Pro', None, None]\\n numbers = [4, -5, -4]\\n\\n # The residues.\\n self.assertEqual(len(sel), 3)\\n for i in range(3):\\n self.assertEqual(sel[i].name, names[i])\\n self.assertEqual(sel[i].num, numbers[i])\",\n \"def run_one_test_cycle(self):\\n logging.info(\\n \\\"{0} operations remaining: {1}\\\".format(\\n self.args.pm_operation, self.args.repetitions\\n )\\n )\\n\\n self.check_last_cycle_duration()\\n if self.args.repetitions > 0:\\n self.run_pm_command()\\n else:\\n self.summary()\",\n \"def test_no_immediate_stop(self):\\n script = ControlScript()\\n options = ControlOptions()\\n options.parseOptions([b\\\"--data-path\\\", self.mktemp()])\\n self.assertNoResult(script.main(MemoryCoreReactor(), options))\",\n \"def run_no_input(self, initial=None, context=None):\\n for _ in self.run(initial, context):\\n raise RuntimeError(\\\"Machine requires input to continue!\\\")\",\n \"def test_single_molecule(self, single_mol_system, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def loop(self, loop: bool=None):\\n self._select_interface(self._rc_loop, self._http_loop, loop)\",\n \"def test_circularloop(self):\\n cmd = f\\\"{SRC_LISTER} -i {PWD}/main\\\"\\n with subprocess.Popen(\\n shlex.split(cmd), stdout=subprocess.PIPE, stderr=subprocess.PIPE\\n ) as proc:\\n try:\\n out, err = proc.communicate(timeout=5)\\n assert len(err.strip()) > 0, \\\"Expected a circular reference error\\\"\\n except subprocess.TimeoutExpired as te:\\n print(\\\"Unexpected parser timeout during infinite loop test\\\")\",\n \"def runSingleTest(cube, instructions, interval):\\n root = Tk()\\n interface = Interface(root, cube)\\n root.after(0, interface.runInstructions, instructions, interval)\\n root.mainloop()\",\n \"def test_reset(self):\\n ran = []\\n def foo():\\n ran.append(None)\\n\\n c = task.Clock()\\n lc = TestableLoopingCall(c, foo)\\n lc.start(2, now=False)\\n c.advance(1)\\n lc.reset()\\n c.advance(1)\\n self.assertEqual(ran, [])\\n c.advance(1)\\n self.assertEqual(ran, [None])\",\n \"def watch_loop(self):\\n # Double threaded function that allows to stop the loop mid execution\\n def repeatIt():\\n # reset UI and flag before starting loop\\n self.resetLabels()\\n self.reset_scrollbar()\\n # enable stop button\\n self.btnStop.config(state=\\\"normal\\\")\\n # disable button while loop is running\\n self.btnStart.config(state=\\\"disabled\\\")\\n self.txtLoop.config(state=\\\"disabled\\\", textvariable=self.loopCounterUI)\\n self.labelLoop.config(text=\\\"Loop Count: \\\")\\n\\n while self.loopCount.get() > 0:\\n # move scrollbar to bottom\\n self.testCanvas.yview_moveto(0)\\n # count the loop\\n self.loopCounterUI.set(self.loopCounterUI.get() + 1)\\n\\n # Run the test cases\\n self.runThis()\\n\\n # Below are just to reset the UI\\n if not self.stopLoop:\\n print(\\\"loop not stopped so proceed\\\")\\n # let user know script is stopping\\n x = Label(\\n self.testFrame, text=f'End of Loop',\\n background=self.bgChooser(),\\n foreground=\\\"#630984\\\",\\n font=self.boldFont)\\n x.pack(fill=X)\\n # flag gor BG and labels\\n self.bgCounter += 1\\n self.LabelLists.append(x)\\n # allow window to catch up\\n self.tkRoot.update()\\n self.update_scrollbar()\\n else:\\n print(\\\"loop has been stopped so not gonna print End of Loop\\\")\\n\\n # pause before restarting loop\\n self.loopCount.set(self.loopCount.get()-1)\\n time.sleep(1)\\n\\n # disable stop button\\n self.btnStop.config(state=\\\"disabled\\\")\\n # re-enable button after loop is done\\n self.btnStart.config(state=\\\"normal\\\")\\n self.txtLoop.config(state=\\\"normal\\\", textvariable=self.loopCount)\\n self.labelLoop.config(text=\\\"Enter Loop Count: \\\")\\n # self.testCanvas.yview_moveto(0)\\n # Let user know the script is done\\n if not self.stopLoop:\\n # loop did not stopped\\n x = Label(\\n self.testFrame, text=f'Test is done!',\\n background=self.bgChooser(),\\n foreground=\\\"#057224\\\",\\n font=self.boldFont)\\n x.pack(fill=X)\\n self.bgCounter += 1\\n else:\\n x = Label(\\n self.testFrame, text=f'Test stopped!',\\n background=self.bgChooser(),\\n foreground=\\\"#057224\\\",\\n font=self.boldFont)\\n x.pack(fill=X)\\n self.bgCounter += 1\\n self.btnStart.config(state=\\\"normal\\\")\\n self.txtLoop.config(state=\\\"normal\\\", textvariable=self.loopCount)\\n self.labelLoop.config(text=\\\"Enter Loop count: \\\")\\n self.loopCount.set(50000)\\n self.LabelLists.append(x)\\n # allow window to catch up\\n self.tkRoot.update()\\n self.update_scrollbar()\\n thread = threading.Thread(target=repeatIt)\\n thread.start()\",\n \"def _run_cycle(self):\\n pass\",\n \"def infinite_loop():\\n return True\",\n \"def pauseLoop(self):\\n print('SYNC stim detected LOW')\\n self.loopRunning = False\",\n \"def run(self):\\n while True:\\n try:\\n self.check_value()\\n except Exception as e:\\n print(f\\\"[ERROR]: Error running the continuous run loop on sample_module: {e}\\\")\\n continue\",\n \"def test_select_pdb_conformation(self):\\n with mmtools.utils.temporary_directory() as tmp_dir:\\n yaml_content = \\\"\\\"\\\"\\n ---\\n options:\\n output_dir: {}\\n setup_dir: .\\n molecules:\\n selected:\\n filepath: {}\\n leap: {{parameters: oldff/leaprc.ff14SB}}\\n select: 1\\n \\\"\\\"\\\".format(tmp_dir, self.pdb_path)\\n yaml_content = textwrap.dedent(yaml_content)\\n exp_builder = ExperimentBuilder(yaml_content)\\n\\n # The molecule now is neither set up nor processed\\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\\n assert is_setup is False\\n assert is_processed is False\\n\\n # The setup of the molecule must isolate the frame in a single-frame PDB\\n exp_builder._db._setup_molecules('selected')\\n selected_pdb_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\\n 'selected', 'selected.pdb')\\n assert os.path.exists(os.path.join(selected_pdb_path))\\n assert os.path.getsize(os.path.join(selected_pdb_path)) > 0\\n\\n # The positions must be the ones of the second frame\\n selected_pdb = PDBFile(selected_pdb_path)\\n selected_pos = selected_pdb.getPositions(asNumpy=True)\\n second_pos = PDBFile(self.pdb_path).getPositions(asNumpy=True, frame=1)\\n assert selected_pdb.getNumFrames() == 1\\n assert (selected_pos == second_pos).all()\\n\\n # The description of the molecule is now updated\\n assert os.path.normpath(exp_builder._db.molecules['selected']['filepath']) == selected_pdb_path\\n\\n # The molecule now both set up and processed\\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\\n assert is_setup is True\\n assert is_processed is True\\n\\n # A new instance of ExperimentBuilder is able to resume with correct molecule\\n exp_builder = ExperimentBuilder(yaml_content)\\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\\n assert is_setup is True\\n assert is_processed is True\",\n \"def _handle_loop(self):\\n pass\",\n \"def test_simulationRun(self):\\n self.opt = { 'temperature' : 300.0, 'friction' : 1, 'dt' : 0.00002,\\n 'nIter' : 2, 'nstepsNC' : 2, 'nstepsMD' : 1, 'nprop' : 1,\\n 'nonbondedMethod' : 'NoCutoff', 'constraints': 'HBonds',\\n 'trajectory_interval' : 1, 'reporter_interval' : 1,\\n 'outfname' : 'mc-test',\\n 'platform' : None,\\n 'constraints' : 'HBonds',\\n 'mc_per_iter' : 2 }\\n\\n structure = self.full_struct\\n class SetRotationMove(RandomLigandRotationMove):\\n def __init__(self, structure, resname='LIG'):\\n super(SetRotationMove, self).__init__(structure, resname)\\n\\n def move(self, context):\\n \\\"\\\"\\\"Function that performs a random rotation about the\\n center of mass of the ligand.\\n \\\"\\\"\\\"\\n #TODO: check if we need to deepcopy\\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\\n\\n self.positions = positions[self.atom_indices]\\n self.center_of_mass = self.getCenterOfMass(self.positions, self.masses)\\n reduced_pos = self.positions - self.center_of_mass\\n\\n # Define random rotational move on the ligand\\n #set rotation so that test is reproducible\\n set_rotation_matrix = np.array([[-0.62297988, -0.17349253, 0.7627558 ],\\n [ 0.55082352, -0.78964857, 0.27027502],\\n [ 0.55541834, 0.58851973, 0.58749893]])\\n\\n\\n #set_rotation_matrix = np.array([[1, 0, 0],\\n # [0, 1, 0],\\n # [0, 0, 1]])\\n\\n #multiply lig coordinates by rot matrix and add back COM translation from origin\\n rot_move = np.dot(reduced_pos, set_rotation_matrix) * positions.unit + self.center_of_mass\\n\\n # Update ligand positions in nc_sim\\n for index, atomidx in enumerate(self.atom_indices):\\n positions[atomidx] = rot_move[index]\\n context.setPositions(positions)\\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\\n self.positions = positions[self.atom_indices]\\n return context\\n\\n\\n self.model = SetRotationMove(structure, resname='ALA')\\n #self.model = RandomLigandRotationMove(structure, resname='ALA')\\n\\n self.model.atom_indices = range(22)\\n self.model.topology = structure[self.model.atom_indices].topology\\n self.model.positions = structure[self.model.atom_indices].positions\\n self.model.calculateProperties()\\n\\n self.mover = MoveEngine(self.model)\\n #Initialize the SimulationFactory object\\n sims = SimulationFactory(structure, self.mover, **self.opt)\\n #print(sims)\\n system = sims.generateSystem(structure, **self.opt)\\n simdict = sims.createSimulationSet()\\n alch_system = sims.generateAlchSystem(system, self.model.atom_indices)\\n self.nc_sim = sims.generateSimFromStruct(structure, self.mover, alch_system, ncmc=True, **self.opt)\\n self.model.calculateProperties()\\n self.initial_positions = self.nc_sim.context.getState(getPositions=True).getPositions(asNumpy=True)\\n mc_sim = Simulation(sims, self.mover, **self.opt)\\n #monkeypatch to access acceptance value\\n def nacceptRejectMC(self, temperature=300, **opt):\\n \\\"\\\"\\\"Function that chooses to accept or reject the proposed move.\\n \\\"\\\"\\\"\\n md_state0 = self.current_state['md']['state0']\\n md_state1 = self.current_state['md']['state1']\\n log_mc = (md_state1['potential_energy'] - md_state0['potential_energy']) * (-1.0/self.nc_sim.context._integrator.kT)\\n randnum = math.log(np.random.random())\\n\\n if log_mc > randnum:\\n self.accept += 1\\n print('MC MOVE ACCEPTED: log_mc {} > randnum {}'.format(log_mc, randnum) )\\n self.md_sim.context.setPositions(md_state1['positions'])\\n else:\\n self.reject += 1\\n print('MC MOVE REJECTED: log_mc {} < {}'.format(log_mc, randnum) )\\n self.md_sim.context.setPositions(md_state0['positions'])\\n self.log_mc = log_mc\\n self.md_sim.context.setVelocitiesToTemperature(self.opt['temperature'])\\n mc_sim.acceptRejectMC = nacceptRejectMC\\n nacceptRejectMC.__get__(mc_sim)\\n mc_sim.acceptRejectMC = types.MethodType(nacceptRejectMC, mc_sim)\\n mc_sim.runMC(self.opt['nIter'])\\n #get log acceptance\\n print(mc_sim.log_mc)\\n #if mc is working, should be around -24.1\\n assert mc_sim.log_mc <= -23.8 and mc_sim.log_mc >= -24.3\",\n \"def loop(self):\\n while self.dispatch(True) is not QUIT:\\n pass\",\n \"def runMasking(self,roiNode,inputVolumes,inPlace):\\n\\n self.delayDisplay('Running the algorithm')\\n\\n for vol in inputVolumes:\\n self.maskVolume(vol, roiNode, inPlace)\\n\\n return True\\n\\n self.delayDisplay('Running the aglorithm')\",\n \"def run(self):\\n while True:\\n if self.job_q.empty():\\n self.message_q.put(False)\\n return\\n try:\\n smolecule = self.job_q.get()\\n self.data_pointer[smolecule].get_adp(self.Temp)\\n except IndexError:\\n self.message_q.put((smolecule, None))\\n try:\\n self.message_q.put((smolecule, [j.adp['cart_int'] for j in self.data_pointer[smolecule].atoms]))\\n except KeyError:\\n # =======================================================\\n # self.message_q.put((molecule,[0 for i in self.data_pointer[molecule].atoms]))\\n #=======================================================\\n pass\",\n \"def ml_loop(side: str):\\n\\n # === Here is the execution order of the loop === #\\n # 1. Put the initialization code here\\n ball_served = False\\n blocker_last_x = 0\\n\\n class Pred:\\n pred = 100\\n blocker_pred_x = 0\\n last_command = 0\\n blocker_vx = 0\\n\\n \\n def move_to(player, pred) : #move platform to predicted position to catch ball \\n if player == '1P':\\n if scene_info[\\\"platform_1P\\\"][0]+20 > (pred-10) and scene_info[\\\"platform_1P\\\"][0]+20 < (pred+10): return 0 # NONE\\n elif scene_info[\\\"platform_1P\\\"][0]+20 <= (pred-10) : return 1 # goes right\\n else : return 2 # goes left\\n else :\\n if scene_info[\\\"platform_2P\\\"][0]+20 > (pred-10) and scene_info[\\\"platform_2P\\\"][0]+20 < (pred+10): return 0 # NONE\\n elif scene_info[\\\"platform_2P\\\"][0]+20 <= (pred-10) : return 1 # goes right\\n else : return 2 # goes left\\n\\n def ml_loop_for_1P(): \\n # ball slicing\\n if scene_info[\\\"ball_speed\\\"][1] > 0 and (scene_info[\\\"ball\\\"][1]+scene_info[\\\"ball_speed\\\"][1]) >= 415 and Pred.last_command == 0:\\n print(\\\"------\\\")\\n ball_x = scene_info[\\\"ball\\\"][0]\\n ball_y = scene_info[\\\"ball\\\"][1]\\n ball_vx = scene_info[\\\"ball_speed\\\"][0]\\n ball_slice_vx = scene_info[\\\"ball_speed\\\"][0]+np.sign(scene_info[\\\"ball_speed\\\"][0])*3\\n ball_vy = scene_info[\\\"ball_speed\\\"][1] \\n blocker_x = scene_info['blocker'][0] + Pred.blocker_vx\\n \\n y = abs((415 - ball_y) // ball_vy)\\n pred_ball_1P = ball_x + ball_vx * y\\n\\n y = abs((415 - 260) // ball_vy)\\n pred_ball_blocker = pred_ball_1P + ball_slice_vx * y\\n bound = pred_ball_blocker // 200 # Determine if it is beyond the boundary\\n if (bound > 0): # pred > 200 # fix landing position\\n if (bound%2 == 0) : \\n pred_ball_blocker = pred_ball_blocker - bound*200 \\n else :\\n pred_ball_blocker = 200 - (pred_ball_blocker - 200*bound)\\n elif (bound < 0) : # pred < 0\\n if (bound%2 ==1) :\\n pred_ball_blocker = abs(pred_ball_blocker - (bound+1) *200)\\n else :\\n pred_ball_blocker = pred_ball_blocker + (abs(bound)*200)\\n \\n y = abs((415 - 260) // ball_vy)\\n Pred.blocker_pred_x = blocker_x + Pred.blocker_vx * y \\n if Pred.blocker_pred_x < 0: Pred.blocker_pred_x = abs(Pred.blocker_pred_x)\\n elif Pred.blocker_pred_x > 170: Pred.blocker_pred_x = 170 - (Pred.blocker_pred_x - 170)\\n \\n if pred_ball_blocker >= Pred.blocker_pred_x-10 and pred_ball_blocker < Pred.blocker_pred_x+40:\\n print(\\\"slice will hit blicker\\\")\\n # don't slice \\n # use origin ball vx to predict will hit blocker or not\\n # if will hit blicker let ball go reverse direction\\n y = abs((415 - 260) // ball_vy)\\n pred_ball_blocker = pred_ball_1P + ball_vx * y\\n bound = pred_ball_blocker // 200 # Determine if it is beyond the boundary\\n if (bound > 0): # pred > 200 # fix landing position\\n if (bound%2 == 0) : \\n pred_ball_blocker = pred_ball_blocker - bound*200 \\n else :\\n pred_ball_blocker = 200 - (pred_ball_blocker - 200*bound)\\n elif (bound < 0) : # pred < 0\\n if (bound%2 ==1) :\\n pred_ball_blocker = abs(pred_ball_blocker - (bound+1) *200)\\n else :\\n pred_ball_blocker = pred_ball_blocker + (abs(bound)*200)\\n\\n if pred_ball_blocker >= Pred.blocker_pred_x-10 and pred_ball_blocker < Pred.blocker_pred_x+40:\\n print(\\\"will hit blocker, hit reversed direction\\\")\\n if scene_info[\\\"ball_speed\\\"][0] > 0: return 2\\n else: return 1\\n else: \\n print(\\\"will not hit blicker, do nothing\\\")\\n return 0\\n else:\\n # slice\\n print(\\\"slice will not hit blocker\\\")\\n if scene_info[\\\"ball_speed\\\"][0] > 0: return 1\\n else: return 2\\n\\n elif scene_info[\\\"ball_speed\\\"][1] > 0 : # 球正在向下 # ball goes down\\n x = ( scene_info[\\\"platform_1P\\\"][1]-scene_info[\\\"ball\\\"][1] ) // scene_info[\\\"ball_speed\\\"][1] # 幾個frame以後會需要接 # x means how many frames before catch the ball\\n Pred.pred = scene_info[\\\"ball\\\"][0]+(scene_info[\\\"ball_speed\\\"][0]*x) # 預測最終位置 # pred means predict ball landing site \\n bound = Pred.pred // 200 # Determine if it is beyond the boundary\\n if (bound > 0): # pred > 200 # fix landing position\\n if (bound%2 == 0) : \\n Pred.pred = Pred.pred - bound*200 \\n else :\\n Pred.pred = 200 - (Pred.pred - 200*bound)\\n elif (bound < 0) : # pred < 0\\n if (bound%2 ==1) :\\n Pred.pred = abs(Pred.pred - (bound+1) *200)\\n else :\\n Pred.pred = Pred.pred + (abs(bound)*200)\\n return move_to(player = '1P',pred = Pred.pred)\\n \\n else : # 球正在向上 # ball goes up\\n return move_to(player = '1P',pred = 100)\\n\\n\\n\\n def ml_loop_for_2P(): # as same as 1P\\n if scene_info[\\\"ball_speed\\\"][1] > 0 : \\n return move_to(player = '2P',pred = 100)\\n else : \\n x = ( scene_info[\\\"platform_2P\\\"][1]+30-scene_info[\\\"ball\\\"][1] ) // scene_info[\\\"ball_speed\\\"][1] \\n pred = scene_info[\\\"ball\\\"][0]+(scene_info[\\\"ball_speed\\\"][0]*x) \\n bound = pred // 200 \\n if (bound > 0):\\n if (bound%2 == 0):\\n pred = pred - bound*200 \\n else :\\n pred = 200 - (pred - 200*bound)\\n elif (bound < 0) :\\n if bound%2 ==1:\\n pred = abs(pred - (bound+1) *200)\\n else :\\n pred = pred + (abs(bound)*200)\\n return move_to(player = '2P',pred = pred)\\n\\n # 2. Inform the game process that ml process is ready\\n comm.ml_ready()\\n\\n # 3. Start an endless loop\\n while True:\\n # 3.1. Receive the scene information sent from the game process\\n scene_info = comm.recv_from_game()\\n\\n # 3.2. If either of two sides wins the game, do the updating or\\n # resetting stuff and inform the game process when the ml process\\n # is ready.\\n if scene_info[\\\"status\\\"] != \\\"GAME_ALIVE\\\":\\n # Do some updating or resetting stuff\\n ball_served = False\\n\\n # 3.2.1 Inform the game process that\\n # the ml process is ready for the next round\\n comm.ml_ready()\\n continue\\n\\n # 3.3 Put the code here to handle the scene information\\n\\n # 3.4 Send the instruction for this frame to the game process\\n if not ball_served:\\n comm.send_to_game({\\\"frame\\\": scene_info[\\\"frame\\\"], \\\"command\\\": \\\"SERVE_TO_LEFT\\\"})\\n blocker_last_x = scene_info[\\\"blocker\\\"][0]\\n Pred.last_command = 0\\n ball_served = True\\n else:\\n if side == \\\"1P\\\":\\n Pred.blocker_vx = scene_info[\\\"blocker\\\"][0] - blocker_last_x\\n if scene_info[\\\"blocker\\\"][0] == 0: Pred.blocker_vx = 5\\n elif scene_info[\\\"blocker\\\"][0] == 170: Pred.blocker_vx = -5\\n command = ml_loop_for_1P()\\n blocker_last_x = scene_info[\\\"blocker\\\"][0]\\n Pred.last_command = command\\n else:\\n command = ml_loop_for_2P()\\n\\n if command == 0:\\n comm.send_to_game({\\\"frame\\\": scene_info[\\\"frame\\\"], \\\"command\\\": \\\"NONE\\\"})\\n elif command == 1:\\n comm.send_to_game({\\\"frame\\\": scene_info[\\\"frame\\\"], \\\"command\\\": \\\"MOVE_RIGHT\\\"})\\n else :\\n comm.send_to_game({\\\"frame\\\": scene_info[\\\"frame\\\"], \\\"command\\\": \\\"MOVE_LEFT\\\"})\",\n \"def handle_stop(_):\\n loop.force_unmute()\",\n \"def get_loop(self) -> bool:\\n return self._select_interface(self._rc_get_loop, self._http_get_loop)\",\n \"def test_sync_task_no_server(comm):\\n run_server, server_args, run_client, client_args = helper_config(comm, \\\"sync\\\")\\n client = run_client(**client_args)\\n try:\\n client.connect()\\n except Exception as exc: # pylint: disable=broad-except\\n assert False, f\\\"unexpected exception: {exc}\\\"\\n sleep(0.1)\\n if comm == \\\"udp\\\":\\n rr = client.read_coils(1, 1, slave=0x01)\\n assert isinstance(rr, ModbusIOException)\\n else:\\n with pytest.raises((asyncio.exceptions.TimeoutError, ConnectionException)):\\n client.read_coils(1, 1, slave=0x01)\\n client.close()\",\n \"def _loop_raw(raw):\\n raise NotImplemented\",\n \"def test_noFailure(self):\\n for i in range(10):\\n self.assertTrue(self.circuit_breaker.available())\",\n \"async def hold_loop(self):\\n pass\",\n \"def temp_mainloop(self, cycles_to_respond=1000):\\n\\n if self.com_port_select.count() > 0:\\n report = \\\"Begin measuring\\\"\\n self.go_button.setEnabled(False) # don't allow to create new threads\\n self.state_temp_loop(True)\\n self.append_msg_box(report)\\n\\n while self.temp_loop_actiator:\\n for num in range(self.com_port_select.count()):\\n # self.MainWindow_exec_thread(lambda: self.sample_devices(cycles_to_respond, num))\\n self.sample_devices(cycles_to_respond, num)\\n self.temp_repr.plot_tc_temp(self.temp_log)\\n timeo = float(self.timeout.text()) # timeout\\n sleep(timeo)\\n # -------- record data once in msg box --------\\n\\n self.go_button.setEnabled(True)\\n self.led_light.setPixmap(QtGui.QPixmap(img[\\\"red_led\\\"]))\\n else:\\n self.append_msg_box(\\\"No device is connected\\\")\",\n \"def testReset(self):\\n \\n clk = Signal(0)\\n rst = Signal(1)\\n clock_gen = ClkDriver(clk, period=4)\\n \\n out = Signal(intbv(0)[4:])\\n counter = Counter(out, clk, rst)\\n \\n def test():\\n for i in range(200):\\n # count up to 9 then reset\\n if int(out) == 9:\\n rst.next = 0\\n yield delay(1)\\n self.assertEqual(int(out), 0)\\n # turn off reset next time\\n else:\\n rst.next = 1\\n yield delay(1)\\n \\n check = test()\\n sim = Simulation(counter, clock_gen, check)\\n sim.run(400, quiet=1)\",\n \"def test_play_again_no(self):\\n # Prepare test\\n choice = random.choice(i18n.IN_NO_LIST)\\n self.console.out_farewell = MagicMock()\\n self.console.input = MagicMock(side_effect=[choice, StopIteration])\\n\\n # Run test\\n self.console.ask_play_again()\\n\\n # Evaluate test\\n calls = [call(FORMAT_NEWLINE_END(i18n.IN_MSG_REPLAY))]\\n self.console.input.assert_has_calls(calls)\\n self.console.out_farewell.assert_called_once()\",\n \"def test_for_loop(self, modes, parse_input_mocked_metadata):\\n bb = parse_input_mocked_metadata(\\n \\\"for int m in {}\\\\n\\\\tMeasureFock() | m\\\".format(modes)\\n )\\n assert np.all(\\n bb._forvar[\\\"m\\\"] == np.array(modes)\\n )\\n assert bb.operations == [\\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[0]]},\\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[1]]},\\n {'op': 'MeasureFock', 'args': [], 'kwargs': {}, 'modes': [modes[2]]}\\n ]\",\n \"def nanny(self): \\n while not self.started and not self.failed:\\n eventlet.sleep(.1)\\n return not self.failed\",\n \"def config_loop(self):\\n loop_label = ['Loop OFF', 'Loop ON']\\n group = self.make_ui_group(False, loop_label[self.loop])\\n orig_loop = self.loop\\n\\n while True:\\n action_left, action_right = (self.button_left.action(),\\n self.button_right.action())\\n if action_left is RichButton.HOLD:\\n return self.loop is not orig_loop, False # Resume config\\n if action_right is RichButton.HOLD:\\n return self.loop is not orig_loop, True # Resume paint\\n if RichButton.TAP in {action_left, action_right}:\\n self.loop = not self.loop\\n group.pop()\\n group.append(centered_label(loop_label[self.loop], 40, 3))\",\n \"def has_loop(self) -> bool:\\n try:\\n list(self)\\n return False\\n except ContainsLoopError:\\n return True\",\n \"def run(self):\\n self.cmdloop()\",\n \"def check_for_barrierless_reaction(self):\\n # Check for barrierless reaction leading to new graphs\\n if self.rc_opt_system_name not in self.systems: # Skip if already done\\n print(\\\"Running Reactive Complex Optimization\\\")\\n print(\\\"Settings:\\\")\\n print(self.settings[self.rc_opt_system_name], \\\"\\\\n\\\")\\n self.systems, success = self.observed_readuct_call(\\n 'run_opt_task', self.systems, [self.rc_key], **self.settings[self.rc_opt_system_name]\\n )\\n self.throw_if_not_successful(\\n success,\\n self.systems,\\n [self.rc_opt_system_name],\\n [],\\n \\\"Reactive complex optimization failed.\\\\n\\\",\\n )\\n _, rc_opt_graph, _, _, rc_opt_decision_lists = \\\\\\n self.get_graph_charges_multiplicities(self.rc_opt_system_name, sum(self.start_charges))\\n\\n if not masm.JsonSerialization.equal_molecules(self.start_graph, rc_opt_graph):\\n return rc_opt_graph, rc_opt_decision_lists\\n return None, None\",\n \"def ios_test_loop(self) -> Optional[pulumi.Input['IosTestLoopArgs']]:\\n return pulumi.get(self, \\\"ios_test_loop\\\")\",\n \"def block(self):\\n # I WILL RUN FOR EVER \\n # BUT WHY ARE YOU RUNNING ?\\n self.__loop.run_forever()\",\n \"def test_timeout_loop(self):\\n\\n self.assertIsNone(self.state.becomeCandidateTimeout)\\n # This should do nothing\\n self.state.cancelBecomeCandidateTimeout()\\n self.assertIsNone(self.state.becomeCandidateTimeout)\\n\\n results = self.state.begin()\\n\\n self.state.resetElectionTimeout()\\n self.assertTrue(self.state.electionTimeout > 0.150)\\n self.assertTrue(self.state.electionTimeout < 0.350)\\n self.assertTrue(isinstance(self.state.becomeCandidateTimeout,\\n base.DelayedCall))\",\n \"def test_readiness(self):\\n self.command.package = self.input_ovf\\n ready, reason = self.command.ready_to_run()\\n self.assertFalse(ready)\\n self.assertRegex(reason, \\\"No file information\\\")\\n self.assertRaises(InvalidInputError, self.command.run)\\n\\n self.command.file_path = \\\"input.vmdk\\\"\\n ready, reason = self.command.ready_to_run()\\n self.assertTrue(ready)\\n\\n self.command.file_path = None\\n self.command.file_id = \\\"file1\\\"\\n ready, reason = self.command.ready_to_run()\\n self.assertTrue(ready)\",\n \"def timeout_loop(self):\\r\\n\\r\\n while not done:\\r\\n\\r\\n if (softwareInterfaceTimeout != -1) and (interfaceNotUsed > softwareInterfaceTimeout):\\r\\n\\r\\n stop(False)\\r\\n\\r\\n \\r\\n\\r\\n time.sleep(MONITOR_INTERVAL/1000000.0)\\r\\n\\r\\n self.interfaceNotUsed = self.interfaceNotUsed + 1\",\n \"def loop_run(self):\\n super(HasLoops, self).loop_run()\\n for loop in getattr(self, \\\"_loops\\\", []):\\n loop.loop_remove_from_parent = weak_method(self.remove_loop)\\n loop.loop_run()\",\n \"def loop(self):\\n\\n print(self.id + \\\" needs an overridden loop method\\\")\",\n \"def test_shared_wires(self):\\n wires = range(2)\\n estimation_wires = range(1, 3)\\n\\n with pytest.raises(ValueError, match=\\\"No wires can be shared between the wires\\\"):\\n quantum_monte_carlo(\\n lambda: None, wires=wires, target_wire=0, estimation_wires=estimation_wires\\n )\",\n \"def test_selection():\\n pdb_inp = iotbx.pdb.input(source_info=None, lines=pdb_answer_0)\\n ncs_obj_phil = ncs.input(\\n hierarchy=pdb_inp.construct_hierarchy())\\n nrg = ncs_obj_phil.get_ncs_restraints_group_list()\\n\\n m1 = list(nrg[0].master_iselection)\\n c1 = list(nrg[0].copies[0].iselection)\\n c2 = list(nrg[0].copies[1].iselection)\\n\\n assert len(m1) == len(c1) # renumbering\\n assert m1 == [0, 1, 2, 3, 4, 5, 6] # 0, 1, X, 3, X, 5, X | 0, 1, 3\\n assert c1 == [7, 8, 9, 10, 11, 12, 13] # 7, 8, 9, X, X, 12, X | 4, 5, 7\\n assert c2 == [14, 15, 16, 17, 18, 19, 20] # 14, 15, X, 17, X, 19, X | 8, 9, 11\\n\\n selection1 = flex.size_t([0,1,5,3,100,101])\\n selection2 = flex.size_t([0,1,5,3,7,8,9,12,100,101])\\n selection3 = flex.size_t([0,1,5,3,7,8,9,12,14,15,19,17,100,101])\\n # gone iseqs for selection3: 2,4,6,10,11,13,16,18,20-99\\n\\n new_nrg = nrg.select(flex.bool(102, selection1))\\n # only atoms in master are selected\\n mt = list(new_nrg[0].master_iselection)\\n c1t = list(new_nrg[0].copies[0].iselection)\\n\\n assert mt == []\\n assert c1t == []\\n\\n # atoms selected in both master and copies\\n new_nrg = nrg.select(flex.bool(102, selection2))\\n # only atoms in master are selected\\n mt = list(new_nrg[0].master_iselection)\\n c1t = list(new_nrg[0].copies[0].iselection)\\n\\n assert mt == []\\n assert c1t == []\\n\\n new_nrg = nrg.select(flex.bool(102, selection3))\\n # only atoms in master are selected\\n mt = list(new_nrg[0].master_iselection)\\n c1t = list(new_nrg[0].copies[0].iselection)\\n c2t = list(new_nrg[0].copies[1].iselection)\\n\\n assert mt == [0, 1, 3], list(mt)\\n assert c1t == [4, 5, 7], list(c1t)\\n assert c2t == [8, 9, 11], list(c2t)\",\n \"def loop_run(self, loops):\\n self.loop_seek(self.num_loops + loops)\",\n \"def is_loop(*args):\\n return _ida_hexrays.is_loop(*args)\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def run_until_stop(self):\\n while self.commands[self.pointer] != END:\\n # Get the cmd\\n cmd = self.commands[self.pointer]\\n opcode = cmd % 100\\n modes = cmd // 100\\n \\n vals, locs, self.pointer = get_vals_and_locs(opcode, modes, self.pointer, self.commands)\\n \\n if opcode == ADD:\\n self.commands[locs[2]] = vals[0] + vals[1]\\n elif opcode == MUL:\\n self.commands[locs[2]] = vals[0] * vals[1]\\n elif opcode == INP:\\n if self.inputs:\\n self.commands[locs[0]] = self.inputs.pop(0)\\n else:\\n # Put the pointer back, so we run this opcode again\\n self.pointer -= 2\\n return False\\n elif opcode == OUT:\\n self.outputs.append(vals[0])\\n elif opcode == JIT:\\n if vals[0] != 0:\\n self.pointer = vals[1]\\n elif opcode == JIF:\\n if vals[0] == 0:\\n self.pointer = vals[1]\\n elif opcode == LT:\\n self.commands[locs[2]] = 1 if vals[0] < vals[1] else 0\\n elif opcode == EQ:\\n self.commands[locs[2]] = 1 if vals[0] == vals[1] else 0\\n else:\\n print(\\\"FAIL????\\\")\\n\\n return True\",\n \"def _while_loop(pd, nmax, max_loop, ncore, outfile):\\n \\n # make sure the random seed is different for every processor\\n random_number_seeds = [3456789, 7654321, 2435467, 8273645,\\n 1085712, 4154712, 1248291, 8415917,\\n 2345161, 5710916, 5718601, 7516234,\\n 9235161, 4917519, 1111245, 8167834] \\n \\n # get the processor ID (1 - Ncore) and convert to single integer\\n current = multiprocessing.current_process()\\n pid = current._identity\\n pid = pid[0]\\n \\n #\\n # choose a different seed for each processor from the list so each processor has\\n # a different randum number seed. Then, fiddle with each seed a little so \\n # the seeds aren't the same every time the code is run\\n seed = np.int(random_number_seeds[pid] * (np.random.rand()*(10.0 - 0.01) + 0.01))\\n \\n np.random.seed(seed)\\n \\n #print 'id and seed', pid, seed\\n \\n n_particles = 0\\n loop_counter = 0\\n fmin_scale = 1.0E-100 # -16 -> -32 -> -100\\n F_max = np.max(pd.DF.f) #; F_min = np.min(pd.DF.f);\\n F_min = np.min(pd.DF.f) * fmin_scale\\n # F_max = np.max(pd.DF.f[:-1])#; F_max = 1.0E-88\\n #print F_min, F_max\\n if pd.optimize:\\n relative_potential = pd._interpolate_relative_potential\\n else:\\n relative_potential = pd.DF.relative_potential\\n \\n \\n pos = np.zeros((nmax, 3))\\n vel = np.zeros((nmax, 3)) \\n \\n while (( n_particles < nmax) and (loop_counter < max_loop)):\\n \\n r = pd._choose_position()\\n Psi = relative_potential(r) \\n \\n v = pd._choose_velocity(r, Psi)\\n \\n E = Psi - 0.5 * v * v\\n \\n f_E = pd.DF.interpolate_f(E)\\n \\n logF = ( np.random.rand()*(np.log10(F_max) - np.log10(F_min)) + np.log10(F_min) )\\n \\n # if choosing random F in log F, might be good to do the comparison in logspace as well\\n #.... i.e log(F) <= log(f_E) \\n #\\n # 0 FOR F_E MEANS THAT E < E_min of the potential. THis happens when Psi - KE is smaller\\n # than the value of the potential at large_r... should this be considered unbound \\n # even though it isn't zero? Is this effectively zero? This has been adjusted in the velocity\\n # picking routine but needs verification to make sure it works.... but regardless, I doubt\\n # that this is the reason why the particles are failing for NFW but working for hernquist....\\n #\\n if np.abs(np.log10(f_E)) == np.inf:\\n keep_particle = False\\n _my_print('log value error... throwing out particle')\\n else:\\n keep_particle = (logF <= np.log10(f_E))\\n\\n \\n if keep_particle: \\n index = n_particles \\n \\n # \\n # need to sample in cosine theta NOT theta!!!!! WTF!!!!!\\n #\\n #\\n \\n theta = np.arccos( np.random.rand() * (2.0) - 1.0)\\n \\n # convert position to cartesian using random theta and phi\\n phi = np.random.rand() * 2.0 * np.pi\\n \\n x = np.sin(theta) * np.cos(phi)\\n y = np.sin(theta) * np.sin(phi)\\n z = np.cos(theta)\\n \\n pos[index] = r * np.array([x,y,z])\\n\\n # repeat for velocity using new random numbersw\\n theta = np.arccos( np.random.rand() * (2.0) - 1.0)\\n phi = np.random.rand() * 2.0 * np.pi\\n \\n vx = np.sin(theta) * np.cos(phi)\\n vy = np.sin(theta) * np.sin(phi)\\n vz = np.cos(theta)\\n \\n vel[index] = v * np.array([vx,vy,vz])\\n \\\"\\\"\\\" \\n #else: # do strict cartesian ... slower.... less attractive\\n # \\n # axis_list = [0, 1, 2]\\n # random.shuffle(axis_list)\\n \\n # #axis_index = np.random.randint(3)\\n # first_axis = axis_list[0]\\n #\\n # pos[index, first_axis] = np.random.rand() * (2.0*r) - r\\n #del axis_list[axis_index]\\n \\n #axis_index = np.random.randint(2)\\n # second_axis = axis_list[1]\\n \\n max_r = np.sqrt(r*r - pos[index,first_axis]**2)\\n \\n pos[index, second_axis] = np.random.rand()*(2.0 * max_r) - max_r\\n #del axis_list[axis_index]\\n \\n max_r = np.sqrt(r*r - pos[index,first_axis]**2 - pos[index,second_axis]**2)\\n \\n third_axis = axis_list[2]\\n pos[index, third_axis] = np.random.rand() * (2.0 * max_r) - max_r\\n \\n if np.sqrt(pos[index,0]**2 + pos[index,1]**2 + pos[index,2]**2) > r:\\n _my_print('R IS TOO LARGE')\\n \\n ###\\n axis_list = [0, 1, 2]\\n random.shuffle(axis_list)\\n \\n #axis_index = np.random.randint(3)\\n first_axis = axis_list[0]\\n \\n vel[index, first_axis] = np.random.rand() * (2.0*v) - v\\n #del axis_list[axis_index]\\n \\n #axis_index = np.random.randint(2)\\n second_axis = axis_list[1]\\n \\n max_v = np.sqrt(v*v - vel[index,first_axis]**2)\\n \\n vel[index, second_axis] = np.random.rand()*(2.0 * max_v) - max_v\\n #del axis_list[axis_index]\\n \\n max_v = np.sqrt(v*v - vel[index,first_axis]**2 - vel[index,second_axis]**2)\\n \\n third_axis = axis_list[2]\\n vel[index, third_axis] = np.random.rand() * (2.0 * max_v) - max_v \\n \\n \\n \\\"\\\"\\\"\\n n_particles = n_particles + 1\\n \\n if (loop_counter % 5000) == 0:\\n _my_print(\\\"Have %4i particles. On loop %6i\\\"%(n_particles, loop_counter))\\n loop_counter = loop_counter + 1\\n \\n # now write out to a temporary file\\n f = open(outfile + \\\"_%02i_\\\"%(pid) + \\\".temp\\\", 'w')\\n fmt = \\\"%12.12E %12.12E %12.12E %12.12E %12.12E %12.12E %12.12E\\\\n\\\"\\n \\n \\n for i in np.arange(nmax):\\n f.write(fmt%(pd.M_part, pos[i,0], pos[i,1], pos[i,2], \\n vel[i,0], vel[i,1], vel[i,2]))\\n \\n \\n f.close() \\n \\n return pos, vel\",\n \"def basic_noisy_selfloop_subsystem():\\n net = basic_noisy_selfloop_network()\\n state = basic_state()\\n return Subsystem(net, state)\",\n \"def takeControl(self):\\n mainloop()\",\n \"def takeControl(self):\\n mainloop()\",\n \"def while_loop(self):\\n if self._loop is None:\\n self._loop = self._while_loop()\\n return self._loop\\n return self._loop\",\n \"def running_loop(self, run_check_ms=None):\\r\\n if self.board.area.down_click_call is None:\\r\\n raise SelectError(\\\"board.area.down_click_call is not set\\\")\\r\\n if self.numgame is not None and self.ngame >= self.numgame:\\r\\n SlTrace.lg(f\\\"running_loop: ngame={self.ngame} > numgame {self.numgame}\\\")\\r\\n self.running = False\\r\\n self.run = False\\r\\n return\\r\\n \\r\\n self.running = True # Still in game\\r\\n self.run = True # progressing (not paused)\\r\\n self.first_time = True \\r\\n self.game_start_ts = SlTrace.getTs(6)\\r\\n self.game_control_updates()\\r\\n if run_check_ms is not None:\\r\\n self.run_check_ms = run_check_ms\\r\\n BlinkerMultiState.enable()\\r\\n \\r\\n while self.running:\\r\\n SlTrace.lg(\\\"running_loop\\\", \\\"running_loop\\\")\\r\\n self.mw.update()\\r\\n if ActiveCheck.not_active():\\r\\n break\\r\\n SlTrace.lg(\\\"running_loop active\\\", \\\"running_loop\\\")\\r\\n self.mw.update_idletasks()\\r\\n if self.event_check():\\r\\n continue # Gobble up pending events\\r\\n \\r\\n if (self.cmd_stream is not None\\r\\n and not self.cmd_stream.is_eof()):\\r\\n self.run_file()\\r\\n self.first_time = False # Assume file did that\\r\\n continue # Check if more\\r\\n else:\\r\\n if self.first_time:\\r\\n if not self.start_game():\\r\\n break\\r\\n self.first_time = False\\r\\n if not self.make_move():\\r\\n break \\r\\n \\r\\n SlTrace.lg(\\\"running_loop after loop\\\", \\\"running_loop\\\")\\r\\n BlinkerMultiState.disable()\\r\\n \\r\\n if self.on_end is not None:\\r\\n SlTrace.lg(\\\"running_loop doing on_end\\\", \\\"running_loop\\\")\\r\\n self.mw.after(0, self.on_end) # After run processing\\r\",\n \"def test_compute_partial_charges(self):\\n # TODO: Test only one molecule for speed?\\n # TODO: Do we need to deepcopy each molecule, or is setUp called separately for each test method?\\n import numpy as np\\n from simtk import unit\\n\\n # Do not modify original molecules.\\n molecules = copy.deepcopy(mini_drug_bank())\\n\\n # Test a single toolkit at a time\\n # Removed ['amber', 'amberff94'] from OE list, as those won't find the residue types they're expecting\\n toolkit_to_charge_method = {\\n OpenEyeToolkitWrapper: [\\n \\\"mmff\\\",\\n \\\"mmff94\\\",\\n \\\"am1bcc\\\",\\n \\\"am1bccnosymspt\\\",\\n \\\"am1bccelf10\\\",\\n ],\\n AmberToolsToolkitWrapper: [\\\"bcc\\\", \\\"gas\\\", \\\"mul\\\"],\\n }\\n\\n manual_skips = []\\n\\n manual_skips.append(\\n \\\"ZINC1564378\\\"\\n ) # Warning: OEMMFF94Charges: assigning OEMMFFAtomTypes failed on mol .\\n manual_skips.append(\\n \\\"ZINC00265517\\\"\\n ) # Warning: OEMMFF94Charges: assigning OEMMFFAtomTypes failed on mol .\\n\\n for toolkit in list(toolkit_to_charge_method.keys()):\\n toolkit_registry = ToolkitRegistry(toolkit_precedence=[toolkit])\\n for charge_model in toolkit_to_charge_method[toolkit]:\\n c = 0\\n for molecule in molecules[:1]: # Just test first molecule to save time\\n c += 1\\n if molecule.name in manual_skips: # Manual skips, hopefully rare\\n continue\\n molecule.compute_partial_charges(\\n charge_model=charge_model, toolkit_registry=toolkit_registry\\n )\\n charges1 = molecule._partial_charges\\n # Make sure everything isn't 0s\\n assert (abs(charges1 / unit.elementary_charge) > 0.01).any()\\n # Check total charge\\n charges_sum_unitless = charges1.sum() / unit.elementary_charge\\n # if abs(charges_sum_unitless - float(molecule.total_charge)) > 0.0001:\\n # print('c {} molecule {} charge_sum {} molecule.total_charge {}'.format(c, molecule.name,\\n # charges_sum_unitless,\\n # molecule.total_charge))\\n # assert_almost_equal(charges_sum_unitless, molecule.total_charge, decimal=4)\\n\\n # Call should be faster second time due to caching\\n # TODO: Implement caching\\n molecule.compute_partial_charges(\\n charge_model=charge_model, toolkit_registry=toolkit_registry\\n )\\n charges2 = molecule._partial_charges\\n assert np.allclose(charges1, charges2, atol=0.002)\",\n \"def main_loop(self):\\n center_point = self.mot.center_point\\n\\n screen_width = center_point[0] * 2\\n screen_height = center_point[1] * 2\\n\\n time.sleep(1)\\n pretty_progress_bar(\\n 3,\\n )\\n\\n # while int(time.time()) - start <= 10:\\n while not self.mot.abort:\\n object1_position = self.mot.position(self.color1)[0]\\n object2_velocity = self.mot.speed(self.color2)\\n # print(object2_velocity)\\n\\n self.compare(object1_position[0] < 0.25 * screen_width, 'left')\\n self.compare(object1_position[0] > 0.75 * screen_width, 'right')\\n self.compare(object1_position[1] < 0.25 * screen_height, 'jump')\\n self.burst_compare(object2_velocity > 150, 'fire')\\n\\n # print('KEYBOARD ABORT')\",\n \"async def loop(self, ctx: commands.Context) -> Optional[bool]:\\n\\n self.queue[ctx.guild.id].loop = (\\n Loops.LOOP if self.queue[ctx.guild.id].loop != Loops.LOOP else Loops.NO_LOOP\\n )\\n return self.queue[ctx.guild.id].loop == Loops.LOOP\",\n \"def test_select_sdf_mol2(self):\\n with mmtools.utils.temporary_directory() as tmp_dir:\\n yaml_content = \\\"\\\"\\\"\\n ---\\n options:\\n output_dir: {}\\n setup_dir: .\\n molecules:\\n sdf_0:\\n filepath: {}\\n antechamber: {{charge_method: bcc}}\\n leap: {{parameters: leaprc.gaff}}\\n select: 0\\n sdf_1:\\n filepath: {}\\n antechamber: {{charge_method: bcc}}\\n leap: {{parameters: leaprc.gaff}}\\n select: 1\\n mol2_0:\\n filepath: {}\\n antechamber: {{charge_method: bcc}}\\n leap: {{parameters: leaprc.gaff}}\\n select: 0\\n mol2_1:\\n filepath: {}\\n antechamber: {{charge_method: bcc}}\\n leap: {{parameters: leaprc.gaff}}\\n select: 1\\n \\\"\\\"\\\".format(tmp_dir, self.sdf_path, self.sdf_path, self.mol2_path, self.mol2_path)\\n yaml_content = textwrap.dedent(yaml_content)\\n exp_builder = ExperimentBuilder(yaml_content)\\n\\n for extension in ['sdf', 'mol2']:\\n multi_path = getattr(self, extension + '_path')\\n for model_idx in [0, 1]:\\n mol_id = extension + '_' + str(model_idx)\\n\\n # The molecule now is neither set up nor processed\\n is_setup, is_processed = exp_builder._db.is_molecule_setup(mol_id)\\n assert is_setup is False\\n assert is_processed is False\\n\\n exp_builder._db._setup_molecules(mol_id)\\n\\n # The setup of the molecule must isolate the frame in a single-frame PDB\\n single_mol_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\\n mol_id, mol_id + '.' + extension)\\n assert os.path.exists(os.path.join(single_mol_path))\\n assert os.path.getsize(os.path.join(single_mol_path)) > 0\\n if extension == 'mol2':\\n # OpenEye loses the resname when writing a mol2 file.\\n mol2_file = utils.Mol2File(single_mol_path)\\n assert len(list(mol2_file.resnames)) == 1\\n assert mol2_file.resname != '<0>'\\n\\n # sdf files must be converted to mol2 to be fed to antechamber\\n if extension == 'sdf':\\n single_mol_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\\n mol_id, mol_id + '.mol2')\\n assert os.path.exists(os.path.join(single_mol_path))\\n assert os.path.getsize(os.path.join(single_mol_path)) > 0\\n\\n # Check antechamber parametrization\\n single_mol_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\\n mol_id, mol_id + '.gaff.mol2')\\n assert os.path.exists(os.path.join(single_mol_path))\\n assert os.path.getsize(os.path.join(single_mol_path)) > 0\\n\\n # The positions must be approximately correct (antechamber move the molecule)\\n selected_oe_mol = utils.load_oe_molecules(single_mol_path, molecule_idx=0)\\n selected_pos = utils.get_oe_mol_positions(selected_oe_mol)\\n second_oe_mol = utils.load_oe_molecules(multi_path, molecule_idx=model_idx)\\n second_pos = utils.get_oe_mol_positions(second_oe_mol)\\n assert selected_oe_mol.NumConfs() == 1\\n assert np.allclose(selected_pos, second_pos, atol=1e-1)\\n\\n # The molecule now both set up and processed\\n is_setup, is_processed = exp_builder._db.is_molecule_setup(mol_id)\\n assert is_setup is True\\n assert is_processed is True\\n\\n # A new instance of ExperimentBuilder is able to resume with correct molecule\\n exp_builder = ExperimentBuilder(yaml_content)\\n is_setup, is_processed = exp_builder._db.is_molecule_setup(mol_id)\\n assert is_setup is True\\n assert is_processed is True\",\n \"async def _do_if_possible(self, coroutine: Awaitable[None]) -> None:\\n try:\\n await coroutine\\n except IncorrectStateException:\\n pass\",\n \"def run1():\\n #Reseting motors\\n ResetRobot.reset_wheel_motors()\\n ResetRobot.reset_attachment_motors()\\n CalibrateRobot.calibrate_gyro()\\n\\n #mission M01 and M02 - space travel and solar panel\\n M01_M02()\\n \\n #Mission M05- Extraction \\n M05_M14()\\n\\n #Back to base before Gerhard (Remove comment if necessary)\\n return_to_base1()\\n\\n # Must delete for competition.. This is to set up forklift to repeat run.\\n Robot.attachment_left.on_for_rotations(-100, 8) #Raises Forklift \"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7604223","0.73143464","0.73025155","0.7007973","0.6872689","0.6866279","0.6847027","0.6842967","0.64472896","0.64401734","0.640884","0.6354868","0.6325706","0.6155382","0.58229405","0.5801081","0.5721982","0.5642657","0.5607593","0.55608016","0.5551149","0.5468765","0.54497504","0.5395656","0.5359691","0.53441703","0.53175354","0.529146","0.529015","0.524933","0.5245704","0.5219824","0.5210233","0.51873183","0.5154336","0.5154214","0.5141546","0.51217514","0.50945526","0.50728786","0.50523144","0.5050906","0.5049756","0.5033937","0.5002918","0.4999775","0.49780378","0.4970924","0.49709025","0.4947381","0.49456465","0.49431938","0.49384576","0.49338943","0.4928376","0.4909999","0.49089763","0.49022332","0.48786455","0.4871272","0.48709127","0.48621902","0.48613873","0.48558372","0.48470107","0.48438486","0.4836962","0.4836237","0.4834882","0.4834814","0.483374","0.48303866","0.4826576","0.48209706","0.48045152","0.480415","0.47891298","0.47798395","0.47650814","0.47638032","0.47531557","0.47513658","0.47478655","0.47455302","0.4743561","0.47432432","0.4738676","0.4734667","0.47299698","0.47268432","0.4724911","0.4724911","0.47244102","0.47237927","0.47233725","0.47227773","0.4721484","0.4720915","0.4718059","0.47128537"],"string":"[\n \"0.7604223\",\n \"0.73143464\",\n \"0.73025155\",\n \"0.7007973\",\n \"0.6872689\",\n \"0.6866279\",\n \"0.6847027\",\n \"0.6842967\",\n \"0.64472896\",\n \"0.64401734\",\n \"0.640884\",\n \"0.6354868\",\n \"0.6325706\",\n \"0.6155382\",\n \"0.58229405\",\n \"0.5801081\",\n \"0.5721982\",\n \"0.5642657\",\n \"0.5607593\",\n \"0.55608016\",\n \"0.5551149\",\n \"0.5468765\",\n \"0.54497504\",\n \"0.5395656\",\n \"0.5359691\",\n \"0.53441703\",\n \"0.53175354\",\n \"0.529146\",\n \"0.529015\",\n \"0.524933\",\n \"0.5245704\",\n \"0.5219824\",\n \"0.5210233\",\n \"0.51873183\",\n \"0.5154336\",\n \"0.5154214\",\n \"0.5141546\",\n \"0.51217514\",\n \"0.50945526\",\n \"0.50728786\",\n \"0.50523144\",\n \"0.5050906\",\n \"0.5049756\",\n \"0.5033937\",\n \"0.5002918\",\n \"0.4999775\",\n \"0.49780378\",\n \"0.4970924\",\n \"0.49709025\",\n \"0.4947381\",\n \"0.49456465\",\n \"0.49431938\",\n \"0.49384576\",\n \"0.49338943\",\n \"0.4928376\",\n \"0.4909999\",\n \"0.49089763\",\n \"0.49022332\",\n \"0.48786455\",\n \"0.4871272\",\n \"0.48709127\",\n \"0.48621902\",\n \"0.48613873\",\n \"0.48558372\",\n \"0.48470107\",\n \"0.48438486\",\n \"0.4836962\",\n \"0.4836237\",\n \"0.4834882\",\n \"0.4834814\",\n \"0.483374\",\n \"0.48303866\",\n \"0.4826576\",\n \"0.48209706\",\n \"0.48045152\",\n \"0.480415\",\n \"0.47891298\",\n \"0.47798395\",\n \"0.47650814\",\n \"0.47638032\",\n \"0.47531557\",\n \"0.47513658\",\n \"0.47478655\",\n \"0.47455302\",\n \"0.4743561\",\n \"0.47432432\",\n \"0.4738676\",\n \"0.4734667\",\n \"0.47299698\",\n \"0.47268432\",\n \"0.4724911\",\n \"0.4724911\",\n \"0.47244102\",\n \"0.47237927\",\n \"0.47233725\",\n \"0.47227773\",\n \"0.4721484\",\n \"0.4720915\",\n \"0.4718059\",\n \"0.47128537\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8007402"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81493,"cells":{"query":{"kind":"string","value":"Test the proper operation of the residue loop with residue selection. The function tested is pipe_control.mol_res_spin.residue_loop()."},"document":{"kind":"string","value":"def test_residue_loop(self):\n\n # Loop over the residues.\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\n # Test the selection.\n self.assertEqual(res.num, 2)\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_residue_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for residue in mol_res_spin.residue_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_return_residue(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_residue(':1')\n res2 = mol_res_spin.return_residue(selection=':2')\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\n\n # Test the data of residue 1.\n self.assertEqual(res1.num, 1)\n self.assertEqual(res1.name, None)\n\n # Test the data of residue 2.\n self.assertEqual(res2.num, 2)\n self.assertEqual(res2.name, 'Glu')\n\n # Test the data of residue 4.\n self.assertEqual(res4.num, 4)\n self.assertEqual(res4.name, 'Pro')\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5.num, -5)\n self.assertEqual(res5.name, None)\n self.assertEqual(res5.spin[1].name, 'N5')","def test_spin_loop(self):\n\n # Spin data.\n select = [1, 0]\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, 'N5')\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 2)","def test_spin_loop_multiatom(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_molecule_loop_no_selection(self):\n\n # Molecule data.\n name = ['Ap4Aase', 'RNA']\n\n # Loop over the molecules.\n i = 0\n for mol in mol_res_spin.molecule_loop():\n # Test the molecule names.\n self.assertEqual(mol.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)","def test_molecule_loop(self):\n\n # Loop over the molecules.\n for mol in mol_res_spin.molecule_loop('#RNA'):\n # Test the molecule name.\n self.assertEqual(mol.name, 'RNA')\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)","def test_boolean_complex_selection(self):\n\n # The residue selection loop.\n sel = list(mol_res_spin.residue_loop(\"#Ap4Aase:4 & :Pro | #RNA\"))\n\n # Residue names and numbers.\n names = ['Pro', None, None]\n numbers = [4, -5, -4]\n\n # The residues.\n self.assertEqual(len(sel), 3)\n for i in range(3):\n self.assertEqual(sel[i].name, names[i])\n self.assertEqual(sel[i].num, numbers[i])","def test_boolean_and_selection(self):\n\n # The selection loop:\n sel = list(mol_res_spin.residue_loop(\"#Ap4Aase:4 & :Pro\"))\n\n # Test:\n self.assertEqual(len(sel), 1)\n for res in sel:\n self.assert_(res.name == \"Pro\" and res.num == 4)","def test_spin_loop_no_selection(self):\n\n # Spin data.\n select = [0, 1, 0, 0, 1, 1, 0, 1]\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 8)","def test_molecule_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for molecule in mol_res_spin.molecule_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_return_residue_pipe_fail(self):\n\n # Try to get a residue from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')","def test_spin_loop_wildcard(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N*'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_multi_molecules_cycle_one(self, multi_mol_system_irregular):\n sequence = \"A\"\n expected = [sequence] * (15 * 3)\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_irregular)\n found = self.sequence_from_system(multi_mol_system_irregular, \"test\")\n assert found == expected","def test_spin_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for spin in mol_res_spin.spin_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_multi_molecules_cycle(self, multi_mol_system_regular, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n expected = expected * 3\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_regular)\n found = self.sequence_from_system(multi_mol_system_regular, \"test\")\n assert found == expected","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def check_residue_callback(self):\n\n if not self.check_for_residue_existance():\n return\n\n self.listbox_current_designs.delete(0, END)\n self.current_residueFull = self.current_residue.get().split(\":\")\n\n if len(self.current_residueFull) > 1:\n self.listbox_restypes.delete(9)\n self.listbox_restypes.insert(9, \"Conserved\")\n else:\n res = self.current_residueFull[0] +\":\"+self.current_chain.get()\n #print res\n if not self.pose.total_residue():\n return\n\n resType = self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get()))\n try:\n resName = self.pose.residue(resType).name()\n except PyRosettaException:\n print \"Residue does not exist in PDB...\"\n return\n\n\n self.current_residue_name_full.set(resName)\n three_letter_name = resName.split(\"_\")[0]; #Fix for Rosetta designated chain endings, His_d\n self.current_residue_name.set(resName)\n\n #Fix for not having data for certain residue types:\n try:\n self.design_accessible_sa.set(self.residue_definitions.resinfo[three_letter_name][0])\n self.design_relative_mutability.set(self.residue_definitions.resinfo[three_letter_name][1])\n self.design_surface_probability.set(self.residue_definitions.resinfo[three_letter_name][2])\n except KeyError:\n print \"No Data for restype\"\n self.design_accessible_sa.set(\"\")\n self.design_relative_mutability.set(\"\")\n self.design_surface_probability.set(\"\")\n\n con = \"Conserved:\" +three_letter_name\n self.listbox_restypes.delete(9)\n self.listbox_restypes.insert(9, con)\n if self.DesignDic.has_key(res):\n for residues in self.DesignDic[res]:\n self.listbox_current_designs.insert(END, residues)","def test_return_single_residue_info(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_single_residue_info('1')\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\n res5 = mol_res_spin.return_single_residue_info('-5')\n\n # Test the data of residue 1.\n self.assertEqual(res1, (1, None))\n\n # Test the data of residue 2.\n self.assertEqual(res2, (2, 'Glu'))\n\n # Test the data of residue 4.\n self.assertEqual(res4, (4, 'Pro'))\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5, (-5, None))","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_single_molecules_cycle_one(self, single_mol_system):\n sequence = \"A\"\n expected = [sequence] * (5 * 3)\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def fixme_test_boolean_parenthesis_selection(self):\n\n # The selection loop:\n sel = list(mol_res_spin.residue_loop(\"(#Ap4Aase & :Pro) | (#RNA & :-4)\"))\n\n # Test:\n self.assertEqual(len(sel), 2)\n for res in sel:\n self.assert_(res.num in [-4, 4])","def test_wrong_length(multi_mol_system_irregular, sequence):\n processor = dssp.AnnotateResidues(\"test\", sequence)\n with pytest.raises(ValueError):\n processor.run_system(multi_mol_system_irregular)","def nextRes(self):\n\n self.current_residueFull = self.current_residue.get().split(\":\")\n if len(self.current_residueFull) < 2:\n res = int(self.current_residue.get())+1\n self.current_residue.set(res)\n self.check_residue_callback()\n else:\n print \"Please Change selection to get info...\"","def test_run_molecule(self, single_mol_system):\n sequence = \"ABCDE\"\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def ROOMSELECTION_LOOP():\n pass","def residue(self, resnum, chain_id, icode=' ', alt=' ', model_num = 0):\n res = self.struct[model_num][chain_id][(alt, resnum, icode)]\n res.chain_id = chain_id\n return res","def test_return_single_residue_info_fail(self):\n\n # Ask for a few residues.\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')","def assignResonanceResidue(resonance, residue):\n\n\n #print 'assignResonanceResidue', makeResonanceGuiName(resonance), residue.seqId\n if residue:\n # we could be setting the residue to None\n if not setAssignmentMolSystem(residue, resonance=resonance):\n return\n \n resonanceSet = resonance.resonanceSet\n if resonanceSet:\n assignNames = set()\n \n for atomSet in resonanceSet.atomSets:\n assignNames.add(atomSet.name)\n \n else:\n assignNames = set(resonance.assignNames)\n \n assignedResidue = getResonanceResidue(resonance)\n \n if assignNames and (assignedResidue is not residue):\n resonance.setAssignNames(assignNames)\n \n if residue:\n atomSets = []\n isotopeCode = resonance.isotopeCode\n if ('HA' in assignNames) and (residue.ccpCode == 'Gly'):\n assignNames.add('HA2')\n assignNames.add('HA3')\n \n for atom in residue.atoms:\n element = atom.chemAtom.elementSymbol\n \n if isotopeCode[-len(element):] != element:\n continue\n \n atomSet = atom.atomSet\n if atomSet:\n if atomSet.name in assignNames:\n if atomSet not in atomSets:\n atomSets.append(atomSet)\n \n if resonanceSet:\n resonanceSet.delete()\n \n if atomSets:\n # might not always find atom sets\n # e.g. if changing residue types\n assignAtomsToRes(atomSets,resonance,None)\n else:\n if resonanceSet:\n resonanceSet.delete()\n #updateResonanceAnnotation(resonance)\n\n if not resonance.resonanceGroup:\n nmrProject = resonance.nmrProject\n spinSystem = None\n molResidue = residue.molResidue\n ccpCode = molResidue.ccpCode\n molType = molResidue.molType\n spinSystems = nmrProject.findAllResonanceGroups(ccpCode=ccpCode,\n molType=molType)\n \n for extantSpinSystem in spinSystems:\n if extantSpinSystem.residue is residue:\n spinSystem = extantSpinSystem\n break\n \n if not spinSystem:\n spinSystem = nmrProject.newResonanceGroup()\n assignSpinSystemResidue(spinSystem,residue)\n \n if resonance not in spinSystem.resonances:\n spinSystem.addResonance(resonance)\n updateResonanceAnnotation(resonance)\n \n else:\n updateResonanceAnnotation(resonance)","def test_RUMI():\r\n\r\n start = 11051\r\n end = 11902\r\n read_poems(start, end)","def check_residue(self, chain_id, resid, resname):\n if resname in PTM_lookup.keys():\n return\n else:\n try:\n ref_resname = PTM_reverse_lookup[resname]\n except KeyError:\n # print \"skipping unrecognized residue\", resname\n return\n ptm_dict = PTM_lookup[ref_resname][resname]\n return (chain_id, resid, ref_resname, ptm_dict[\"goto_atom\"], ptm_dict[\"name\"])","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_selection():\n pdb_inp = iotbx.pdb.input(source_info=None, lines=pdb_answer_0)\n ncs_obj_phil = ncs.input(\n hierarchy=pdb_inp.construct_hierarchy())\n nrg = ncs_obj_phil.get_ncs_restraints_group_list()\n\n m1 = list(nrg[0].master_iselection)\n c1 = list(nrg[0].copies[0].iselection)\n c2 = list(nrg[0].copies[1].iselection)\n\n assert len(m1) == len(c1) # renumbering\n assert m1 == [0, 1, 2, 3, 4, 5, 6] # 0, 1, X, 3, X, 5, X | 0, 1, 3\n assert c1 == [7, 8, 9, 10, 11, 12, 13] # 7, 8, 9, X, X, 12, X | 4, 5, 7\n assert c2 == [14, 15, 16, 17, 18, 19, 20] # 14, 15, X, 17, X, 19, X | 8, 9, 11\n\n selection1 = flex.size_t([0,1,5,3,100,101])\n selection2 = flex.size_t([0,1,5,3,7,8,9,12,100,101])\n selection3 = flex.size_t([0,1,5,3,7,8,9,12,14,15,19,17,100,101])\n # gone iseqs for selection3: 2,4,6,10,11,13,16,18,20-99\n\n new_nrg = nrg.select(flex.bool(102, selection1))\n # only atoms in master are selected\n mt = list(new_nrg[0].master_iselection)\n c1t = list(new_nrg[0].copies[0].iselection)\n\n assert mt == []\n assert c1t == []\n\n # atoms selected in both master and copies\n new_nrg = nrg.select(flex.bool(102, selection2))\n # only atoms in master are selected\n mt = list(new_nrg[0].master_iselection)\n c1t = list(new_nrg[0].copies[0].iselection)\n\n assert mt == []\n assert c1t == []\n\n new_nrg = nrg.select(flex.bool(102, selection3))\n # only atoms in master are selected\n mt = list(new_nrg[0].master_iselection)\n c1t = list(new_nrg[0].copies[0].iselection)\n c2t = list(new_nrg[0].copies[1].iselection)\n\n assert mt == [0, 1, 3], list(mt)\n assert c1t == [4, 5, 7], list(c1t)\n assert c2t == [8, 9, 11], list(c2t)","def residues(ls):\n # List residue atom index to be restrained\n res_atom_set = set()\n\n # Dictionary of lists with the chain residues selected to be restrained\n # e.g. {chainA:[res1, res15], chainB:[res19, res17]}\n chain_dic = {'': []}\n\n # Fill out the chain dictionary\n i = 0\n while i < len(ls):\n if ls[i].isdigit():\n chain_dic[''].append(int(ls[i]))\n i += 1\n else:\n try:\n chain_dic[ls[i]].append(int(ls[i + 2]))\n except:\n chain_dic[ls[i]] = []\n chain_dic[ls[i]].append(int(ls[i + 2]))\n i += 3\n\n # Loop over the molecular system to select the atom indexes to be selected\n hv = oechem.OEHierView(system, oechem.OEAssumption_BondedResidue + oechem.OEAssumption_ResPerceived)\n for chain in hv.GetChains():\n chain_id = chain.GetChainID()\n if chain_id not in chain_dic:\n continue\n for frag in chain.GetFragments():\n for hres in frag.GetResidues():\n res_num = hres.GetOEResidue().GetResidueNumber()\n if res_num not in chain_dic[chain_id]:\n continue\n for oe_at in hres.GetAtoms():\n res_atom_set.add(oe_at.GetIdx())\n\n return res_atom_set","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_run_molecule_not_selected(self, single_mol_system):\n sequence = \"ABCDE\"\n processor = dssp.AnnotateResidues(\n \"test\", sequence, molecule_selector=lambda mol: False\n )\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert vermouth.utils.are_all_equal(found)\n assert found[0] is None","def test_single_molecule(self, single_mol_system, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def test_perceive_residues_natoms_mainchain_charged_glutamic_acid(\n self, strict_chirality\n ):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/MainChain_GLH.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def test_setup_explicit_solvation_system():\n with mmtools.utils.temporary_directory() as tmp_dir:\n yaml_script = get_template_script(tmp_dir)\n del yaml_script['experiments']\n exp_builder = ExperimentBuilder(yaml_script)\n output_dir = os.path.dirname(\n exp_builder._db.get_system('hydration-system')[0].position_path)\n\n # Test that output file exists and that it has correct components\n expected_resnames = {'solvent1': set(['TOL', 'WAT']), 'solvent2': set(['TOL'])}\n for phase in expected_resnames:\n found_resnames = set()\n pdb_path = os.path.join(output_dir, phase + '.pdb')\n prmtop_path = os.path.join(output_dir, phase + '.prmtop')\n inpcrd_path = os.path.join(output_dir, phase + '.inpcrd')\n\n with open(pdb_path, 'r') as f:\n for line in f:\n if len(line) > 10 and line[:5] != 'CRYST':\n found_resnames.add(line[17:20])\n\n assert os.path.exists(prmtop_path)\n assert os.path.exists(inpcrd_path)\n assert os.path.getsize(prmtop_path) > 0\n assert os.path.getsize(inpcrd_path) > 0\n assert found_resnames == expected_resnames[phase]","def test_run_loop_success(self):\n found = False\n pyint = Interpreter(limit=15)\n try:\n pyint.run(code=BF_CODE_LOOP_TWICE)\n except SystemExit: \n found = True\n self.assertFalse(found)","def test_return_molecule(self):\n\n # Ask for a few molecules.\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\n\n # Test the data of molecule 1.\n self.assertEqual(mol1.name, 'Ap4Aase')\n\n # Test the data of molecule 2.\n self.assertEqual(mol2.name, 'RNA')","def test_perceive_residues_natoms_mainchain_arginine(self, strict_chirality):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/MainChain_ARG.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def test_residues(parse_mmtf):\n parse_mmtf.assertEqual(len(parse_mmtf.mmcif_res), len(parse_mmtf.mmtf_res))\n for i, e in enumerate(parse_mmtf.mmcif_res):\n mmcif_r = parse_mmtf.mmcif_res[i]\n mmtf_r = parse_mmtf.mmtf_res[i]\n parse_mmtf.assertEqual(mmtf_r.level, mmcif_r.level)\n parse_mmtf.assertEqual(mmtf_r.disordered, mmcif_r.disordered)\n parse_mmtf.assertEqual(mmtf_r.resname, mmcif_r.resname)\n parse_mmtf.assertEqual(mmtf_r.segid, mmcif_r.segid)\n parse_mmtf.mmcif_atoms = [x for x in mmcif_r.get_atom()]\n parse_mmtf.mmtf_atoms = [x for x in mmtf_r.get_atom()]\n test_atoms(parse_mmtf=parse_mmtf)","def mutate_residue(pose, mutant_position, mutant_aa,\n pack_radius = 0.0, pack_scorefxn = '' ):\n #### a MutateResidue Mover exists similar to this except it does not pack\n #### the area around the mutant residue (no pack_radius feature)\n #mutator = MutateResidue(mutant_position, mutant_aa)\n #mutator.apply(test_pose)\n\n if pose.is_fullatom() == False:\n IOError( 'mutate_residue only works with fullatom poses' )\n\n\n # create a standard scorefxn by default\n if not pack_scorefxn:\n pack_scorefxn = rosetta.core.scoring.get_score_function()\n\n task = pyrosetta.standard_packer_task(pose)\n\n # the Vector1 of booleans (a specific object) is needed for specifying the\n # mutation, this demonstrates another more direct method of setting\n # PackerTask options for design\n aa_bool = rosetta.utility.vector1_bool()\n # PyRosetta uses several ways of tracking amino acids (ResidueTypes)\n # the numbers 1-20 correspond individually to the 20 proteogenic amino acids\n # aa_from_oneletter returns the integer representation of an amino acid\n # from its one letter code\n # convert mutant_aa to its integer representation\n mutant_aa = rosetta.core.chemical.aa_from_oneletter_code(mutant_aa)\n\n # mutation is performed by using a PackerTask with only the mutant\n # amino acid available during design\n # to do this, construct a Vector1 of booleans indicating which amino acid\n # (by its numerical designation, see above) to allow\n for i in range(1, 21):\n # in Python, logical expression are evaluated with priority, thus the\n # line below appends to aa_bool the truth (True or False) of the\n # statement i == mutant_aa\n aa_bool.append( i == int(mutant_aa) )\n\n # modify the mutating residue's assignment in the PackerTask using the\n # Vector1 of booleans across the proteogenic amino acids\n task.nonconst_residue_task(mutant_position\n ).restrict_absent_canonical_aas(aa_bool)\n\n # prevent residues from packing by setting the per-residue \"options\" of\n # the PackerTask\n restrict_non_nbrs_from_repacking(pose, mutant_position, task, pack_radius)\n\n # apply the mutation and pack nearby residues\n #print task\n packer = rosetta.protocols.simple_moves.PackRotamersMover(pack_scorefxn, task)\n packer.apply(pose)","def test_perceive_residues_natoms_mainchain_glutamic_acid(self, strict_chirality):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/MainChain_GLU.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def test_wrong_length_with_filter(multi_mol_system_irregular, sequence):\n # We exclude the second molecule. The filter excludes it based on the\n # number of nodes, which is 15 because it has 5 residues with 3 nodes\n # each.\n processor = dssp.AnnotateResidues(\n \"test\",\n sequence,\n molecule_selector=lambda mol: len(mol.nodes) != (5 * 3),\n )\n with pytest.raises(ValueError):\n processor.run_system(multi_mol_system_irregular)","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def test_modeller_mutations():\n mol_id = 'Abl'\n abl_path = examples_paths()['abl']\n with mmtools.utils.temporary_directory() as tmp_dir:\n # Safety check: protein must have WT residue: THR at residue 85 in chain A\n has_wt_residue = False\n with open(abl_path, 'r') as f:\n for line in f:\n if (line[:6] == 'ATOM ') and (line[21] == 'A') and (int(line[22:26]) == 85) and (line[17:20]=='THR'):\n has_wt_residue = True\n break\n assert has_wt_residue\n\n yaml_content = get_template_script(tmp_dir)\n exp_builder = ExperimentBuilder(yaml_content)\n output_dir = exp_builder._db.get_molecule_dir(mol_id)\n output_path = os.path.join(output_dir, 'Abl.pdb')\n\n # We haven't set the strip_protons options, so this shouldn't do anything\n exp_builder._db._setup_molecules(mol_id)\n assert not os.path.exists(output_path)\n\n # Calling modeller with WT creates a file (although the protein is not mutated).\n exp_builder._db.molecules[mol_id]['modeller'] = {\n 'apply_mutations': {\n 'chain_id': 'A',\n 'mutations': 'WT',\n }\n }\n setup_molecule_output_check(exp_builder._db, mol_id, output_path)\n os.remove(output_path) # Remove file for next check.\n\n\n # Reinitialize exp_builder\n exp_builder = ExperimentBuilder(yaml_content)\n\n # Now we set the strip_protons options and repeat for the mutant case\n exp_builder._db.molecules[mol_id]['modeller'] = {\n 'apply_mutations': {\n 'chain_id': 'A',\n 'mutations': 'T85I',\n }\n }\n setup_molecule_output_check(exp_builder._db, mol_id, output_path)\n\n # Safety check: protein must have mutated residue: ILE at residue 85 in chain A\n has_mut_residue = False\n with open(output_path, 'r') as f:\n for line in f:\n if (line[:6] == 'ATOM ') and (line[21] == 'A') and (int(line[22:26]) == 85) and (line[17:20]=='ILE'):\n has_mut_residue = True\n break\n assert has_mut_residue","def generate_quadratic_residues(bit_length, modulus, count):\n for count in range(0, count):\n yield generate_quadratic_residue(bit_length, modulus)","def test_recomb(self):\n sol1, sol2 = [0,0,0,0],[1,1,1,1]\n hot_regions = [0,0,0,1] ##NOTE: sum(hot_regions) shouls always be 1\n rec_events = 1\n sol = list(d.recombine(sol1,sol2,rec_events,hot_regions))\n print(f\"recomb sol: {sol}\")\n self.assertTrue( (sol == [0,0,0,1]) or (sol == [1,1,1,0]) )","def test_case_01_right_scalene(self):\n self.__assert_equals_test_case(self.yield_right_scalene_triangles(), 'Right Scalene Triangle')","def test_rb(self):\n\n # Load simulator\n backend = qiskit.Aer.get_backend('qasm_simulator')\n\n # Test up to 2 qubits\n nq_list = [1, 2]\n\n for nq in nq_list:\n\n print(\"Testing %d qubit RB\" % nq)\n\n for pattern_type in range(2):\n for multiplier_type in range(2):\n # See documentation of choose_pattern for the meaning of\n # the different pattern types\n\n rb_opts = {}\n rb_opts['nseeds'] = 3\n rb_opts['length_vector'] = [1, 3, 4, 7]\n rb_opts['rb_pattern'] = self.choose_pattern(\n pattern_type, nq)\n # if the pattern type is not relevant for nq\n if rb_opts['rb_pattern'] is None:\n continue\n rb_opts['length_multiplier'] = self.choose_multiplier(\n multiplier_type, len(rb_opts['rb_pattern']))\n\n # Generate the sequences\n try:\n rb_circs, _ = rb.randomized_benchmarking_seq(**rb_opts)\n except OSError:\n skip_msg = ('Skipping tests for %s qubits because '\n 'tables are missing' % str(nq))\n print(skip_msg)\n continue\n\n # Perform an ideal execution on the generated sequences\n # basis_gates = ['u1','u2','u3','cx'] # use U, CX for now\n # Shelly: changed format to fit qiskit current version\n basis_gates = 'u1, u2, u3, cx'\n shots = 100\n result = []\n for seed in range(rb_opts['nseeds']):\n result.append(\n qiskit.execute(rb_circs[seed], backend=backend,\n basis_gates=basis_gates,\n shots=shots).result())\n\n # Verify the generated sequences\n for seed in range(rb_opts['nseeds']):\n length_vec = rb_opts['length_vector']\n for circ_index, vec_len in enumerate(length_vec):\n\n self.assertEqual(\n rb_circs[seed][circ_index].name,\n 'rb_seed_%s_length_%s' % (\n str(seed), str(vec_len)),\n 'Error: incorrect circuit name')\n self.verify_circuit(rb_circs[seed][circ_index],\n nq, rb_opts,\n vec_len, result[seed], shots)\n\n self.assertEqual(circ_index, len(rb_circs),\n \"Error: additional circuits exist\")","def test_perceive_residues_natoms_t4(self, strict_chirality):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/T4-protein.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def test_rotamer_core_constraint(self):\n\n LIGAND_PATH = 'ligands/oleic_acid.pdb'\n ligand_path = get_data_file_path(LIGAND_PATH)\n\n # Test atom index constraint\n molecule = Molecule(ligand_path, core_constraints=[19, ],\n exclude_terminal_rotamers=False)\n\n rotamers_per_branch = molecule.rotamers\n\n assert len(rotamers_per_branch) == 1, \"Found an invalid number \" + \\\n \"of branches: {}\".format(len(rotamers_per_branch))\n\n atom_list = list()\n for rotamer in rotamers_per_branch[0]:\n atom_list.append(set([rotamer.index1, rotamer.index2]))\n\n EXPECTED_INDICES = [set([18, 19]), set([17, 18]), set([16, 17]),\n set([15, 16]), set([14, 15]), set([13, 14]),\n set([12, 13]), set([11, 12]), set([9, 10]),\n set([8, 9]), set([7, 8]), set([6, 7]),\n set([5, 6]), set([2, 5]), set([0, 2]),\n set([0, 1])]\n\n assert len(atom_list) == len(EXPECTED_INDICES), \"Unexpected \" + \\\n \"number of rotamers\"\n\n assert all(atom_pair in EXPECTED_INDICES for atom_pair in atom_list), \\\n \"Invalid rotamer library\"\n\n # Test PDB atom name constraint\n molecule = Molecule(ligand_path, core_constraints=[' C18', ],\n exclude_terminal_rotamers=False)\n\n rotamers_per_branch = molecule.rotamers\n\n assert len(rotamers_per_branch) == 1, \"Found an invalid number \" + \\\n \"of branches: {}\".format(len(rotamers_per_branch))\n\n atom_list = list()\n for rotamer in rotamers_per_branch[0]:\n atom_list.append(set([rotamer.index1, rotamer.index2]))\n\n EXPECTED_INDICES = [set([18, 19]), set([17, 18]), set([16, 17]),\n set([15, 16]), set([14, 15]), set([13, 14]),\n set([12, 13]), set([11, 12]), set([9, 10]),\n set([8, 9]), set([7, 8]), set([6, 7]),\n set([5, 6]), set([2, 5]), set([0, 2]),\n set([0, 1])]\n\n assert len(atom_list) == len(EXPECTED_INDICES), \"Unexpected \" + \\\n \"number of rotamers\"\n\n assert all(atom_pair in EXPECTED_INDICES for atom_pair in atom_list), \\\n \"Invalid rotamer library\"\n\n # Test core constraint with terminal exclusion\n molecule = Molecule(ligand_path, core_constraints=[' C18', ],\n exclude_terminal_rotamers=True)\n\n rotamers_per_branch = molecule.rotamers\n\n assert len(rotamers_per_branch) == 1, \"Found an invalid number \" + \\\n \"of branches: {}\".format(len(rotamers_per_branch))\n\n atom_list = list()\n for rotamer in rotamers_per_branch[0]:\n atom_list.append(set([rotamer.index1, rotamer.index2]))\n\n EXPECTED_INDICES = [set([17, 18]), set([16, 17]), set([15, 16]),\n set([14, 15]), set([13, 14]), set([12, 13]),\n set([11, 12]), set([9, 10]), set([8, 9]),\n set([7, 8]), set([6, 7]), set([5, 6]),\n set([2, 5]), set([0, 2]), set([0, 1])]\n\n assert len(atom_list) == len(EXPECTED_INDICES), \"Unexpected \" + \\\n \"number of rotamers\"\n\n assert all(atom_pair in EXPECTED_INDICES for atom_pair in atom_list), \\\n \"Invalid rotamer library\"\n\n # Test core constraint with a central core\n molecule = Molecule(ligand_path, core_constraints=[' C9 ', ],\n exclude_terminal_rotamers=True)\n\n rotamers_per_branch = molecule.rotamers\n\n assert len(rotamers_per_branch) == 2, \"Found an invalid number \" + \\\n \"of branches: {}\".format(len(rotamers_per_branch))\n\n atom_list_1 = list()\n atom_list_2 = list()\n rotamers = rotamers_per_branch[0]\n for rotamer in rotamers:\n atom_list_1.append(set([rotamer.index1, rotamer.index2]))\n\n rotamers = rotamers_per_branch[1]\n for rotamer in rotamers:\n atom_list_2.append(set([rotamer.index1, rotamer.index2]))\n\n EXPECTED_INDICES_1 = [set([9, 10]), set([8, 9]), set([7, 8]),\n set([6, 7]), set([5, 6]), set([2, 5]),\n set([0, 2]), set([0, 1])]\n\n EXPECTED_INDICES_2 = [set([12, 11]), set([12, 13]), set([13, 14]),\n set([14, 15]), set([15, 16]), set([16, 17]),\n set([17, 18])]\n\n where_1 = list()\n for atom_pair in atom_list_1:\n if atom_pair in EXPECTED_INDICES_1:\n where_1.append(1)\n elif atom_pair in EXPECTED_INDICES_2:\n where_1.append(2)\n else:\n where_1.append(0)\n\n where_2 = list()\n for atom_pair in atom_list_2:\n if atom_pair in EXPECTED_INDICES_1:\n where_2.append(1)\n elif atom_pair in EXPECTED_INDICES_2:\n where_2.append(2)\n else:\n where_2.append(0)\n\n assert (all(i == 1 for i in where_1)\n and all(i == 2 for i in where_2)) or \\\n (all(i == 2 for i in where_1)\n and all(i == 1 for i in where_2)), \"Invalid rotamer library \" + \\\n \"{}, {}\".format(where_1, where_2)\n\n assert (all(i == 1 for i in where_1)\n and all(i == 2 for i in where_2)\n and len(where_1) == len(EXPECTED_INDICES_1)\n and len(where_2) == len(EXPECTED_INDICES_2)) or \\\n (all(i == 2 for i in where_1)\n and all(i == 1 for i in where_2)\n and len(where_1) == len(EXPECTED_INDICES_2)\n and len(where_2) == len(EXPECTED_INDICES_1)), \"Unexpected \" + \\\n \"number of rotamers\"\n\n # Test core constraint with a multiple central core\n molecule = Molecule(ligand_path,\n core_constraints=[' C8 ', ' C9 ', ' C10'],\n exclude_terminal_rotamers=True)\n\n rotamers_per_branch = molecule.rotamers\n\n assert len(rotamers_per_branch) == 2, \"Found an invalid number \" + \\\n \"of branches: {}\".format(len(rotamers_per_branch))\n\n atom_list_1 = list()\n atom_list_2 = list()\n rotamers = rotamers_per_branch[0]\n for rotamer in rotamers:\n atom_list_1.append(set([rotamer.index1, rotamer.index2]))\n\n rotamers = rotamers_per_branch[1]\n for rotamer in rotamers:\n atom_list_2.append(set([rotamer.index1, rotamer.index2]))\n\n EXPECTED_INDICES_1 = [set([8, 9]), set([7, 8]), set([6, 7]),\n set([5, 6]), set([2, 5]), set([0, 2]),\n set([0, 1])]\n\n EXPECTED_INDICES_2 = [set([12, 11]), set([12, 13]), set([13, 14]),\n set([14, 15]), set([15, 16]), set([16, 17]),\n set([17, 18])]\n\n where_1 = list()\n for atom_pair in atom_list_1:\n if atom_pair in EXPECTED_INDICES_1:\n where_1.append(1)\n elif atom_pair in EXPECTED_INDICES_2:\n where_1.append(2)\n else:\n where_1.append(0)\n\n where_2 = list()\n for atom_pair in atom_list_2:\n if atom_pair in EXPECTED_INDICES_1:\n where_2.append(1)\n elif atom_pair in EXPECTED_INDICES_2:\n where_2.append(2)\n else:\n where_2.append(0)\n\n assert (all(i == 1 for i in where_1)\n and all(i == 2 for i in where_2)) or \\\n (all(i == 2 for i in where_1)\n and all(i == 1 for i in where_2)), \"Invalid rotamer library \" + \\\n \"{}, {}\".format(where_1, where_2)\n\n assert (all(i == 1 for i in where_1)\n and all(i == 2 for i in where_2)\n and len(where_1) == len(EXPECTED_INDICES_1)\n and len(where_2) == len(EXPECTED_INDICES_2)) or \\\n (all(i == 2 for i in where_1)\n and all(i == 1 for i in where_2)\n and len(where_1) == len(EXPECTED_INDICES_2)\n and len(where_2) == len(EXPECTED_INDICES_1)), \"Unexpected \" + \\\n \"number of rotamers\"","def check_for_residue_existance(self):\n if not self.pose.total_residue():\n print \"No pose Loaded.\"\n return False\n\n if not self.current_chain.get() or not self.current_residue.get():\n print \"Chain or residue not set\"\n return False\n\n current_region = self.current_residue.get().split(\":\")\n if len(current_region)>1:\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\n\n\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\n print \"Region not found in pose\"\n return False\n else:\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\n\n print \"Residue not found in pose\"\n return False\n\n #If everythig is good then:\n return True","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def test_perceive_residues_cyclic_peptide_chirality(self, strict_chirality):\n smiles = (\n \"[H]c1c(c(c(c(c1[H])[H])C([H])([H])[C@]2(C(=O)N([C@](C(=O)N([C@@](C(=O)N3[C@@](C(=O)N2[H])\"\n \"(C(C(C3([H])[H])([H])[H])([H])[H])[H])([H])C([H])([H])[H])[H])([H])C([H])([H])C4=C(N(c5c4c(c(c(c5[H])\"\n \"[H])[H])[H])[H])[H])[H])[H])[H])[H]\"\n )\n offmol = Molecule.from_smiles(smiles)\n # perceive residues\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n if strict_chirality:\n # Make sure it fails if strict_chirality=True\n with pytest.raises(AssertionError):\n assert counter == offmol.n_atoms\n else:\n assert counter == offmol.n_atoms","def getResAromaticVectors(residues):\n for res in residues.keys():\n rtype = res.split(\":\")[1][0:3] # A:GLY48 => GLY\n try:\n if rtype == \"PHE\" or rtype == \"TYR\":\n if len(residues[res]) == 6:\n pass\n else:\n if DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n elif rtype == \"TRP\":\n if len(residues[res]) >= 9:\n residues[res] = purgeTrp(residues[res])\n else:\n if DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n elif rtype == \"HIS\":\n if len(residues[res]) >= 5:\n residues[res] = purgeHis(residues[res])\n else:\n if DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n elif rtype == \"ARG\":\n residues[res] = purgeArg(residues[res])\n if not residues[res] and DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n elif rtype == \"DA\" or rtype == \"A\":\n if len(residues[res]) >= 10:\n residues[res] = purgeAdenine(residues[res])\n else:\n if DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n elif rtype == \"DC\" or rtype == \"C\":\n if len(residues[res]) >= 6:\n residues[res] = purgeAdenine(residues[res])\n else:\n if DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n elif rtype == \"DG\" or rtype == \"G\":\n if len(residues[res]) >= 10:\n residues[res] = purgeAdenine(residues[res])\n else:\n if DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n if residues[res]:\n residues[res] = atomsToVec(residues[res])\n else:\n del residues[res]\n except:\n if DEBUG: print \"Fatal error in processing residue [ %s ]\"% res\n del residues[res]\n return residues","def test_rescoring_option_problem(self):\r\n # get descriptor:\r\n problem_url_name = 'H1P1'\r\n self.define_option_problem(problem_url_name)\r\n location = InstructorTaskModuleTestCase.problem_location(problem_url_name)\r\n descriptor = self.module_store.get_item(location)\r\n\r\n # first store answers for each of the separate users:\r\n self.submit_student_answer('u1', problem_url_name, [OPTION_1, OPTION_1])\r\n self.submit_student_answer('u2', problem_url_name, [OPTION_1, OPTION_2])\r\n self.submit_student_answer('u3', problem_url_name, [OPTION_2, OPTION_1])\r\n self.submit_student_answer('u4', problem_url_name, [OPTION_2, OPTION_2])\r\n\r\n self.check_state('u1', descriptor, 2, 2, 1)\r\n self.check_state('u2', descriptor, 1, 2, 1)\r\n self.check_state('u3', descriptor, 1, 2, 1)\r\n self.check_state('u4', descriptor, 0, 2, 1)\r\n\r\n # update the data in the problem definition\r\n self.redefine_option_problem(problem_url_name)\r\n # confirm that simply rendering the problem again does not result in a change\r\n # in the grade:\r\n self.render_problem('u1', problem_url_name)\r\n self.check_state('u1', descriptor, 2, 2, 1)\r\n\r\n # rescore the problem for only one student -- only that student's grade should change:\r\n self.submit_rescore_one_student_answer('instructor', problem_url_name, User.objects.get(username='u1'))\r\n self.check_state('u1', descriptor, 0, 2, 1)\r\n self.check_state('u2', descriptor, 1, 2, 1)\r\n self.check_state('u3', descriptor, 1, 2, 1)\r\n self.check_state('u4', descriptor, 0, 2, 1)\r\n\r\n # rescore the problem for all students\r\n self.submit_rescore_all_student_answers('instructor', problem_url_name)\r\n self.check_state('u1', descriptor, 0, 2, 1)\r\n self.check_state('u2', descriptor, 1, 2, 1)\r\n self.check_state('u3', descriptor, 1, 2, 1)\r\n self.check_state('u4', descriptor, 2, 2, 1)","def test_check_for_max_rmsd():\n phil_groups = ncs_group_master_phil.fetch(\n iotbx.phil.parse(phil_str)).extract()\n pdb_inp = iotbx.pdb.input(source_info=None, lines=test_pdb_str_2)\n ncs_obj_phil = ncs.input(\n hierarchy=pdb_inp.construct_hierarchy(),\n ncs_phil_groups=phil_groups.ncs_group)\n nrgl = ncs_obj_phil.get_ncs_restraints_group_list()\n pdb_inp = iotbx.pdb.input(lines=test_pdb_str_2,source_info=None)\n ph = pdb_inp.construct_hierarchy()\n # passing test\n assert nrgl.check_for_max_rmsd(ph.atoms().extract_xyz() ,chain_max_rmsd=1)\n # make sure test fails when it suppose to\n nrgl[0].copies[1].t = matrix.col([100, -89.7668, 5.8996])\n assert not nrgl.check_for_max_rmsd(ph.atoms().extract_xyz(),chain_max_rmsd=1)","def isResidueAssigned(residue):\n\n for atom in residue.atoms:\n if atom.atomSet:\n if atom.atomSet.resonanceSets:\n return True\n \n return False","def test_run_a_scan_on_sdp_subarray_in_mid():","def test_from_pdb_t4_n_residues(self):\n expected_n_residues = 164 # noqa\n raise NotImplementedError","def mantra_simulation(lineup, module, mode='ST'):\n\n def try_optimal_solution(module, n_of_players_with_vote):\n\n \"\"\"\n If an optimal solution exists this function assign it to the\n variable \"final\" which is defined inside MANTRA_simulation but not\n globally. That's why we refers to it later by using \"nonlocal\".\n \"\"\"\n\n nonlocal all_lineups\n nonlocal final_field\n nonlocal malus\n\n # For each candidate\n for candidate in all_lineups:\n\n # We create the list where each player in the combination has only\n # 1 role\n candidates_single_role = all_lineups_single_role(candidate)\n\n # And test each of these combinations\n for new_cand in candidates_single_role:\n\n # If we find a solution we store the result\n if find_solution(new_cand, module, n_of_players_with_vote):\n final_field = new_cand\n break\n\n # And stop the iteration over the other condidates\n if final_field:\n malus = 0\n break\n\n def try_efficient_solution(module, n_of_players_with_vote):\n\n \"\"\"\n If an optimal solution is not found we look for an efficient one.\n In case an efficient solution exists we store the lineup and the\n module.\n \"\"\"\n\n modules_for_efficient_solution = copy.copy(all_modules)\n modules_for_efficient_solution.remove(module)\n\n nonlocal all_lineups\n nonlocal final_field\n nonlocal efficient_module\n nonlocal malus\n\n # Iterate over all the candidates\n for candidate in all_lineups:\n candidates_single_role = all_lineups_single_role(candidate)\n for new_cand in candidates_single_role:\n\n # And over all the modules\n for a_module in modules_for_efficient_solution:\n\n # If we find a solution we store the result\n if find_solution(new_cand, a_module,\n n_of_players_with_vote):\n final_field = new_cand\n efficient_module = a_module\n break\n\n # Stop the iteration over the other permutations\n if final_field:\n break\n\n # Stop the iteration over the other candidates\n if final_field:\n malus = 0\n break\n\n def try_adapted_solution(n_of_players_with_vote):\n\n \"\"\"\n If an efficient solution is not found we look for an adapted one.\n In case it exists we store the lineup, the module, the number of\n malus assigned and the other modules that are equally valid.\n \"\"\"\n\n modules_for_adapted_solution = copy.copy(all_modules)\n\n nonlocal all_lineups\n nonlocal final_field\n nonlocal adapted_module\n nonlocal malus\n\n # As for the efficient case we iterate over:\n\n # 1. All the candidates\n for candidate in all_lineups:\n candidates_single_role = all_lineups_single_role(candidate)\n\n # 2. Each candidate transformed in single role\n for new_cand in candidates_single_role:\n\n # 3. All the modules\n for a_module in modules_for_adapted_solution:\n\n n_malus = find_adapted_solution(\n new_cand, a_module, n_of_players_with_vote)\n\n # If a solution for this candidate with this module exists\n # AND n_malus is decreased, we store the number of malus,\n # the module and the lineup\n if n_malus and n_malus < malus:\n malus = n_malus\n adapted_module = a_module\n final_field = new_cand\n\n if malus == 1:\n # In this case we break the loop because 1 is the\n # minimum number of malus possible so we are not\n # interested in iterating over the remaining\n # candidates\n break\n\n if malus == 1:\n break\n if malus == 1:\n break\n\n def look_for_solution(module, n_of_players_with_vote):\n\n \"\"\"\n It sequentially applies the three functions to look for the right\n solution.\n \"\"\"\n\n try_optimal_solution(module, n_of_players_with_vote)\n if not final_field:\n try_efficient_solution(module, n_of_players_with_vote)\n if not final_field:\n try_adapted_solution(n_of_players_with_vote)\n\n def solve_gkeeper():\n\n \"\"\"\n Goal keeper substitution has to be the first thing to solve, if\n needed. Here we modify field, bench and n_subst depending on whether\n the gkeepers has vote or not.\n \"\"\"\n\n nonlocal field\n nonlocal bench\n nonlocal n_subst\n\n # If the goal keeper n the field received a vote we delete all the\n # remaining goal keepers from the bench\n if find_gkeeper(field):\n bench = delete_gkeeper(bench)\n\n # If the gkeeper in the field has no vote but the there is at least one\n # gkeeper in the bench with vote we make the substitution and delete\n # all the remaining gkeepers from the lineup, if there is any. We\n # finally decrease the n_subst\n elif not find_gkeeper(field) and find_gkeeper(bench):\n gkeeper = find_gkeeper(bench)\n field.insert(0, gkeeper)\n bench = delete_gkeeper(bench)\n n_subst -= 1\n\n # If there is no gkeeper with vote neither in the field nor in the\n # bench than we just decrease the n_subst\n elif not find_gkeeper(field) and not find_gkeeper(bench):\n n_subst -= 1\n\n def calculation(a_number):\n\n \"\"\"\n This is the function that is recursively applied to find the correct\n lineup. The input 'a_number' is an integer which represents the\n number of players (gkeeper excluded) who will partecipate in the\n lineup calculation. In case the algorithm does not find any solution\n after the first iteration it repeats the process considering 1\n substitution and 1 player less.\n \"\"\"\n\n nonlocal field\n nonlocal bench\n nonlocal module\n nonlocal n_subst\n nonlocal all_lineups\n\n all_lineups = valid_lineups(field, bench, n_subst)\n look_for_solution(module, a_number)\n\n if not final_field:\n n_subst -= 1\n return calculation(a_number-1)\n\n clean_lineup = [(player[0], modify_player_name(player[1]), player[2])\n for player in lineup]\n\n # Select the players with vote and store the number of substitutions needed\n if mode == 'FG':\n field, bench = players_with_vote(clean_lineup, 'FG')\n else:\n field, bench = players_with_vote(clean_lineup)\n\n n_subst = 11 - len(field)\n\n # In case no substitutions are needed, no calculation is started. In this\n # case malus can only be due to errors coming from the fantaplayers when\n # creating the lineup\n if not n_subst:\n malus = 0\n ref_roles = schemes[module]\n field[0] = (field[0][0], field[0][1], 'Por')\n\n for x in range(10):\n roles_available = ref_roles[x].split('/')\n roles_player = field[x + 1][2]\n roles_shared = list(set(roles_available).intersection(\n roles_player))\n if roles_shared:\n field[x + 1] = (field[x + 1][0], field[x + 1][1],\n roles_shared[0])\n else:\n malus += 1\n for role in roles_player:\n temp_roles = malus_roles[role]\n temp_roles = [role.split('/') for role in temp_roles]\n temp_roles = [single_role for element in temp_roles for\n single_role in element]\n temp_roles = ['W' if role in ('W1', 'W2') else role for\n role in temp_roles]\n temp_roles = list(set(temp_roles))\n roles_shared = list(set(roles_available).intersection(\n temp_roles))\n field[x + 1] = (field[x + 1][0], field[x + 1][1],\n roles_shared[0])\n break\n\n return field, bench, malus\n\n # Initialize all the parameters. We chose 10 for malus just because it is\n # a number high enough and we look for the solution with the lower number\n # of malus\n final_field = [] # The final lineup\n efficient_module = 0 # Valid module in case of eff solution\n adapted_module = 0 # Valid module in case of adp solution\n malus = 10 # Number of malus assigned\n magic_number = 10 # N. of players considered in the lineup\n all_lineups = 0 # All candidates\n\n # We need all the modules to be able to iterate over them in case an\n # efficient or adapted solution is needed. We also remove the module chosen\n # by the fantaplayer and then insert it as first element. In this way, this\n # module will be the first to be checked\n all_modules = ['343', '3412', '3421', '352', '442', '433',\n '4312', '4321', '4231', '4411', '4222']\n all_modules.remove(module)\n all_modules.insert(0, module)\n\n # Set the right magic_number value if n_subst > 3\n if n_subst > 3:\n magic_number = 13 - n_subst\n n_subst = 3\n\n # Handle the goal keeper issue\n solve_gkeeper()\n if find_gkeeper(field):\n gkeeper = field[0]\n field.remove(gkeeper)\n else:\n gkeeper = 0\n\n calculation(magic_number)\n\n if gkeeper:\n gkeeper = (gkeeper[0], gkeeper[1], gkeeper[2][0])\n final_field.insert(0, gkeeper)\n\n # Create the bench\n field_names = [player[1] for player in final_field]\n final_bench = [player for player in clean_lineup[11:] if player[1] not in\n field_names]\n\n return final_field, final_bench, malus, efficient_module, adapted_module","def test_run_loop_exc(self):\n with self.assertRaises(ExecutionException):\n pyint = Interpreter(limit=1)\n pyint.run(code=BF_CODE_LOOP_TWICE)","def test_assign_resources_to_tmc_subarray_in_mid():","def select_perturbation_residues(molecule):\n # Validte the length of the molecule\n validate_molecule_length(molecule)\n # Set the maximum allowed perturbation numbers\n maxNum = 3\n # Select a random number between 1 and maxNum\n ranNum = random.randint(1, maxNum)\n # Define the perturbed list to hold the perturbed residue name\n perturbed = []\n count = 0\n while count < ranNum:\n # Random select a residue number in the molecule \n index = random.randint(1, len(molecule))\n perturbed.append([molecule.name, index, molecule[index].name])\n count += 1\n\n return perturbed","def test_perceive_residues_sorting(self, strict_chirality):\n molecule = Molecule.from_file(get_data_file_path(\"proteins/ace-a10-nme.sdf\"))\n\n molecule.perceive_residues(strict_chirality=strict_chirality)\n\n for index, residue in enumerate(molecule.residues):\n found = residue.residue_number\n expected = str(index + 1)\n\n assert isinstance(found, str)\n assert found == expected","def algorithm_loop(self):","def get_residues_sequence (structure):\n list_fastas=[]\n residues_dict = {'CYS': 'C', 'ASP': 'D', 'SER': 'S', 'GLN': 'Q', 'LYS': 'K',\n 'ILE': 'I', 'PRO': 'P', 'THR': 'T', 'PHE': 'F', 'ASN': 'N',\n 'GLY': 'G', 'HIS': 'H', 'LEU': 'L', 'ARG': 'R', 'TRP': 'W',\n 'ALA': 'A', 'VAL': 'V', 'GLU': 'E', 'TYR': 'Y', 'MET': 'M'}\n\n rna_dict={ ' G': 'G', ' C': 'C', ' A': 'A', ' T': 'T', ' U': 'U'}\n dna_dict={ ' DG': 'G', ' DC': 'C', ' DA': 'A', ' DT': 'T', ' DU': 'U'}\n\n for model in structure:\n for chain in model:\n string=\"\"\n for residue in chain:\n for atom in residue:\n if atom.id == \"CA\":\n if residue.resname == 'UNK':\n continue \n else:\n if residue.resname not in residues_dict:\n raise NoExistsResidue(residue.resname) \n residue_name = residues_dict[residue.resname] \n string = string + residue_name\n elif atom.id == \"P\":\n if residue.resname.startswith(\" D\"):\n residue_name= dna_dict[residue.resname]\n if residue.resname not in dna_dict:\n raise NoExistsDesoxiribonucleotide(residue.resname)\n else:\n residue_name= rna_dict[residue.resname]\n if residue.resname not in rna_dict:\n raise NoExistsRibonucleotide(residue.resname)\n string= string + residue_name\n if string != \"\":\n list_fastas.append(string)\n return list_fastas","def test_return_molecule_pipe_fail(self):\n\n # Try to get a molecule from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')","def test_select_pdb_conformation(self):\n with mmtools.utils.temporary_directory() as tmp_dir:\n yaml_content = \"\"\"\n ---\n options:\n output_dir: {}\n setup_dir: .\n molecules:\n selected:\n filepath: {}\n leap: {{parameters: oldff/leaprc.ff14SB}}\n select: 1\n \"\"\".format(tmp_dir, self.pdb_path)\n yaml_content = textwrap.dedent(yaml_content)\n exp_builder = ExperimentBuilder(yaml_content)\n\n # The molecule now is neither set up nor processed\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\n assert is_setup is False\n assert is_processed is False\n\n # The setup of the molecule must isolate the frame in a single-frame PDB\n exp_builder._db._setup_molecules('selected')\n selected_pdb_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\n 'selected', 'selected.pdb')\n assert os.path.exists(os.path.join(selected_pdb_path))\n assert os.path.getsize(os.path.join(selected_pdb_path)) > 0\n\n # The positions must be the ones of the second frame\n selected_pdb = PDBFile(selected_pdb_path)\n selected_pos = selected_pdb.getPositions(asNumpy=True)\n second_pos = PDBFile(self.pdb_path).getPositions(asNumpy=True, frame=1)\n assert selected_pdb.getNumFrames() == 1\n assert (selected_pos == second_pos).all()\n\n # The description of the molecule is now updated\n assert os.path.normpath(exp_builder._db.molecules['selected']['filepath']) == selected_pdb_path\n\n # The molecule now both set up and processed\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\n assert is_setup is True\n assert is_processed is True\n\n # A new instance of ExperimentBuilder is able to resume with correct molecule\n exp_builder = ExperimentBuilder(yaml_content)\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\n assert is_setup is True\n assert is_processed is True","def initResonance(resonance, doMerge=True):\n from ccpnmr.analysis.core.MoleculeBasic import DEFAULT_ISOTOPES\n \n if resonance.isDeleted:\n return\n \n #print 'initResonance', makeResonanceGuiName(resonance)\n resonanceSet = resonance.resonanceSet\n \n if resonance.name == 'r%d' % resonance.serial:\n resonance.setName(None)\n \n if resonanceSet:\n atomSets = tuple(resonanceSet.atomSets)\n atom = atomSets[0].findFirstAtom()\n element = atom.chemAtom.elementSymbol\n if resonance.isotopeCode[-len(element):] != element:\n msg = 'Resonance %d isotope-assignment mismatch: Resetting isotope' \n print msg % resonance.serial\n \n resonance.isotopeCode = DEFAULT_ISOTOPES.get(element, 'unknown')\n getBoundResonances(resonance, recalculate=True, contribs=None) \n \n spinSystem = findSpinSystem(resonance)\n if spinSystem:\n if resonance.resonanceGroup: # same as the spin system\n residue = atom.residue\n \n if spinSystem.residue is not residue:\n #assignSpinSystemResidue(spinSystem,residue)\n \n if doMerge:\n ccpCode = residue.molResidue.ccpCode\n spinSystems = list(resonance.nmrProject.findAllResonanceGroups(residue=residue))\n N = len(spinSystems)\n msg = 'There are %d separate %d%s spin systems. Merge together?'\n if (N > 1) and showOkCancel('Confirm', msg % (N,residue.seqCode,ccpCode)):\n assignSpinSystemResidue(spinSystem,residue) \n \n for spinSystem1 in spinSystems[1:]:\n mergeSpinSystems(spinSystem1,spinSystems[0])\n \n else:\n assignSpinSystemResidue(spinSystem,residue) \n \n else:\n assignSpinSystemResidue(spinSystem,residue) \n \n else:\n addSpinSystemResonance(spinSystem, resonance)\n\n assignResonanceType(resonance, atomSets)\n \n else:\n updateResonanceAnnotation(resonance)\n\n if not resonance.shifts:\n if resonance.peakDimContribs:\n for contrib in resonance.peakDimContribs:\n peakDim = contrib.peakDim\n experiment = peakDim.peak.peakList.dataSource.experiment\n \n if experiment.shiftList is None:\n shiftList = resonance.nmrProject.findFirstMeasurementList(className='ShiftList')\n if shiftList is None:\n shiftList = resonance.nmrProject.newShiftList(unit='ppm')\n experiment.setShiftList( shiftList )\n \n updateResonShift(resonance,peakDim)","def testrescorr():\n tau = np.zeros((2,50))\n tau[0,25] = 2\n tau[1,23] = 3\n tau2 = spec_utils.res_corr(tau, 2, 8)\n #Check flux conserved\n assert np.abs(np.sum(tau2[0,:])/ np.sum(tau[0,:]) -1) < 1e-6\n assert np.abs(np.sum(tau2[1,:])/ np.sum(tau[1,:]) -1) < 1e-6\n #Check expanded by expected amount\n for i in (0,1):\n assert np.size(np.where(tau2[i,:]> 0)) == 15","def test_rescore_unmask(self):\r\n module = CapaFactory.create(xml=self.common_shuffle_xml)\r\n get_request_dict = {CapaFactory.input_key(): 'mask_0'}\r\n module.check_problem(get_request_dict)\r\n # On rescore, state/student_answers should use unmasked names\r\n with patch.object(module.runtime, 'track_function') as mock_track_function:\r\n module.rescore_problem()\r\n mock_call = mock_track_function.mock_calls[0]\r\n event_info = mock_call[1][1]\r\n self.assertEquals(mock_call[1][0], 'problem_rescore')\r\n self.assertEquals(event_info['state']['student_answers'][CapaFactory.answer_key()], 'choice_2')\r\n self.assertIsNotNone(event_info['permutation'][CapaFactory.answer_key()])","def test_terminal_rotamer_filtering(self):\n LIGAND_PATH = 'ligands/oleic_acid.pdb'\n\n ligand_path = get_data_file_path(LIGAND_PATH)\n molecule = Molecule(ligand_path, exclude_terminal_rotamers=True)\n\n rotamers_per_branch = molecule.rotamers\n\n assert len(rotamers_per_branch) == 2, \"Found an invalid number \" + \\\n \"of branches: {}\".format(len(rotamers_per_branch))\n\n atom_list_1 = list()\n atom_list_2 = list()\n rotamers = rotamers_per_branch[0]\n for rotamer in rotamers:\n atom_list_1.append(set([rotamer.index1, rotamer.index2]))\n\n rotamers = rotamers_per_branch[1]\n for rotamer in rotamers:\n atom_list_2.append(set([rotamer.index1, rotamer.index2]))\n\n EXPECTED_INDICES_1 = [set([9, 10]), set([8, 9]), set([7, 8]),\n set([6, 7]), set([5, 6]), set([2, 5]),\n set([0, 2]), set([0, 1])]\n\n EXPECTED_INDICES_2 = [set([12, 11]), set([12, 13]), set([13, 14]),\n set([14, 15]), set([15, 16]), set([16, 17]),\n set([17, 18])]\n\n where_1 = list()\n for atom_pair in atom_list_1:\n if atom_pair in EXPECTED_INDICES_1:\n where_1.append(1)\n elif atom_pair in EXPECTED_INDICES_2:\n where_1.append(2)\n else:\n where_1.append(0)\n\n where_2 = list()\n for atom_pair in atom_list_2:\n if atom_pair in EXPECTED_INDICES_1:\n where_2.append(1)\n elif atom_pair in EXPECTED_INDICES_2:\n where_2.append(2)\n else:\n where_2.append(0)\n\n assert (all(i == 1 for i in where_1)\n and all(i == 2 for i in where_2)) or \\\n (all(i == 2 for i in where_1)\n and all(i == 1 for i in where_2)), \"Invalid rotamer library \" + \\\n \"{}, {}\".format(where_1, where_2)\n\n assert (all(i == 1 for i in where_1)\n and all(i == 2 for i in where_2)\n and len(where_1) == len(EXPECTED_INDICES_1)\n and len(where_2) == len(EXPECTED_INDICES_2)) or \\\n (all(i == 2 for i in where_1)\n and all(i == 1 for i in where_2)\n and len(where_1) == len(EXPECTED_INDICES_2)\n and len(where_2) == len(EXPECTED_INDICES_1)), \"Unexpected \" + \\\n \"number of rotamers\"","def test_find_surface_residues():\n atom_dict_0 = find_surface_residues(protein, max_dist=0, scaling=1)\n atom_dict_1 = find_surface_residues(protein, max_dist=2, scaling=1)\n atom_dict_2 = find_surface_residues(protein, max_dist=3, scaling=1)\n atom_dict_3 = find_surface_residues(protein, max_dist=None, scaling=1)\n atom_dict_4 = find_surface_residues(protein, max_dist=None, scaling=2)\n\n assert atom_dict_0.size == 0\n assert len(atom_dict_1) > len(atom_dict_0), ('Increasing max_dist should '\n 'result in more/equal number '\n 'of atoms found')\n\n assert len(atom_dict_2) >= len(atom_dict_1), ('Increasing max_dist should '\n 'result in more/equal number '\n 'of atoms found')\n assert_array_equal(np.intersect1d(atom_dict_1['id'], atom_dict_2['id']), atom_dict_1['id'])\n\n if oddt.toolkit.backend == 'ob':\n ref_len_1 = 762\n ref_len_2 = 968\n ref_len_3 = 654\n ref_len_4 = 379\n elif oddt.toolkit.backend == 'rdk' and oddt.toolkits.rdk.__version__ >= '2019.09':\n ref_len_1 = 762\n ref_len_2 = 968\n ref_len_3 = 664\n ref_len_4 = 393\n else:\n ref_len_1 = 759\n ref_len_2 = 966\n ref_len_3 = 735\n ref_len_4 = 489\n\n assert len(atom_dict_1) == ref_len_1\n assert len(atom_dict_2) == ref_len_2\n assert len(atom_dict_3) == ref_len_3\n assert len(atom_dict_4) == ref_len_4\n\n # Adding hydrogen atoms should have no effect on the result\n protein.addh()\n atom_dict_addh = find_surface_residues(protein, max_dist=2, scaling=1)\n assert_array_equal(atom_dict_addh['id'], atom_dict_1['id'])\n\n with pytest.raises(TypeError):\n find_surface_residues(molecule=1)\n with pytest.raises(ValueError):\n find_surface_residues(molecule=protein, max_dist='a')\n with pytest.raises(ValueError):\n find_surface_residues(molecule=protein, max_dist=[1, 1, 1])","def test_single_segment(self):\n\n recombination = MagicMock()\n recombination.bases = np.array([5, 10, 15, 20], dtype = np.uint32)\n recombination.cm = np.array([0.00000, 0.001, 0.00125, 0.00215])\n recombination.rates = np.array([0.0002000000, 0.0000500000,\n 0.0001800000, 0.0002000000])\n\n starts = [0]\n stops = [5]\n lengths = cm_lengths(starts, stops, recombination)\n expect = np.array([0.000], dtype = np.float64)\n np.testing.assert_almost_equal(lengths, expect)\n\n starts = [5]\n stops = [10]\n lengths = cm_lengths(starts, stops, recombination)\n expect = np.array([0.001], dtype = np.float64)\n np.testing.assert_almost_equal(lengths, expect)\n\n starts = [10]\n stops = [15]\n lengths = cm_lengths(starts, stops, recombination)\n expect = np.array([0.00025], dtype = np.float64)\n np.testing.assert_almost_equal(lengths, expect)\n\n starts = [15]\n stops = [20]\n lengths = cm_lengths(starts, stops, recombination)\n expect = np.array([0.0009], dtype = np.float64)\n np.testing.assert_almost_equal(lengths, expect)\n\n starts = [11]\n stops = [14]\n lengths = cm_lengths(starts, stops, recombination)\n expect = np.array([0.00015], dtype = np.float64)\n np.testing.assert_almost_equal(lengths, expect)\n\n starts = [11]\n stops = [19]\n lengths = cm_lengths(starts, stops, recombination)\n expect = np.array([0.0009199999999999999], dtype = np.float64)\n np.testing.assert_almost_equal(lengths, expect)\n\n starts = [11]\n stops = [18]\n lengths = cm_lengths(starts, stops, recombination)\n expect = np.array([0.0007399999999999999], dtype = np.float64)\n np.testing.assert_almost_equal(lengths, expect)\n\n starts = [0]\n stops = [20]\n lengths = cm_lengths(starts, stops, recombination)\n expect = np.array([0.00215], dtype = np.float64)\n np.testing.assert_almost_equal(lengths, expect)","def read_resfile(filename):\n def place_constraints(constraint, init_seq):\n \"\"\"\n places the constraints in the appropriate dicts \n -initial_seq for building the initial sequence with TPIKAA and TNOTAA\n -constraints for restricting the conditional model with PIKAA, NOTAA, ALLAA, POLAR, etc.\n \"\"\"\n if not init_seq:\n constraints[res_id] = constraint\n else:\n initial_seq[res_id] = constraint\n\n constraints = dict() # amino acids to restrict in the design\n header, start_id = check_for_header(filename) # amino acids to use as default for those not specified in constraints\n initial_seq = dict() # amino acids to use when initializing the sequence\n\n with open(filename, \"r\") as f:\n # iterate over the lines and extract arguments (residue id, command)\n lines = f.readlines()\n for line in lines[start_id + 1:]:\n args = [arg.strip() for arg in line.split(\" \")]\n is_integer(args[0]) # the res id needs to be an integer\n assert isinstance(args[1], str), \"the resfile command needs to be a string\"\n \n res_id = int(args[0]) - 1\n if args[1] == \"-\": # if given a range of residue ids (ex. 31 - 33 NOTAA)\n is_integer(args[2]) # the res id needs to be an integer\n for res_id in range(res_id, int(args[2])):\n constraint, init_seq = check_for_commands(args, 3, 4)\n place_constraints(constraint, init_seq)\n else: # if not given a range (ex. 31 NOTAA CA)\n constraint, init_seq = check_for_commands(args, 1, 2)\n place_constraints(constraint, init_seq)\n \n # update the initial seq dictionary to only have one element per residue id (at random)\n initial_seq = {res_id : (common.atoms.resfile_commands[\"ALLAAwc\"] - restricted_aa).pop() for res_id, restricted_aa in initial_seq.items()}\n\n return constraints, header, initial_seq","def test_empty_with_filter(multi_mol_system_irregular):\n sequence = \"not empty\"\n processor = dssp.AnnotateResidues(\n \"test\", sequence, molecule_selector=lambda mol: False\n )\n with pytest.raises(ValueError):\n processor.run_system(multi_mol_system_irregular)","def test_special_RR(self):\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, -0.1).to_matrix(), \"RR\", {})\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, 0.2).to_matrix(), \"RR\", {\"r\": 2})\n self.check_oneq_special_cases(U3Gate(-np.pi, 0.2, 0.0).to_matrix(), \"RR\", {\"r\": 1})\n self.check_oneq_special_cases(U3Gate(np.pi, 0.0, 0.2).to_matrix(), \"RR\", {\"r\": 1})\n self.check_oneq_special_cases(U3Gate(0.1, 0.2, 0.3).to_matrix(), \"RR\", {\"r\": 2})","def test_rotamer_library_builder(self):\n LIGAND_PATH = 'ligands/oleic_acid.pdb'\n\n ligand_path = get_data_file_path(LIGAND_PATH)\n molecule = Molecule(ligand_path, exclude_terminal_rotamers=False)\n\n # rotamer_library = RotamerLibrary(molecule)\n\n rotamers_per_branch = molecule.rotamers\n\n assert len(rotamers_per_branch) == 2, \"Found an invalid number \" + \\\n \"of branches: {}\".format(len(rotamers_per_branch))\n\n atom_list_1 = list()\n atom_list_2 = list()\n\n rotamers = rotamers_per_branch[0]\n for rotamer in rotamers:\n atom_list_1.append(set([rotamer.index1, rotamer.index2]))\n\n rotamers = rotamers_per_branch[1]\n for rotamer in rotamers:\n atom_list_2.append(set([rotamer.index1, rotamer.index2]))\n\n EXPECTED_INDICES_1 = [set([9, 10]), set([8, 9]), set([7, 8]),\n set([6, 7]), set([5, 6]), set([2, 5]),\n set([0, 2]), set([0, 1])]\n\n EXPECTED_INDICES_2 = [set([12, 11]), set([12, 13]), set([13, 14]),\n set([14, 15]), set([15, 16]), set([16, 17]),\n set([17, 18]), set([18, 19])]\n\n where_1 = list()\n for atom_pair in atom_list_1:\n if atom_pair in EXPECTED_INDICES_1:\n where_1.append(1)\n elif atom_pair in EXPECTED_INDICES_2:\n where_1.append(2)\n else:\n where_1.append(0)\n\n where_2 = list()\n for atom_pair in atom_list_2:\n if atom_pair in EXPECTED_INDICES_1:\n where_2.append(1)\n elif atom_pair in EXPECTED_INDICES_2:\n where_2.append(2)\n else:\n where_2.append(0)\n\n assert (all(i == 1 for i in where_1)\n and all(i == 2 for i in where_2)) or \\\n (all(i == 2 for i in where_1)\n and all(i == 1 for i in where_2)), \"Invalid rotamer library \" + \\\n \"{}, {}\".format(where_1, where_2)\n\n assert (all(i == 1 for i in where_1)\n and all(i == 2 for i in where_2)\n and len(where_1) == len(EXPECTED_INDICES_1)\n and len(where_2) == len(EXPECTED_INDICES_2)) or \\\n (all(i == 2 for i in where_1)\n and all(i == 1 for i in where_2)\n and len(where_1) == len(EXPECTED_INDICES_2)\n and len(where_2) == len(EXPECTED_INDICES_1)), \"Unexpected \" + \\\n \"number of rotamers\"","def run(prefix):\n # run_tests.assert_folder_is_empty(prefix=prefix)\n xrs_good,xrs_poor,f_obs,r_free_flags = run_tests.setup_helix_example()\n # pdb_inp = os.path.join(qr_unit_tests,\"data_files\",\"2lvr.pdb\")\n r = run_tests.run_cmd(prefix,\n args = [\"restraints=cctbx\",\"mode=gtest\",\"g_scan=20\",\"g_mode=1\"],\n pdb_name = 'm00_poor.pdb', mtz_name='')\n assert os.path.isfile('1-20.npy')","def test_repetition_vector():\n cosimulations = [\n example.control.gauss_seidel(1., 5., 1.),\n example.control.gauss_seidel(1., 5., 1., True),\n example.control.gauss_seidel(1., 5., 1., True, True),\n example.control.gauss_seidel(1., 5., 1., False, True),\n example.control.gauss_jacobi(1., 5., 1.),\n example.control.multi_rate(1., 5., 1.),\n ]\n for cosimulation in cosimulations:\n sdfg = cs.convert_to_sdf(cosimulation)\n schedule = sdf.calculate_schedule(sdfg)\n network, hs, _, _ = cosimulation\n _, connections = network\n repetitions = cs.repetition_vector(connections, hs)\n for agent in sdfg[0]:\n assert sum(agent == executed for executed in schedule) == repetitions[agent]","def run_sims_foreach_allele(params_foreach_allele_dirpath, output_dirpath, start_popsize, max_popsize, gens, trials, seq_error_dirpath, use_norm_approx):\n\n ################ hard_coded_parameters ###################\n #this gives the selection coefficient. These are 'neutral'\n #simulations, so this is set at 0, but if one wants to \n #simulate alleles under selection, then change this\n #accordingly\n s = 0.0\n ################ hard_coded_parameters ###################\n\n if seq_error_dirpath[-1] != '/':\n seq_error_dirpath += '/'\n if output_dirpath[-1] != '/':\n output_dirpath += '/'\n if params_foreach_allele_dirpath[-1] != '/':\n params_foreach_allele_dirpath += '/'\n if not os.path.exists(output_dirpath):\n os.makedirs(output_dirpath)\n\n #get error rate for each possible amino acid\n error_rate_dic = estimate_error(seq_error_dirpath)\n\n #now get the population size at each\n #generation\n pop_sizes = get_pop_sizes(start_popsize, max_popsize, gens)\n\n #choose the correct parameter file based upon\n #the value of the global variable 'SGE_TASK_ID'\n param_filepaths = []\n for i in os.listdir(params_foreach_allele_dirpath):\n if i == 'README' or i[0] == '.':\n continue\n param_filepaths.append(params_foreach_allele_dirpath + i)\n sge_task_id = int(os.environ['SGE_TASK_ID'])\n param_filepath = param_filepaths[sge_task_id-1]\n\n #read in parameters from the parameter\n #file\n filein = open(param_filepath, \"r\")\n filein.readline()#burn header\n line = filein.readline()[:-1].split('\\t')\n filein.close()\n gene = line[0]\n position = line[1]\n derived_allele = line[3]\n rep = line[4]\n start_allele_freq = line[5]\n ending_num_reads = line[6]\n\n #check if sufficient data in param file\n if start_allele_freq == 'NA' or ending_num_reads == 'NA':\n output_filepath = '%s%s_%s_%s_%s' % (output_dirpath, gene, derived_allele, position, rep)\n fileout = open(output_filepath, \"w\")\n fileout.write(\"No simulations because start allele freq and/or ending number of reads was 'NA'.\\nnull\\n\")\n fileout.close()\n return\n else:\n start_allele_freq = float(start_allele_freq)\n ending_num_reads = float(ending_num_reads)\n #check if the ending number of reads is zero\n if ending_num_reads == 0.0:\n output_filepath = '%s%s_%s_%s_%s' % (output_dirpath, gene, derived_allele, position, rep)\n fileout = open(output_filepath, \"w\")\n fileout.write(\"No simulations because the ending number of reads was 0 so the ending allele frequency is undefined.\\nnull\\n\")\n fileout.close()\n return\n\n #this is the mutation rate that the given allele will mutate\n #to no longer be that allele\n error_rate_from = error_rate_dic[derived_allele][0]\n #this is the mutation rate where other alleles will mutate\n #to become the given allele\n error_rate_to = error_rate_dic[derived_allele][1]\n\n #define the output filepath based on allele identity\n output_filepath = '%s%s_%s_%s_%s' % (output_dirpath, gene, derived_allele, position, rep)\n\n #run simulation!\n run_sims(output_filepath, pop_sizes, trials, error_rate_from, error_rate_to, start_allele_freq, ending_num_reads, use_norm_approx, s)\n\n return","def test_multi_molecules_diff_sizes(self, multi_mol_system_irregular, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_irregular)\n found = self.sequence_from_system(multi_mol_system_irregular, \"test\")\n assert found == expected","def test_lsr_pairwise():\n for case in iter_testcases('pairwise'):\n n_items = case[\"n_items\"]\n data = case[\"data\"]\n assert np.allclose(\n case[\"lsr_est\"], lsr_pairwise(n_items, data),\n atol=ATOL, rtol=RTOL)","def internal_loop(p, i, j, k, l):\n return _RNAstructure_wrap.internal_loop(p, i, j, k, l)","def test_simulationRun(self):\n self.opt = { 'temperature' : 300.0, 'friction' : 1, 'dt' : 0.00002,\n 'nIter' : 2, 'nstepsNC' : 2, 'nstepsMD' : 1, 'nprop' : 1,\n 'nonbondedMethod' : 'NoCutoff', 'constraints': 'HBonds',\n 'trajectory_interval' : 1, 'reporter_interval' : 1,\n 'outfname' : 'mc-test',\n 'platform' : None,\n 'constraints' : 'HBonds',\n 'mc_per_iter' : 2 }\n\n structure = self.full_struct\n class SetRotationMove(RandomLigandRotationMove):\n def __init__(self, structure, resname='LIG'):\n super(SetRotationMove, self).__init__(structure, resname)\n\n def move(self, context):\n \"\"\"Function that performs a random rotation about the\n center of mass of the ligand.\n \"\"\"\n #TODO: check if we need to deepcopy\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\n\n self.positions = positions[self.atom_indices]\n self.center_of_mass = self.getCenterOfMass(self.positions, self.masses)\n reduced_pos = self.positions - self.center_of_mass\n\n # Define random rotational move on the ligand\n #set rotation so that test is reproducible\n set_rotation_matrix = np.array([[-0.62297988, -0.17349253, 0.7627558 ],\n [ 0.55082352, -0.78964857, 0.27027502],\n [ 0.55541834, 0.58851973, 0.58749893]])\n\n\n #set_rotation_matrix = np.array([[1, 0, 0],\n # [0, 1, 0],\n # [0, 0, 1]])\n\n #multiply lig coordinates by rot matrix and add back COM translation from origin\n rot_move = np.dot(reduced_pos, set_rotation_matrix) * positions.unit + self.center_of_mass\n\n # Update ligand positions in nc_sim\n for index, atomidx in enumerate(self.atom_indices):\n positions[atomidx] = rot_move[index]\n context.setPositions(positions)\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\n self.positions = positions[self.atom_indices]\n return context\n\n\n self.model = SetRotationMove(structure, resname='ALA')\n #self.model = RandomLigandRotationMove(structure, resname='ALA')\n\n self.model.atom_indices = range(22)\n self.model.topology = structure[self.model.atom_indices].topology\n self.model.positions = structure[self.model.atom_indices].positions\n self.model.calculateProperties()\n\n self.mover = MoveEngine(self.model)\n #Initialize the SimulationFactory object\n sims = SimulationFactory(structure, self.mover, **self.opt)\n #print(sims)\n system = sims.generateSystem(structure, **self.opt)\n simdict = sims.createSimulationSet()\n alch_system = sims.generateAlchSystem(system, self.model.atom_indices)\n self.nc_sim = sims.generateSimFromStruct(structure, self.mover, alch_system, ncmc=True, **self.opt)\n self.model.calculateProperties()\n self.initial_positions = self.nc_sim.context.getState(getPositions=True).getPositions(asNumpy=True)\n mc_sim = Simulation(sims, self.mover, **self.opt)\n #monkeypatch to access acceptance value\n def nacceptRejectMC(self, temperature=300, **opt):\n \"\"\"Function that chooses to accept or reject the proposed move.\n \"\"\"\n md_state0 = self.current_state['md']['state0']\n md_state1 = self.current_state['md']['state1']\n log_mc = (md_state1['potential_energy'] - md_state0['potential_energy']) * (-1.0/self.nc_sim.context._integrator.kT)\n randnum = math.log(np.random.random())\n\n if log_mc > randnum:\n self.accept += 1\n print('MC MOVE ACCEPTED: log_mc {} > randnum {}'.format(log_mc, randnum) )\n self.md_sim.context.setPositions(md_state1['positions'])\n else:\n self.reject += 1\n print('MC MOVE REJECTED: log_mc {} < {}'.format(log_mc, randnum) )\n self.md_sim.context.setPositions(md_state0['positions'])\n self.log_mc = log_mc\n self.md_sim.context.setVelocitiesToTemperature(self.opt['temperature'])\n mc_sim.acceptRejectMC = nacceptRejectMC\n nacceptRejectMC.__get__(mc_sim)\n mc_sim.acceptRejectMC = types.MethodType(nacceptRejectMC, mc_sim)\n mc_sim.runMC(self.opt['nIter'])\n #get log acceptance\n print(mc_sim.log_mc)\n #if mc is working, should be around -24.1\n assert mc_sim.log_mc <= -23.8 and mc_sim.log_mc >= -24.3","def test_08(self, test):\r\n globalConfig.test = test\r\n\r\n forbiddenRoutes = []\r\n outputList = getOutputList()\r\n inputList = getInputList()\r\n if len(inputList) == 0 or len(outputList) == 0:\r\n return test.UNCLEAR(\"Not tested. No resources found.\")\r\n\r\n for outputInstance in outputList:\r\n sourceID = outputInstance.getSourceID()\r\n for inputInstance in inputList:\r\n inputParent = inputInstance.getParent()\r\n if inputParent['type'] == \"source\" and sourceID == inputParent['id']:\r\n route = {\r\n \"input\": inputInstance,\r\n \"output\": outputInstance\r\n }\r\n forbiddenRoutes.append(route)\r\n\r\n for route in forbiddenRoutes:\r\n outputCaps = route['output'].getCaps()\r\n msg = (\"It is possible to create a loop using re-entrant matrices \"\r\n \"between Input {} and Output {}\".format(route['input'].id, route['output'].id))\r\n try:\r\n routableInputs = outputCaps['routable_inputs']\r\n except KeyError:\r\n return test.FAIL(\"Could not find 'routable_inputs' in /caps \"\r\n \"for Output {}\".format(route['output'].id))\r\n if routableInputs is None or route['input'].id in routableInputs:\r\n return test.FAIL(msg)\r\n return test.PASS()","def test_perceive_residues_natoms_mainchain_alanine(self, strict_chirality):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/MainChain_ALA.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def main():\n\n modulus = lambda c: (c.real*c.real + c.imag*c.imag)\n test_case = 0\n while True:\n try:\n _r, _i, iterations = input().split()\n except EOFError:\n break\n\n position = complex(float(_r), float(_i))\n z_value, outside = complex(0.0, 0.0), False\n for _ in range(int(iterations)):\n z_next = z_value * z_value + position\n outside = (modulus(z_next) > 4)\n if outside:\n break\n z_value = z_next\n\n test_case += 1\n print('Case {0}: {1}'.format(test_case, 'OUT' if outside else 'IN'))","def test_parallel_resistors(self):\r\n self.assertEqual(calc.evaluator({}, {}, '1||1'), 0.5)\r\n self.assertEqual(calc.evaluator({}, {}, '1||1||2'), 0.4)\r\n self.assertEqual(calc.evaluator({}, {}, \"j||1\"), 0.5 + 0.5j)","def test_template_forloop(self):\n print \"Running: %s - %s\" % (self.id(), self.shortDescription())\n # compare sequence items\n for i in range(0, 3):\n input_item = g.config['templates']['sequence'][i]\n output_item = self.output_config['out_templates']['sequence'][i]\n\n self.assertEqual(input_item, output_item,\n 'sequence items (%i) do not match' % i)","def test_ok_mm_primer(self):\r\n primers = ['AAAA', 'GGGG']\r\n self.assertEqual(ok_mm_primer('AAAA', primers, 0), True)\r\n self.assertEqual(ok_mm_primer('AAAA', primers, 3), True)\r\n self.assertEqual(ok_mm_primer('CCCC', primers, 0), False)\r\n self.assertEqual(ok_mm_primer('CCCA', primers, 3), True)\r\n self.assertEqual(ok_mm_primer('CCCA', primers, 2), False)\r\n self.assertEqual(ok_mm_primer('CCGG', primers, 2), True)\r\n self.assertEqual(ok_mm_primer('CCGA', primers, 2), False)","def build_set(ls, dsets):\n\n def noh(ls, dsets):\n \"\"\"\n This function remove hydrogens from the selection\n \"\"\"\n data_set = build_set(ls[1], dsets)\n\n noh_set = set()\n pred = oechem.OEIsHydrogen()\n\n for idx in data_set:\n atom = system.GetAtom(oechem.OEHasAtomIdx(idx))\n if not pred(atom):\n noh_set.add(idx)\n\n return noh_set\n\n def residues(ls):\n \"\"\"\n This function select residues based on the residue numbers. An example of\n selection can be:\n mask = 'resid A:16 17 19 B:1'\n \"\"\"\n # List residue atom index to be restrained\n res_atom_set = set()\n\n # Dictionary of lists with the chain residues selected to be restrained\n # e.g. {chainA:[res1, res15], chainB:[res19, res17]}\n chain_dic = {'': []}\n\n # Fill out the chain dictionary\n i = 0\n while i < len(ls):\n if ls[i].isdigit():\n chain_dic[''].append(int(ls[i]))\n i += 1\n else:\n try:\n chain_dic[ls[i]].append(int(ls[i + 2]))\n except:\n chain_dic[ls[i]] = []\n chain_dic[ls[i]].append(int(ls[i + 2]))\n i += 3\n\n # Loop over the molecular system to select the atom indexes to be selected\n hv = oechem.OEHierView(system, oechem.OEAssumption_BondedResidue + oechem.OEAssumption_ResPerceived)\n for chain in hv.GetChains():\n chain_id = chain.GetChainID()\n if chain_id not in chain_dic:\n continue\n for frag in chain.GetFragments():\n for hres in frag.GetResidues():\n res_num = hres.GetOEResidue().GetResidueNumber()\n if res_num not in chain_dic[chain_id]:\n continue\n for oe_at in hres.GetAtoms():\n res_atom_set.add(oe_at.GetIdx())\n\n return res_atom_set\n\n def around(dist, ls):\n \"\"\"\n This function select atom not far than the threshold distance from\n the current selection. The threshold distance is in Angstrom\n\n selection can be:\n mask = '5.0 around ligand'\n \"\"\"\n # at = system.GetAtom(oechem.OEHasAtomIdx(idx))\n\n # Atom set selection\n atom_set_around = set()\n\n # Create a OE bit vector mask for each atoms\n bv_around = oechem.OEBitVector(system.GetMaxAtomIdx())\n\n # Set the mask atom\n for at in system.GetAtoms():\n if at.GetIdx() in ls:\n bv_around.SetBitOn(at.GetIdx())\n\n # Predicate\n pred = oechem.OEAtomIdxSelected(bv_around)\n\n # Create the system molecule based on the atom mask\n molecules = oechem.OEMol()\n oechem.OESubsetMol(molecules, system, pred)\n\n # Create the Nearest neighbours\n nn = oechem.OENearestNbrs(system, float(dist))\n\n for nbrs in nn.GetNbrs(molecules):\n for atom in oechem.OEGetResidueAtoms(nbrs.GetBgn()):\n if atom.GetIdx() in ls:\n continue\n atom_set_around.add(atom.GetIdx())\n\n return atom_set_around\n\n # Start Body of the selection function by language\n\n # Terminal Literal return the related set\n if isinstance(ls, str):\n return dsets[ls]\n # Not or Noh\n if len(ls) == 2:\n if ls[0] == 'noh': # Noh case\n return noh(ls, dsets)\n elif ls[0] == 'not': # Not case\n return dsets['system'] - build_set(ls[1], dsets)\n else: # Resid case with one index\n return residues(ls[1])\n\n if len(ls) == 3:\n if ls[1] == 'or': # Or Case (set union)\n return build_set(ls[0], dsets) | build_set(ls[2], dsets)\n elif ls[1] == 'and': # And Case (set intersection)\n return build_set(ls[0], dsets) & build_set(ls[2], dsets)\n elif ls[1] == 'diff': # Diff case (set difference)\n return build_set(ls[0], dsets) - build_set(ls[2], dsets)\n elif ls[1] == 'around': # Around case\n return around(ls[0], build_set(ls[2], dsets))\n else:\n return residues(ls[1:]) # Resid case with one or two indexes\n else:\n if ls[0] == 'resid':\n return residues(ls[1:]) # Resid case with multiple indexes\n else:\n raise ValueError(\"The passed list have too many tokens: {}\".format(ls))"],"string":"[\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_residue_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for residue in mol_res_spin.residue_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_return_residue(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_residue(':1')\\n res2 = mol_res_spin.return_residue(selection=':2')\\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1.num, 1)\\n self.assertEqual(res1.name, None)\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2.num, 2)\\n self.assertEqual(res2.name, 'Glu')\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4.num, 4)\\n self.assertEqual(res4.name, 'Pro')\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5.num, -5)\\n self.assertEqual(res5.name, None)\\n self.assertEqual(res5.spin[1].name, 'N5')\",\n \"def test_spin_loop(self):\\n\\n # Spin data.\\n select = [1, 0]\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, 'N5')\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 2)\",\n \"def test_spin_loop_multiatom(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_molecule_loop_no_selection(self):\\n\\n # Molecule data.\\n name = ['Ap4Aase', 'RNA']\\n\\n # Loop over the molecules.\\n i = 0\\n for mol in mol_res_spin.molecule_loop():\\n # Test the molecule names.\\n self.assertEqual(mol.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)\",\n \"def test_molecule_loop(self):\\n\\n # Loop over the molecules.\\n for mol in mol_res_spin.molecule_loop('#RNA'):\\n # Test the molecule name.\\n self.assertEqual(mol.name, 'RNA')\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)\",\n \"def test_boolean_complex_selection(self):\\n\\n # The residue selection loop.\\n sel = list(mol_res_spin.residue_loop(\\\"#Ap4Aase:4 & :Pro | #RNA\\\"))\\n\\n # Residue names and numbers.\\n names = ['Pro', None, None]\\n numbers = [4, -5, -4]\\n\\n # The residues.\\n self.assertEqual(len(sel), 3)\\n for i in range(3):\\n self.assertEqual(sel[i].name, names[i])\\n self.assertEqual(sel[i].num, numbers[i])\",\n \"def test_boolean_and_selection(self):\\n\\n # The selection loop:\\n sel = list(mol_res_spin.residue_loop(\\\"#Ap4Aase:4 & :Pro\\\"))\\n\\n # Test:\\n self.assertEqual(len(sel), 1)\\n for res in sel:\\n self.assert_(res.name == \\\"Pro\\\" and res.num == 4)\",\n \"def test_spin_loop_no_selection(self):\\n\\n # Spin data.\\n select = [0, 1, 0, 0, 1, 1, 0, 1]\\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 8)\",\n \"def test_molecule_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for molecule in mol_res_spin.molecule_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_return_residue_pipe_fail(self):\\n\\n # Try to get a residue from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')\",\n \"def test_spin_loop_wildcard(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N*'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_molecule_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the molecules.\\n i = 0\\n for molecule in mol_res_spin.molecule_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_multi_molecules_cycle_one(self, multi_mol_system_irregular):\\n sequence = \\\"A\\\"\\n expected = [sequence] * (15 * 3)\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_irregular)\\n found = self.sequence_from_system(multi_mol_system_irregular, \\\"test\\\")\\n assert found == expected\",\n \"def test_spin_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for spin in mol_res_spin.spin_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_multi_molecules_cycle(self, multi_mol_system_regular, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n expected = expected * 3\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_regular)\\n found = self.sequence_from_system(multi_mol_system_regular, \\\"test\\\")\\n assert found == expected\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def check_residue_callback(self):\\n\\n if not self.check_for_residue_existance():\\n return\\n\\n self.listbox_current_designs.delete(0, END)\\n self.current_residueFull = self.current_residue.get().split(\\\":\\\")\\n\\n if len(self.current_residueFull) > 1:\\n self.listbox_restypes.delete(9)\\n self.listbox_restypes.insert(9, \\\"Conserved\\\")\\n else:\\n res = self.current_residueFull[0] +\\\":\\\"+self.current_chain.get()\\n #print res\\n if not self.pose.total_residue():\\n return\\n\\n resType = self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get()))\\n try:\\n resName = self.pose.residue(resType).name()\\n except PyRosettaException:\\n print \\\"Residue does not exist in PDB...\\\"\\n return\\n\\n\\n self.current_residue_name_full.set(resName)\\n three_letter_name = resName.split(\\\"_\\\")[0]; #Fix for Rosetta designated chain endings, His_d\\n self.current_residue_name.set(resName)\\n\\n #Fix for not having data for certain residue types:\\n try:\\n self.design_accessible_sa.set(self.residue_definitions.resinfo[three_letter_name][0])\\n self.design_relative_mutability.set(self.residue_definitions.resinfo[three_letter_name][1])\\n self.design_surface_probability.set(self.residue_definitions.resinfo[three_letter_name][2])\\n except KeyError:\\n print \\\"No Data for restype\\\"\\n self.design_accessible_sa.set(\\\"\\\")\\n self.design_relative_mutability.set(\\\"\\\")\\n self.design_surface_probability.set(\\\"\\\")\\n\\n con = \\\"Conserved:\\\" +three_letter_name\\n self.listbox_restypes.delete(9)\\n self.listbox_restypes.insert(9, con)\\n if self.DesignDic.has_key(res):\\n for residues in self.DesignDic[res]:\\n self.listbox_current_designs.insert(END, residues)\",\n \"def test_return_single_residue_info(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_single_residue_info('1')\\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\\n res5 = mol_res_spin.return_single_residue_info('-5')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1, (1, None))\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2, (2, 'Glu'))\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4, (4, 'Pro'))\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5, (-5, None))\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_single_molecules_cycle_one(self, single_mol_system):\\n sequence = \\\"A\\\"\\n expected = [sequence] * (5 * 3)\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def fixme_test_boolean_parenthesis_selection(self):\\n\\n # The selection loop:\\n sel = list(mol_res_spin.residue_loop(\\\"(#Ap4Aase & :Pro) | (#RNA & :-4)\\\"))\\n\\n # Test:\\n self.assertEqual(len(sel), 2)\\n for res in sel:\\n self.assert_(res.num in [-4, 4])\",\n \"def test_wrong_length(multi_mol_system_irregular, sequence):\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n with pytest.raises(ValueError):\\n processor.run_system(multi_mol_system_irregular)\",\n \"def nextRes(self):\\n\\n self.current_residueFull = self.current_residue.get().split(\\\":\\\")\\n if len(self.current_residueFull) < 2:\\n res = int(self.current_residue.get())+1\\n self.current_residue.set(res)\\n self.check_residue_callback()\\n else:\\n print \\\"Please Change selection to get info...\\\"\",\n \"def test_run_molecule(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def ROOMSELECTION_LOOP():\\n pass\",\n \"def residue(self, resnum, chain_id, icode=' ', alt=' ', model_num = 0):\\n res = self.struct[model_num][chain_id][(alt, resnum, icode)]\\n res.chain_id = chain_id\\n return res\",\n \"def test_return_single_residue_info_fail(self):\\n\\n # Ask for a few residues.\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')\",\n \"def assignResonanceResidue(resonance, residue):\\n\\n\\n #print 'assignResonanceResidue', makeResonanceGuiName(resonance), residue.seqId\\n if residue:\\n # we could be setting the residue to None\\n if not setAssignmentMolSystem(residue, resonance=resonance):\\n return\\n \\n resonanceSet = resonance.resonanceSet\\n if resonanceSet:\\n assignNames = set()\\n \\n for atomSet in resonanceSet.atomSets:\\n assignNames.add(atomSet.name)\\n \\n else:\\n assignNames = set(resonance.assignNames)\\n \\n assignedResidue = getResonanceResidue(resonance)\\n \\n if assignNames and (assignedResidue is not residue):\\n resonance.setAssignNames(assignNames)\\n \\n if residue:\\n atomSets = []\\n isotopeCode = resonance.isotopeCode\\n if ('HA' in assignNames) and (residue.ccpCode == 'Gly'):\\n assignNames.add('HA2')\\n assignNames.add('HA3')\\n \\n for atom in residue.atoms:\\n element = atom.chemAtom.elementSymbol\\n \\n if isotopeCode[-len(element):] != element:\\n continue\\n \\n atomSet = atom.atomSet\\n if atomSet:\\n if atomSet.name in assignNames:\\n if atomSet not in atomSets:\\n atomSets.append(atomSet)\\n \\n if resonanceSet:\\n resonanceSet.delete()\\n \\n if atomSets:\\n # might not always find atom sets\\n # e.g. if changing residue types\\n assignAtomsToRes(atomSets,resonance,None)\\n else:\\n if resonanceSet:\\n resonanceSet.delete()\\n #updateResonanceAnnotation(resonance)\\n\\n if not resonance.resonanceGroup:\\n nmrProject = resonance.nmrProject\\n spinSystem = None\\n molResidue = residue.molResidue\\n ccpCode = molResidue.ccpCode\\n molType = molResidue.molType\\n spinSystems = nmrProject.findAllResonanceGroups(ccpCode=ccpCode,\\n molType=molType)\\n \\n for extantSpinSystem in spinSystems:\\n if extantSpinSystem.residue is residue:\\n spinSystem = extantSpinSystem\\n break\\n \\n if not spinSystem:\\n spinSystem = nmrProject.newResonanceGroup()\\n assignSpinSystemResidue(spinSystem,residue)\\n \\n if resonance not in spinSystem.resonances:\\n spinSystem.addResonance(resonance)\\n updateResonanceAnnotation(resonance)\\n \\n else:\\n updateResonanceAnnotation(resonance)\",\n \"def test_RUMI():\\r\\n\\r\\n start = 11051\\r\\n end = 11902\\r\\n read_poems(start, end)\",\n \"def check_residue(self, chain_id, resid, resname):\\n if resname in PTM_lookup.keys():\\n return\\n else:\\n try:\\n ref_resname = PTM_reverse_lookup[resname]\\n except KeyError:\\n # print \\\"skipping unrecognized residue\\\", resname\\n return\\n ptm_dict = PTM_lookup[ref_resname][resname]\\n return (chain_id, resid, ref_resname, ptm_dict[\\\"goto_atom\\\"], ptm_dict[\\\"name\\\"])\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_selection():\\n pdb_inp = iotbx.pdb.input(source_info=None, lines=pdb_answer_0)\\n ncs_obj_phil = ncs.input(\\n hierarchy=pdb_inp.construct_hierarchy())\\n nrg = ncs_obj_phil.get_ncs_restraints_group_list()\\n\\n m1 = list(nrg[0].master_iselection)\\n c1 = list(nrg[0].copies[0].iselection)\\n c2 = list(nrg[0].copies[1].iselection)\\n\\n assert len(m1) == len(c1) # renumbering\\n assert m1 == [0, 1, 2, 3, 4, 5, 6] # 0, 1, X, 3, X, 5, X | 0, 1, 3\\n assert c1 == [7, 8, 9, 10, 11, 12, 13] # 7, 8, 9, X, X, 12, X | 4, 5, 7\\n assert c2 == [14, 15, 16, 17, 18, 19, 20] # 14, 15, X, 17, X, 19, X | 8, 9, 11\\n\\n selection1 = flex.size_t([0,1,5,3,100,101])\\n selection2 = flex.size_t([0,1,5,3,7,8,9,12,100,101])\\n selection3 = flex.size_t([0,1,5,3,7,8,9,12,14,15,19,17,100,101])\\n # gone iseqs for selection3: 2,4,6,10,11,13,16,18,20-99\\n\\n new_nrg = nrg.select(flex.bool(102, selection1))\\n # only atoms in master are selected\\n mt = list(new_nrg[0].master_iselection)\\n c1t = list(new_nrg[0].copies[0].iselection)\\n\\n assert mt == []\\n assert c1t == []\\n\\n # atoms selected in both master and copies\\n new_nrg = nrg.select(flex.bool(102, selection2))\\n # only atoms in master are selected\\n mt = list(new_nrg[0].master_iselection)\\n c1t = list(new_nrg[0].copies[0].iselection)\\n\\n assert mt == []\\n assert c1t == []\\n\\n new_nrg = nrg.select(flex.bool(102, selection3))\\n # only atoms in master are selected\\n mt = list(new_nrg[0].master_iselection)\\n c1t = list(new_nrg[0].copies[0].iselection)\\n c2t = list(new_nrg[0].copies[1].iselection)\\n\\n assert mt == [0, 1, 3], list(mt)\\n assert c1t == [4, 5, 7], list(c1t)\\n assert c2t == [8, 9, 11], list(c2t)\",\n \"def residues(ls):\\n # List residue atom index to be restrained\\n res_atom_set = set()\\n\\n # Dictionary of lists with the chain residues selected to be restrained\\n # e.g. {chainA:[res1, res15], chainB:[res19, res17]}\\n chain_dic = {'': []}\\n\\n # Fill out the chain dictionary\\n i = 0\\n while i < len(ls):\\n if ls[i].isdigit():\\n chain_dic[''].append(int(ls[i]))\\n i += 1\\n else:\\n try:\\n chain_dic[ls[i]].append(int(ls[i + 2]))\\n except:\\n chain_dic[ls[i]] = []\\n chain_dic[ls[i]].append(int(ls[i + 2]))\\n i += 3\\n\\n # Loop over the molecular system to select the atom indexes to be selected\\n hv = oechem.OEHierView(system, oechem.OEAssumption_BondedResidue + oechem.OEAssumption_ResPerceived)\\n for chain in hv.GetChains():\\n chain_id = chain.GetChainID()\\n if chain_id not in chain_dic:\\n continue\\n for frag in chain.GetFragments():\\n for hres in frag.GetResidues():\\n res_num = hres.GetOEResidue().GetResidueNumber()\\n if res_num not in chain_dic[chain_id]:\\n continue\\n for oe_at in hres.GetAtoms():\\n res_atom_set.add(oe_at.GetIdx())\\n\\n return res_atom_set\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_run_molecule_not_selected(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\", sequence, molecule_selector=lambda mol: False\\n )\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert vermouth.utils.are_all_equal(found)\\n assert found[0] is None\",\n \"def test_single_molecule(self, single_mol_system, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def test_perceive_residues_natoms_mainchain_charged_glutamic_acid(\\n self, strict_chirality\\n ):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/MainChain_GLH.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def test_setup_explicit_solvation_system():\\n with mmtools.utils.temporary_directory() as tmp_dir:\\n yaml_script = get_template_script(tmp_dir)\\n del yaml_script['experiments']\\n exp_builder = ExperimentBuilder(yaml_script)\\n output_dir = os.path.dirname(\\n exp_builder._db.get_system('hydration-system')[0].position_path)\\n\\n # Test that output file exists and that it has correct components\\n expected_resnames = {'solvent1': set(['TOL', 'WAT']), 'solvent2': set(['TOL'])}\\n for phase in expected_resnames:\\n found_resnames = set()\\n pdb_path = os.path.join(output_dir, phase + '.pdb')\\n prmtop_path = os.path.join(output_dir, phase + '.prmtop')\\n inpcrd_path = os.path.join(output_dir, phase + '.inpcrd')\\n\\n with open(pdb_path, 'r') as f:\\n for line in f:\\n if len(line) > 10 and line[:5] != 'CRYST':\\n found_resnames.add(line[17:20])\\n\\n assert os.path.exists(prmtop_path)\\n assert os.path.exists(inpcrd_path)\\n assert os.path.getsize(prmtop_path) > 0\\n assert os.path.getsize(inpcrd_path) > 0\\n assert found_resnames == expected_resnames[phase]\",\n \"def test_run_loop_success(self):\\n found = False\\n pyint = Interpreter(limit=15)\\n try:\\n pyint.run(code=BF_CODE_LOOP_TWICE)\\n except SystemExit: \\n found = True\\n self.assertFalse(found)\",\n \"def test_return_molecule(self):\\n\\n # Ask for a few molecules.\\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\\n\\n # Test the data of molecule 1.\\n self.assertEqual(mol1.name, 'Ap4Aase')\\n\\n # Test the data of molecule 2.\\n self.assertEqual(mol2.name, 'RNA')\",\n \"def test_perceive_residues_natoms_mainchain_arginine(self, strict_chirality):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/MainChain_ARG.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def test_residues(parse_mmtf):\\n parse_mmtf.assertEqual(len(parse_mmtf.mmcif_res), len(parse_mmtf.mmtf_res))\\n for i, e in enumerate(parse_mmtf.mmcif_res):\\n mmcif_r = parse_mmtf.mmcif_res[i]\\n mmtf_r = parse_mmtf.mmtf_res[i]\\n parse_mmtf.assertEqual(mmtf_r.level, mmcif_r.level)\\n parse_mmtf.assertEqual(mmtf_r.disordered, mmcif_r.disordered)\\n parse_mmtf.assertEqual(mmtf_r.resname, mmcif_r.resname)\\n parse_mmtf.assertEqual(mmtf_r.segid, mmcif_r.segid)\\n parse_mmtf.mmcif_atoms = [x for x in mmcif_r.get_atom()]\\n parse_mmtf.mmtf_atoms = [x for x in mmtf_r.get_atom()]\\n test_atoms(parse_mmtf=parse_mmtf)\",\n \"def mutate_residue(pose, mutant_position, mutant_aa,\\n pack_radius = 0.0, pack_scorefxn = '' ):\\n #### a MutateResidue Mover exists similar to this except it does not pack\\n #### the area around the mutant residue (no pack_radius feature)\\n #mutator = MutateResidue(mutant_position, mutant_aa)\\n #mutator.apply(test_pose)\\n\\n if pose.is_fullatom() == False:\\n IOError( 'mutate_residue only works with fullatom poses' )\\n\\n\\n # create a standard scorefxn by default\\n if not pack_scorefxn:\\n pack_scorefxn = rosetta.core.scoring.get_score_function()\\n\\n task = pyrosetta.standard_packer_task(pose)\\n\\n # the Vector1 of booleans (a specific object) is needed for specifying the\\n # mutation, this demonstrates another more direct method of setting\\n # PackerTask options for design\\n aa_bool = rosetta.utility.vector1_bool()\\n # PyRosetta uses several ways of tracking amino acids (ResidueTypes)\\n # the numbers 1-20 correspond individually to the 20 proteogenic amino acids\\n # aa_from_oneletter returns the integer representation of an amino acid\\n # from its one letter code\\n # convert mutant_aa to its integer representation\\n mutant_aa = rosetta.core.chemical.aa_from_oneletter_code(mutant_aa)\\n\\n # mutation is performed by using a PackerTask with only the mutant\\n # amino acid available during design\\n # to do this, construct a Vector1 of booleans indicating which amino acid\\n # (by its numerical designation, see above) to allow\\n for i in range(1, 21):\\n # in Python, logical expression are evaluated with priority, thus the\\n # line below appends to aa_bool the truth (True or False) of the\\n # statement i == mutant_aa\\n aa_bool.append( i == int(mutant_aa) )\\n\\n # modify the mutating residue's assignment in the PackerTask using the\\n # Vector1 of booleans across the proteogenic amino acids\\n task.nonconst_residue_task(mutant_position\\n ).restrict_absent_canonical_aas(aa_bool)\\n\\n # prevent residues from packing by setting the per-residue \\\"options\\\" of\\n # the PackerTask\\n restrict_non_nbrs_from_repacking(pose, mutant_position, task, pack_radius)\\n\\n # apply the mutation and pack nearby residues\\n #print task\\n packer = rosetta.protocols.simple_moves.PackRotamersMover(pack_scorefxn, task)\\n packer.apply(pose)\",\n \"def test_perceive_residues_natoms_mainchain_glutamic_acid(self, strict_chirality):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/MainChain_GLU.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def test_wrong_length_with_filter(multi_mol_system_irregular, sequence):\\n # We exclude the second molecule. The filter excludes it based on the\\n # number of nodes, which is 15 because it has 5 residues with 3 nodes\\n # each.\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\",\\n sequence,\\n molecule_selector=lambda mol: len(mol.nodes) != (5 * 3),\\n )\\n with pytest.raises(ValueError):\\n processor.run_system(multi_mol_system_irregular)\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def test_modeller_mutations():\\n mol_id = 'Abl'\\n abl_path = examples_paths()['abl']\\n with mmtools.utils.temporary_directory() as tmp_dir:\\n # Safety check: protein must have WT residue: THR at residue 85 in chain A\\n has_wt_residue = False\\n with open(abl_path, 'r') as f:\\n for line in f:\\n if (line[:6] == 'ATOM ') and (line[21] == 'A') and (int(line[22:26]) == 85) and (line[17:20]=='THR'):\\n has_wt_residue = True\\n break\\n assert has_wt_residue\\n\\n yaml_content = get_template_script(tmp_dir)\\n exp_builder = ExperimentBuilder(yaml_content)\\n output_dir = exp_builder._db.get_molecule_dir(mol_id)\\n output_path = os.path.join(output_dir, 'Abl.pdb')\\n\\n # We haven't set the strip_protons options, so this shouldn't do anything\\n exp_builder._db._setup_molecules(mol_id)\\n assert not os.path.exists(output_path)\\n\\n # Calling modeller with WT creates a file (although the protein is not mutated).\\n exp_builder._db.molecules[mol_id]['modeller'] = {\\n 'apply_mutations': {\\n 'chain_id': 'A',\\n 'mutations': 'WT',\\n }\\n }\\n setup_molecule_output_check(exp_builder._db, mol_id, output_path)\\n os.remove(output_path) # Remove file for next check.\\n\\n\\n # Reinitialize exp_builder\\n exp_builder = ExperimentBuilder(yaml_content)\\n\\n # Now we set the strip_protons options and repeat for the mutant case\\n exp_builder._db.molecules[mol_id]['modeller'] = {\\n 'apply_mutations': {\\n 'chain_id': 'A',\\n 'mutations': 'T85I',\\n }\\n }\\n setup_molecule_output_check(exp_builder._db, mol_id, output_path)\\n\\n # Safety check: protein must have mutated residue: ILE at residue 85 in chain A\\n has_mut_residue = False\\n with open(output_path, 'r') as f:\\n for line in f:\\n if (line[:6] == 'ATOM ') and (line[21] == 'A') and (int(line[22:26]) == 85) and (line[17:20]=='ILE'):\\n has_mut_residue = True\\n break\\n assert has_mut_residue\",\n \"def generate_quadratic_residues(bit_length, modulus, count):\\n for count in range(0, count):\\n yield generate_quadratic_residue(bit_length, modulus)\",\n \"def test_recomb(self):\\n sol1, sol2 = [0,0,0,0],[1,1,1,1]\\n hot_regions = [0,0,0,1] ##NOTE: sum(hot_regions) shouls always be 1\\n rec_events = 1\\n sol = list(d.recombine(sol1,sol2,rec_events,hot_regions))\\n print(f\\\"recomb sol: {sol}\\\")\\n self.assertTrue( (sol == [0,0,0,1]) or (sol == [1,1,1,0]) )\",\n \"def test_case_01_right_scalene(self):\\n self.__assert_equals_test_case(self.yield_right_scalene_triangles(), 'Right Scalene Triangle')\",\n \"def test_rb(self):\\n\\n # Load simulator\\n backend = qiskit.Aer.get_backend('qasm_simulator')\\n\\n # Test up to 2 qubits\\n nq_list = [1, 2]\\n\\n for nq in nq_list:\\n\\n print(\\\"Testing %d qubit RB\\\" % nq)\\n\\n for pattern_type in range(2):\\n for multiplier_type in range(2):\\n # See documentation of choose_pattern for the meaning of\\n # the different pattern types\\n\\n rb_opts = {}\\n rb_opts['nseeds'] = 3\\n rb_opts['length_vector'] = [1, 3, 4, 7]\\n rb_opts['rb_pattern'] = self.choose_pattern(\\n pattern_type, nq)\\n # if the pattern type is not relevant for nq\\n if rb_opts['rb_pattern'] is None:\\n continue\\n rb_opts['length_multiplier'] = self.choose_multiplier(\\n multiplier_type, len(rb_opts['rb_pattern']))\\n\\n # Generate the sequences\\n try:\\n rb_circs, _ = rb.randomized_benchmarking_seq(**rb_opts)\\n except OSError:\\n skip_msg = ('Skipping tests for %s qubits because '\\n 'tables are missing' % str(nq))\\n print(skip_msg)\\n continue\\n\\n # Perform an ideal execution on the generated sequences\\n # basis_gates = ['u1','u2','u3','cx'] # use U, CX for now\\n # Shelly: changed format to fit qiskit current version\\n basis_gates = 'u1, u2, u3, cx'\\n shots = 100\\n result = []\\n for seed in range(rb_opts['nseeds']):\\n result.append(\\n qiskit.execute(rb_circs[seed], backend=backend,\\n basis_gates=basis_gates,\\n shots=shots).result())\\n\\n # Verify the generated sequences\\n for seed in range(rb_opts['nseeds']):\\n length_vec = rb_opts['length_vector']\\n for circ_index, vec_len in enumerate(length_vec):\\n\\n self.assertEqual(\\n rb_circs[seed][circ_index].name,\\n 'rb_seed_%s_length_%s' % (\\n str(seed), str(vec_len)),\\n 'Error: incorrect circuit name')\\n self.verify_circuit(rb_circs[seed][circ_index],\\n nq, rb_opts,\\n vec_len, result[seed], shots)\\n\\n self.assertEqual(circ_index, len(rb_circs),\\n \\\"Error: additional circuits exist\\\")\",\n \"def test_perceive_residues_natoms_t4(self, strict_chirality):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/T4-protein.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def test_rotamer_core_constraint(self):\\n\\n LIGAND_PATH = 'ligands/oleic_acid.pdb'\\n ligand_path = get_data_file_path(LIGAND_PATH)\\n\\n # Test atom index constraint\\n molecule = Molecule(ligand_path, core_constraints=[19, ],\\n exclude_terminal_rotamers=False)\\n\\n rotamers_per_branch = molecule.rotamers\\n\\n assert len(rotamers_per_branch) == 1, \\\"Found an invalid number \\\" + \\\\\\n \\\"of branches: {}\\\".format(len(rotamers_per_branch))\\n\\n atom_list = list()\\n for rotamer in rotamers_per_branch[0]:\\n atom_list.append(set([rotamer.index1, rotamer.index2]))\\n\\n EXPECTED_INDICES = [set([18, 19]), set([17, 18]), set([16, 17]),\\n set([15, 16]), set([14, 15]), set([13, 14]),\\n set([12, 13]), set([11, 12]), set([9, 10]),\\n set([8, 9]), set([7, 8]), set([6, 7]),\\n set([5, 6]), set([2, 5]), set([0, 2]),\\n set([0, 1])]\\n\\n assert len(atom_list) == len(EXPECTED_INDICES), \\\"Unexpected \\\" + \\\\\\n \\\"number of rotamers\\\"\\n\\n assert all(atom_pair in EXPECTED_INDICES for atom_pair in atom_list), \\\\\\n \\\"Invalid rotamer library\\\"\\n\\n # Test PDB atom name constraint\\n molecule = Molecule(ligand_path, core_constraints=[' C18', ],\\n exclude_terminal_rotamers=False)\\n\\n rotamers_per_branch = molecule.rotamers\\n\\n assert len(rotamers_per_branch) == 1, \\\"Found an invalid number \\\" + \\\\\\n \\\"of branches: {}\\\".format(len(rotamers_per_branch))\\n\\n atom_list = list()\\n for rotamer in rotamers_per_branch[0]:\\n atom_list.append(set([rotamer.index1, rotamer.index2]))\\n\\n EXPECTED_INDICES = [set([18, 19]), set([17, 18]), set([16, 17]),\\n set([15, 16]), set([14, 15]), set([13, 14]),\\n set([12, 13]), set([11, 12]), set([9, 10]),\\n set([8, 9]), set([7, 8]), set([6, 7]),\\n set([5, 6]), set([2, 5]), set([0, 2]),\\n set([0, 1])]\\n\\n assert len(atom_list) == len(EXPECTED_INDICES), \\\"Unexpected \\\" + \\\\\\n \\\"number of rotamers\\\"\\n\\n assert all(atom_pair in EXPECTED_INDICES for atom_pair in atom_list), \\\\\\n \\\"Invalid rotamer library\\\"\\n\\n # Test core constraint with terminal exclusion\\n molecule = Molecule(ligand_path, core_constraints=[' C18', ],\\n exclude_terminal_rotamers=True)\\n\\n rotamers_per_branch = molecule.rotamers\\n\\n assert len(rotamers_per_branch) == 1, \\\"Found an invalid number \\\" + \\\\\\n \\\"of branches: {}\\\".format(len(rotamers_per_branch))\\n\\n atom_list = list()\\n for rotamer in rotamers_per_branch[0]:\\n atom_list.append(set([rotamer.index1, rotamer.index2]))\\n\\n EXPECTED_INDICES = [set([17, 18]), set([16, 17]), set([15, 16]),\\n set([14, 15]), set([13, 14]), set([12, 13]),\\n set([11, 12]), set([9, 10]), set([8, 9]),\\n set([7, 8]), set([6, 7]), set([5, 6]),\\n set([2, 5]), set([0, 2]), set([0, 1])]\\n\\n assert len(atom_list) == len(EXPECTED_INDICES), \\\"Unexpected \\\" + \\\\\\n \\\"number of rotamers\\\"\\n\\n assert all(atom_pair in EXPECTED_INDICES for atom_pair in atom_list), \\\\\\n \\\"Invalid rotamer library\\\"\\n\\n # Test core constraint with a central core\\n molecule = Molecule(ligand_path, core_constraints=[' C9 ', ],\\n exclude_terminal_rotamers=True)\\n\\n rotamers_per_branch = molecule.rotamers\\n\\n assert len(rotamers_per_branch) == 2, \\\"Found an invalid number \\\" + \\\\\\n \\\"of branches: {}\\\".format(len(rotamers_per_branch))\\n\\n atom_list_1 = list()\\n atom_list_2 = list()\\n rotamers = rotamers_per_branch[0]\\n for rotamer in rotamers:\\n atom_list_1.append(set([rotamer.index1, rotamer.index2]))\\n\\n rotamers = rotamers_per_branch[1]\\n for rotamer in rotamers:\\n atom_list_2.append(set([rotamer.index1, rotamer.index2]))\\n\\n EXPECTED_INDICES_1 = [set([9, 10]), set([8, 9]), set([7, 8]),\\n set([6, 7]), set([5, 6]), set([2, 5]),\\n set([0, 2]), set([0, 1])]\\n\\n EXPECTED_INDICES_2 = [set([12, 11]), set([12, 13]), set([13, 14]),\\n set([14, 15]), set([15, 16]), set([16, 17]),\\n set([17, 18])]\\n\\n where_1 = list()\\n for atom_pair in atom_list_1:\\n if atom_pair in EXPECTED_INDICES_1:\\n where_1.append(1)\\n elif atom_pair in EXPECTED_INDICES_2:\\n where_1.append(2)\\n else:\\n where_1.append(0)\\n\\n where_2 = list()\\n for atom_pair in atom_list_2:\\n if atom_pair in EXPECTED_INDICES_1:\\n where_2.append(1)\\n elif atom_pair in EXPECTED_INDICES_2:\\n where_2.append(2)\\n else:\\n where_2.append(0)\\n\\n assert (all(i == 1 for i in where_1)\\n and all(i == 2 for i in where_2)) or \\\\\\n (all(i == 2 for i in where_1)\\n and all(i == 1 for i in where_2)), \\\"Invalid rotamer library \\\" + \\\\\\n \\\"{}, {}\\\".format(where_1, where_2)\\n\\n assert (all(i == 1 for i in where_1)\\n and all(i == 2 for i in where_2)\\n and len(where_1) == len(EXPECTED_INDICES_1)\\n and len(where_2) == len(EXPECTED_INDICES_2)) or \\\\\\n (all(i == 2 for i in where_1)\\n and all(i == 1 for i in where_2)\\n and len(where_1) == len(EXPECTED_INDICES_2)\\n and len(where_2) == len(EXPECTED_INDICES_1)), \\\"Unexpected \\\" + \\\\\\n \\\"number of rotamers\\\"\\n\\n # Test core constraint with a multiple central core\\n molecule = Molecule(ligand_path,\\n core_constraints=[' C8 ', ' C9 ', ' C10'],\\n exclude_terminal_rotamers=True)\\n\\n rotamers_per_branch = molecule.rotamers\\n\\n assert len(rotamers_per_branch) == 2, \\\"Found an invalid number \\\" + \\\\\\n \\\"of branches: {}\\\".format(len(rotamers_per_branch))\\n\\n atom_list_1 = list()\\n atom_list_2 = list()\\n rotamers = rotamers_per_branch[0]\\n for rotamer in rotamers:\\n atom_list_1.append(set([rotamer.index1, rotamer.index2]))\\n\\n rotamers = rotamers_per_branch[1]\\n for rotamer in rotamers:\\n atom_list_2.append(set([rotamer.index1, rotamer.index2]))\\n\\n EXPECTED_INDICES_1 = [set([8, 9]), set([7, 8]), set([6, 7]),\\n set([5, 6]), set([2, 5]), set([0, 2]),\\n set([0, 1])]\\n\\n EXPECTED_INDICES_2 = [set([12, 11]), set([12, 13]), set([13, 14]),\\n set([14, 15]), set([15, 16]), set([16, 17]),\\n set([17, 18])]\\n\\n where_1 = list()\\n for atom_pair in atom_list_1:\\n if atom_pair in EXPECTED_INDICES_1:\\n where_1.append(1)\\n elif atom_pair in EXPECTED_INDICES_2:\\n where_1.append(2)\\n else:\\n where_1.append(0)\\n\\n where_2 = list()\\n for atom_pair in atom_list_2:\\n if atom_pair in EXPECTED_INDICES_1:\\n where_2.append(1)\\n elif atom_pair in EXPECTED_INDICES_2:\\n where_2.append(2)\\n else:\\n where_2.append(0)\\n\\n assert (all(i == 1 for i in where_1)\\n and all(i == 2 for i in where_2)) or \\\\\\n (all(i == 2 for i in where_1)\\n and all(i == 1 for i in where_2)), \\\"Invalid rotamer library \\\" + \\\\\\n \\\"{}, {}\\\".format(where_1, where_2)\\n\\n assert (all(i == 1 for i in where_1)\\n and all(i == 2 for i in where_2)\\n and len(where_1) == len(EXPECTED_INDICES_1)\\n and len(where_2) == len(EXPECTED_INDICES_2)) or \\\\\\n (all(i == 2 for i in where_1)\\n and all(i == 1 for i in where_2)\\n and len(where_1) == len(EXPECTED_INDICES_2)\\n and len(where_2) == len(EXPECTED_INDICES_1)), \\\"Unexpected \\\" + \\\\\\n \\\"number of rotamers\\\"\",\n \"def check_for_residue_existance(self):\\n if not self.pose.total_residue():\\n print \\\"No pose Loaded.\\\"\\n return False\\n\\n if not self.current_chain.get() or not self.current_residue.get():\\n print \\\"Chain or residue not set\\\"\\n return False\\n\\n current_region = self.current_residue.get().split(\\\":\\\")\\n if len(current_region)>1:\\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\\n\\n\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\\n print \\\"Region not found in pose\\\"\\n return False\\n else:\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\\n\\n print \\\"Residue not found in pose\\\"\\n return False\\n\\n #If everythig is good then:\\n return True\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def test_perceive_residues_cyclic_peptide_chirality(self, strict_chirality):\\n smiles = (\\n \\\"[H]c1c(c(c(c(c1[H])[H])C([H])([H])[C@]2(C(=O)N([C@](C(=O)N([C@@](C(=O)N3[C@@](C(=O)N2[H])\\\"\\n \\\"(C(C(C3([H])[H])([H])[H])([H])[H])[H])([H])C([H])([H])[H])[H])([H])C([H])([H])C4=C(N(c5c4c(c(c(c5[H])\\\"\\n \\\"[H])[H])[H])[H])[H])[H])[H])[H])[H]\\\"\\n )\\n offmol = Molecule.from_smiles(smiles)\\n # perceive residues\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n if strict_chirality:\\n # Make sure it fails if strict_chirality=True\\n with pytest.raises(AssertionError):\\n assert counter == offmol.n_atoms\\n else:\\n assert counter == offmol.n_atoms\",\n \"def getResAromaticVectors(residues):\\n for res in residues.keys():\\n rtype = res.split(\\\":\\\")[1][0:3] # A:GLY48 => GLY\\n try:\\n if rtype == \\\"PHE\\\" or rtype == \\\"TYR\\\":\\n if len(residues[res]) == 6:\\n pass\\n else:\\n if DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n elif rtype == \\\"TRP\\\":\\n if len(residues[res]) >= 9:\\n residues[res] = purgeTrp(residues[res])\\n else:\\n if DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n elif rtype == \\\"HIS\\\":\\n if len(residues[res]) >= 5:\\n residues[res] = purgeHis(residues[res])\\n else:\\n if DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n elif rtype == \\\"ARG\\\":\\n residues[res] = purgeArg(residues[res])\\n if not residues[res] and DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n elif rtype == \\\"DA\\\" or rtype == \\\"A\\\":\\n if len(residues[res]) >= 10:\\n residues[res] = purgeAdenine(residues[res])\\n else:\\n if DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n elif rtype == \\\"DC\\\" or rtype == \\\"C\\\":\\n if len(residues[res]) >= 6:\\n residues[res] = purgeAdenine(residues[res])\\n else:\\n if DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n elif rtype == \\\"DG\\\" or rtype == \\\"G\\\":\\n if len(residues[res]) >= 10:\\n residues[res] = purgeAdenine(residues[res])\\n else:\\n if DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n if residues[res]:\\n residues[res] = atomsToVec(residues[res])\\n else:\\n del residues[res]\\n except:\\n if DEBUG: print \\\"Fatal error in processing residue [ %s ]\\\"% res\\n del residues[res]\\n return residues\",\n \"def test_rescoring_option_problem(self):\\r\\n # get descriptor:\\r\\n problem_url_name = 'H1P1'\\r\\n self.define_option_problem(problem_url_name)\\r\\n location = InstructorTaskModuleTestCase.problem_location(problem_url_name)\\r\\n descriptor = self.module_store.get_item(location)\\r\\n\\r\\n # first store answers for each of the separate users:\\r\\n self.submit_student_answer('u1', problem_url_name, [OPTION_1, OPTION_1])\\r\\n self.submit_student_answer('u2', problem_url_name, [OPTION_1, OPTION_2])\\r\\n self.submit_student_answer('u3', problem_url_name, [OPTION_2, OPTION_1])\\r\\n self.submit_student_answer('u4', problem_url_name, [OPTION_2, OPTION_2])\\r\\n\\r\\n self.check_state('u1', descriptor, 2, 2, 1)\\r\\n self.check_state('u2', descriptor, 1, 2, 1)\\r\\n self.check_state('u3', descriptor, 1, 2, 1)\\r\\n self.check_state('u4', descriptor, 0, 2, 1)\\r\\n\\r\\n # update the data in the problem definition\\r\\n self.redefine_option_problem(problem_url_name)\\r\\n # confirm that simply rendering the problem again does not result in a change\\r\\n # in the grade:\\r\\n self.render_problem('u1', problem_url_name)\\r\\n self.check_state('u1', descriptor, 2, 2, 1)\\r\\n\\r\\n # rescore the problem for only one student -- only that student's grade should change:\\r\\n self.submit_rescore_one_student_answer('instructor', problem_url_name, User.objects.get(username='u1'))\\r\\n self.check_state('u1', descriptor, 0, 2, 1)\\r\\n self.check_state('u2', descriptor, 1, 2, 1)\\r\\n self.check_state('u3', descriptor, 1, 2, 1)\\r\\n self.check_state('u4', descriptor, 0, 2, 1)\\r\\n\\r\\n # rescore the problem for all students\\r\\n self.submit_rescore_all_student_answers('instructor', problem_url_name)\\r\\n self.check_state('u1', descriptor, 0, 2, 1)\\r\\n self.check_state('u2', descriptor, 1, 2, 1)\\r\\n self.check_state('u3', descriptor, 1, 2, 1)\\r\\n self.check_state('u4', descriptor, 2, 2, 1)\",\n \"def test_check_for_max_rmsd():\\n phil_groups = ncs_group_master_phil.fetch(\\n iotbx.phil.parse(phil_str)).extract()\\n pdb_inp = iotbx.pdb.input(source_info=None, lines=test_pdb_str_2)\\n ncs_obj_phil = ncs.input(\\n hierarchy=pdb_inp.construct_hierarchy(),\\n ncs_phil_groups=phil_groups.ncs_group)\\n nrgl = ncs_obj_phil.get_ncs_restraints_group_list()\\n pdb_inp = iotbx.pdb.input(lines=test_pdb_str_2,source_info=None)\\n ph = pdb_inp.construct_hierarchy()\\n # passing test\\n assert nrgl.check_for_max_rmsd(ph.atoms().extract_xyz() ,chain_max_rmsd=1)\\n # make sure test fails when it suppose to\\n nrgl[0].copies[1].t = matrix.col([100, -89.7668, 5.8996])\\n assert not nrgl.check_for_max_rmsd(ph.atoms().extract_xyz(),chain_max_rmsd=1)\",\n \"def isResidueAssigned(residue):\\n\\n for atom in residue.atoms:\\n if atom.atomSet:\\n if atom.atomSet.resonanceSets:\\n return True\\n \\n return False\",\n \"def test_run_a_scan_on_sdp_subarray_in_mid():\",\n \"def test_from_pdb_t4_n_residues(self):\\n expected_n_residues = 164 # noqa\\n raise NotImplementedError\",\n \"def mantra_simulation(lineup, module, mode='ST'):\\n\\n def try_optimal_solution(module, n_of_players_with_vote):\\n\\n \\\"\\\"\\\"\\n If an optimal solution exists this function assign it to the\\n variable \\\"final\\\" which is defined inside MANTRA_simulation but not\\n globally. That's why we refers to it later by using \\\"nonlocal\\\".\\n \\\"\\\"\\\"\\n\\n nonlocal all_lineups\\n nonlocal final_field\\n nonlocal malus\\n\\n # For each candidate\\n for candidate in all_lineups:\\n\\n # We create the list where each player in the combination has only\\n # 1 role\\n candidates_single_role = all_lineups_single_role(candidate)\\n\\n # And test each of these combinations\\n for new_cand in candidates_single_role:\\n\\n # If we find a solution we store the result\\n if find_solution(new_cand, module, n_of_players_with_vote):\\n final_field = new_cand\\n break\\n\\n # And stop the iteration over the other condidates\\n if final_field:\\n malus = 0\\n break\\n\\n def try_efficient_solution(module, n_of_players_with_vote):\\n\\n \\\"\\\"\\\"\\n If an optimal solution is not found we look for an efficient one.\\n In case an efficient solution exists we store the lineup and the\\n module.\\n \\\"\\\"\\\"\\n\\n modules_for_efficient_solution = copy.copy(all_modules)\\n modules_for_efficient_solution.remove(module)\\n\\n nonlocal all_lineups\\n nonlocal final_field\\n nonlocal efficient_module\\n nonlocal malus\\n\\n # Iterate over all the candidates\\n for candidate in all_lineups:\\n candidates_single_role = all_lineups_single_role(candidate)\\n for new_cand in candidates_single_role:\\n\\n # And over all the modules\\n for a_module in modules_for_efficient_solution:\\n\\n # If we find a solution we store the result\\n if find_solution(new_cand, a_module,\\n n_of_players_with_vote):\\n final_field = new_cand\\n efficient_module = a_module\\n break\\n\\n # Stop the iteration over the other permutations\\n if final_field:\\n break\\n\\n # Stop the iteration over the other candidates\\n if final_field:\\n malus = 0\\n break\\n\\n def try_adapted_solution(n_of_players_with_vote):\\n\\n \\\"\\\"\\\"\\n If an efficient solution is not found we look for an adapted one.\\n In case it exists we store the lineup, the module, the number of\\n malus assigned and the other modules that are equally valid.\\n \\\"\\\"\\\"\\n\\n modules_for_adapted_solution = copy.copy(all_modules)\\n\\n nonlocal all_lineups\\n nonlocal final_field\\n nonlocal adapted_module\\n nonlocal malus\\n\\n # As for the efficient case we iterate over:\\n\\n # 1. All the candidates\\n for candidate in all_lineups:\\n candidates_single_role = all_lineups_single_role(candidate)\\n\\n # 2. Each candidate transformed in single role\\n for new_cand in candidates_single_role:\\n\\n # 3. All the modules\\n for a_module in modules_for_adapted_solution:\\n\\n n_malus = find_adapted_solution(\\n new_cand, a_module, n_of_players_with_vote)\\n\\n # If a solution for this candidate with this module exists\\n # AND n_malus is decreased, we store the number of malus,\\n # the module and the lineup\\n if n_malus and n_malus < malus:\\n malus = n_malus\\n adapted_module = a_module\\n final_field = new_cand\\n\\n if malus == 1:\\n # In this case we break the loop because 1 is the\\n # minimum number of malus possible so we are not\\n # interested in iterating over the remaining\\n # candidates\\n break\\n\\n if malus == 1:\\n break\\n if malus == 1:\\n break\\n\\n def look_for_solution(module, n_of_players_with_vote):\\n\\n \\\"\\\"\\\"\\n It sequentially applies the three functions to look for the right\\n solution.\\n \\\"\\\"\\\"\\n\\n try_optimal_solution(module, n_of_players_with_vote)\\n if not final_field:\\n try_efficient_solution(module, n_of_players_with_vote)\\n if not final_field:\\n try_adapted_solution(n_of_players_with_vote)\\n\\n def solve_gkeeper():\\n\\n \\\"\\\"\\\"\\n Goal keeper substitution has to be the first thing to solve, if\\n needed. Here we modify field, bench and n_subst depending on whether\\n the gkeepers has vote or not.\\n \\\"\\\"\\\"\\n\\n nonlocal field\\n nonlocal bench\\n nonlocal n_subst\\n\\n # If the goal keeper n the field received a vote we delete all the\\n # remaining goal keepers from the bench\\n if find_gkeeper(field):\\n bench = delete_gkeeper(bench)\\n\\n # If the gkeeper in the field has no vote but the there is at least one\\n # gkeeper in the bench with vote we make the substitution and delete\\n # all the remaining gkeepers from the lineup, if there is any. We\\n # finally decrease the n_subst\\n elif not find_gkeeper(field) and find_gkeeper(bench):\\n gkeeper = find_gkeeper(bench)\\n field.insert(0, gkeeper)\\n bench = delete_gkeeper(bench)\\n n_subst -= 1\\n\\n # If there is no gkeeper with vote neither in the field nor in the\\n # bench than we just decrease the n_subst\\n elif not find_gkeeper(field) and not find_gkeeper(bench):\\n n_subst -= 1\\n\\n def calculation(a_number):\\n\\n \\\"\\\"\\\"\\n This is the function that is recursively applied to find the correct\\n lineup. The input 'a_number' is an integer which represents the\\n number of players (gkeeper excluded) who will partecipate in the\\n lineup calculation. In case the algorithm does not find any solution\\n after the first iteration it repeats the process considering 1\\n substitution and 1 player less.\\n \\\"\\\"\\\"\\n\\n nonlocal field\\n nonlocal bench\\n nonlocal module\\n nonlocal n_subst\\n nonlocal all_lineups\\n\\n all_lineups = valid_lineups(field, bench, n_subst)\\n look_for_solution(module, a_number)\\n\\n if not final_field:\\n n_subst -= 1\\n return calculation(a_number-1)\\n\\n clean_lineup = [(player[0], modify_player_name(player[1]), player[2])\\n for player in lineup]\\n\\n # Select the players with vote and store the number of substitutions needed\\n if mode == 'FG':\\n field, bench = players_with_vote(clean_lineup, 'FG')\\n else:\\n field, bench = players_with_vote(clean_lineup)\\n\\n n_subst = 11 - len(field)\\n\\n # In case no substitutions are needed, no calculation is started. In this\\n # case malus can only be due to errors coming from the fantaplayers when\\n # creating the lineup\\n if not n_subst:\\n malus = 0\\n ref_roles = schemes[module]\\n field[0] = (field[0][0], field[0][1], 'Por')\\n\\n for x in range(10):\\n roles_available = ref_roles[x].split('/')\\n roles_player = field[x + 1][2]\\n roles_shared = list(set(roles_available).intersection(\\n roles_player))\\n if roles_shared:\\n field[x + 1] = (field[x + 1][0], field[x + 1][1],\\n roles_shared[0])\\n else:\\n malus += 1\\n for role in roles_player:\\n temp_roles = malus_roles[role]\\n temp_roles = [role.split('/') for role in temp_roles]\\n temp_roles = [single_role for element in temp_roles for\\n single_role in element]\\n temp_roles = ['W' if role in ('W1', 'W2') else role for\\n role in temp_roles]\\n temp_roles = list(set(temp_roles))\\n roles_shared = list(set(roles_available).intersection(\\n temp_roles))\\n field[x + 1] = (field[x + 1][0], field[x + 1][1],\\n roles_shared[0])\\n break\\n\\n return field, bench, malus\\n\\n # Initialize all the parameters. We chose 10 for malus just because it is\\n # a number high enough and we look for the solution with the lower number\\n # of malus\\n final_field = [] # The final lineup\\n efficient_module = 0 # Valid module in case of eff solution\\n adapted_module = 0 # Valid module in case of adp solution\\n malus = 10 # Number of malus assigned\\n magic_number = 10 # N. of players considered in the lineup\\n all_lineups = 0 # All candidates\\n\\n # We need all the modules to be able to iterate over them in case an\\n # efficient or adapted solution is needed. We also remove the module chosen\\n # by the fantaplayer and then insert it as first element. In this way, this\\n # module will be the first to be checked\\n all_modules = ['343', '3412', '3421', '352', '442', '433',\\n '4312', '4321', '4231', '4411', '4222']\\n all_modules.remove(module)\\n all_modules.insert(0, module)\\n\\n # Set the right magic_number value if n_subst > 3\\n if n_subst > 3:\\n magic_number = 13 - n_subst\\n n_subst = 3\\n\\n # Handle the goal keeper issue\\n solve_gkeeper()\\n if find_gkeeper(field):\\n gkeeper = field[0]\\n field.remove(gkeeper)\\n else:\\n gkeeper = 0\\n\\n calculation(magic_number)\\n\\n if gkeeper:\\n gkeeper = (gkeeper[0], gkeeper[1], gkeeper[2][0])\\n final_field.insert(0, gkeeper)\\n\\n # Create the bench\\n field_names = [player[1] for player in final_field]\\n final_bench = [player for player in clean_lineup[11:] if player[1] not in\\n field_names]\\n\\n return final_field, final_bench, malus, efficient_module, adapted_module\",\n \"def test_run_loop_exc(self):\\n with self.assertRaises(ExecutionException):\\n pyint = Interpreter(limit=1)\\n pyint.run(code=BF_CODE_LOOP_TWICE)\",\n \"def test_assign_resources_to_tmc_subarray_in_mid():\",\n \"def select_perturbation_residues(molecule):\\n # Validte the length of the molecule\\n validate_molecule_length(molecule)\\n # Set the maximum allowed perturbation numbers\\n maxNum = 3\\n # Select a random number between 1 and maxNum\\n ranNum = random.randint(1, maxNum)\\n # Define the perturbed list to hold the perturbed residue name\\n perturbed = []\\n count = 0\\n while count < ranNum:\\n # Random select a residue number in the molecule \\n index = random.randint(1, len(molecule))\\n perturbed.append([molecule.name, index, molecule[index].name])\\n count += 1\\n\\n return perturbed\",\n \"def test_perceive_residues_sorting(self, strict_chirality):\\n molecule = Molecule.from_file(get_data_file_path(\\\"proteins/ace-a10-nme.sdf\\\"))\\n\\n molecule.perceive_residues(strict_chirality=strict_chirality)\\n\\n for index, residue in enumerate(molecule.residues):\\n found = residue.residue_number\\n expected = str(index + 1)\\n\\n assert isinstance(found, str)\\n assert found == expected\",\n \"def algorithm_loop(self):\",\n \"def get_residues_sequence (structure):\\n list_fastas=[]\\n residues_dict = {'CYS': 'C', 'ASP': 'D', 'SER': 'S', 'GLN': 'Q', 'LYS': 'K',\\n 'ILE': 'I', 'PRO': 'P', 'THR': 'T', 'PHE': 'F', 'ASN': 'N',\\n 'GLY': 'G', 'HIS': 'H', 'LEU': 'L', 'ARG': 'R', 'TRP': 'W',\\n 'ALA': 'A', 'VAL': 'V', 'GLU': 'E', 'TYR': 'Y', 'MET': 'M'}\\n\\n rna_dict={ ' G': 'G', ' C': 'C', ' A': 'A', ' T': 'T', ' U': 'U'}\\n dna_dict={ ' DG': 'G', ' DC': 'C', ' DA': 'A', ' DT': 'T', ' DU': 'U'}\\n\\n for model in structure:\\n for chain in model:\\n string=\\\"\\\"\\n for residue in chain:\\n for atom in residue:\\n if atom.id == \\\"CA\\\":\\n if residue.resname == 'UNK':\\n continue \\n else:\\n if residue.resname not in residues_dict:\\n raise NoExistsResidue(residue.resname) \\n residue_name = residues_dict[residue.resname] \\n string = string + residue_name\\n elif atom.id == \\\"P\\\":\\n if residue.resname.startswith(\\\" D\\\"):\\n residue_name= dna_dict[residue.resname]\\n if residue.resname not in dna_dict:\\n raise NoExistsDesoxiribonucleotide(residue.resname)\\n else:\\n residue_name= rna_dict[residue.resname]\\n if residue.resname not in rna_dict:\\n raise NoExistsRibonucleotide(residue.resname)\\n string= string + residue_name\\n if string != \\\"\\\":\\n list_fastas.append(string)\\n return list_fastas\",\n \"def test_return_molecule_pipe_fail(self):\\n\\n # Try to get a molecule from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')\",\n \"def test_select_pdb_conformation(self):\\n with mmtools.utils.temporary_directory() as tmp_dir:\\n yaml_content = \\\"\\\"\\\"\\n ---\\n options:\\n output_dir: {}\\n setup_dir: .\\n molecules:\\n selected:\\n filepath: {}\\n leap: {{parameters: oldff/leaprc.ff14SB}}\\n select: 1\\n \\\"\\\"\\\".format(tmp_dir, self.pdb_path)\\n yaml_content = textwrap.dedent(yaml_content)\\n exp_builder = ExperimentBuilder(yaml_content)\\n\\n # The molecule now is neither set up nor processed\\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\\n assert is_setup is False\\n assert is_processed is False\\n\\n # The setup of the molecule must isolate the frame in a single-frame PDB\\n exp_builder._db._setup_molecules('selected')\\n selected_pdb_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\\n 'selected', 'selected.pdb')\\n assert os.path.exists(os.path.join(selected_pdb_path))\\n assert os.path.getsize(os.path.join(selected_pdb_path)) > 0\\n\\n # The positions must be the ones of the second frame\\n selected_pdb = PDBFile(selected_pdb_path)\\n selected_pos = selected_pdb.getPositions(asNumpy=True)\\n second_pos = PDBFile(self.pdb_path).getPositions(asNumpy=True, frame=1)\\n assert selected_pdb.getNumFrames() == 1\\n assert (selected_pos == second_pos).all()\\n\\n # The description of the molecule is now updated\\n assert os.path.normpath(exp_builder._db.molecules['selected']['filepath']) == selected_pdb_path\\n\\n # The molecule now both set up and processed\\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\\n assert is_setup is True\\n assert is_processed is True\\n\\n # A new instance of ExperimentBuilder is able to resume with correct molecule\\n exp_builder = ExperimentBuilder(yaml_content)\\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\\n assert is_setup is True\\n assert is_processed is True\",\n \"def initResonance(resonance, doMerge=True):\\n from ccpnmr.analysis.core.MoleculeBasic import DEFAULT_ISOTOPES\\n \\n if resonance.isDeleted:\\n return\\n \\n #print 'initResonance', makeResonanceGuiName(resonance)\\n resonanceSet = resonance.resonanceSet\\n \\n if resonance.name == 'r%d' % resonance.serial:\\n resonance.setName(None)\\n \\n if resonanceSet:\\n atomSets = tuple(resonanceSet.atomSets)\\n atom = atomSets[0].findFirstAtom()\\n element = atom.chemAtom.elementSymbol\\n if resonance.isotopeCode[-len(element):] != element:\\n msg = 'Resonance %d isotope-assignment mismatch: Resetting isotope' \\n print msg % resonance.serial\\n \\n resonance.isotopeCode = DEFAULT_ISOTOPES.get(element, 'unknown')\\n getBoundResonances(resonance, recalculate=True, contribs=None) \\n \\n spinSystem = findSpinSystem(resonance)\\n if spinSystem:\\n if resonance.resonanceGroup: # same as the spin system\\n residue = atom.residue\\n \\n if spinSystem.residue is not residue:\\n #assignSpinSystemResidue(spinSystem,residue)\\n \\n if doMerge:\\n ccpCode = residue.molResidue.ccpCode\\n spinSystems = list(resonance.nmrProject.findAllResonanceGroups(residue=residue))\\n N = len(spinSystems)\\n msg = 'There are %d separate %d%s spin systems. Merge together?'\\n if (N > 1) and showOkCancel('Confirm', msg % (N,residue.seqCode,ccpCode)):\\n assignSpinSystemResidue(spinSystem,residue) \\n \\n for spinSystem1 in spinSystems[1:]:\\n mergeSpinSystems(spinSystem1,spinSystems[0])\\n \\n else:\\n assignSpinSystemResidue(spinSystem,residue) \\n \\n else:\\n assignSpinSystemResidue(spinSystem,residue) \\n \\n else:\\n addSpinSystemResonance(spinSystem, resonance)\\n\\n assignResonanceType(resonance, atomSets)\\n \\n else:\\n updateResonanceAnnotation(resonance)\\n\\n if not resonance.shifts:\\n if resonance.peakDimContribs:\\n for contrib in resonance.peakDimContribs:\\n peakDim = contrib.peakDim\\n experiment = peakDim.peak.peakList.dataSource.experiment\\n \\n if experiment.shiftList is None:\\n shiftList = resonance.nmrProject.findFirstMeasurementList(className='ShiftList')\\n if shiftList is None:\\n shiftList = resonance.nmrProject.newShiftList(unit='ppm')\\n experiment.setShiftList( shiftList )\\n \\n updateResonShift(resonance,peakDim)\",\n \"def testrescorr():\\n tau = np.zeros((2,50))\\n tau[0,25] = 2\\n tau[1,23] = 3\\n tau2 = spec_utils.res_corr(tau, 2, 8)\\n #Check flux conserved\\n assert np.abs(np.sum(tau2[0,:])/ np.sum(tau[0,:]) -1) < 1e-6\\n assert np.abs(np.sum(tau2[1,:])/ np.sum(tau[1,:]) -1) < 1e-6\\n #Check expanded by expected amount\\n for i in (0,1):\\n assert np.size(np.where(tau2[i,:]> 0)) == 15\",\n \"def test_rescore_unmask(self):\\r\\n module = CapaFactory.create(xml=self.common_shuffle_xml)\\r\\n get_request_dict = {CapaFactory.input_key(): 'mask_0'}\\r\\n module.check_problem(get_request_dict)\\r\\n # On rescore, state/student_answers should use unmasked names\\r\\n with patch.object(module.runtime, 'track_function') as mock_track_function:\\r\\n module.rescore_problem()\\r\\n mock_call = mock_track_function.mock_calls[0]\\r\\n event_info = mock_call[1][1]\\r\\n self.assertEquals(mock_call[1][0], 'problem_rescore')\\r\\n self.assertEquals(event_info['state']['student_answers'][CapaFactory.answer_key()], 'choice_2')\\r\\n self.assertIsNotNone(event_info['permutation'][CapaFactory.answer_key()])\",\n \"def test_terminal_rotamer_filtering(self):\\n LIGAND_PATH = 'ligands/oleic_acid.pdb'\\n\\n ligand_path = get_data_file_path(LIGAND_PATH)\\n molecule = Molecule(ligand_path, exclude_terminal_rotamers=True)\\n\\n rotamers_per_branch = molecule.rotamers\\n\\n assert len(rotamers_per_branch) == 2, \\\"Found an invalid number \\\" + \\\\\\n \\\"of branches: {}\\\".format(len(rotamers_per_branch))\\n\\n atom_list_1 = list()\\n atom_list_2 = list()\\n rotamers = rotamers_per_branch[0]\\n for rotamer in rotamers:\\n atom_list_1.append(set([rotamer.index1, rotamer.index2]))\\n\\n rotamers = rotamers_per_branch[1]\\n for rotamer in rotamers:\\n atom_list_2.append(set([rotamer.index1, rotamer.index2]))\\n\\n EXPECTED_INDICES_1 = [set([9, 10]), set([8, 9]), set([7, 8]),\\n set([6, 7]), set([5, 6]), set([2, 5]),\\n set([0, 2]), set([0, 1])]\\n\\n EXPECTED_INDICES_2 = [set([12, 11]), set([12, 13]), set([13, 14]),\\n set([14, 15]), set([15, 16]), set([16, 17]),\\n set([17, 18])]\\n\\n where_1 = list()\\n for atom_pair in atom_list_1:\\n if atom_pair in EXPECTED_INDICES_1:\\n where_1.append(1)\\n elif atom_pair in EXPECTED_INDICES_2:\\n where_1.append(2)\\n else:\\n where_1.append(0)\\n\\n where_2 = list()\\n for atom_pair in atom_list_2:\\n if atom_pair in EXPECTED_INDICES_1:\\n where_2.append(1)\\n elif atom_pair in EXPECTED_INDICES_2:\\n where_2.append(2)\\n else:\\n where_2.append(0)\\n\\n assert (all(i == 1 for i in where_1)\\n and all(i == 2 for i in where_2)) or \\\\\\n (all(i == 2 for i in where_1)\\n and all(i == 1 for i in where_2)), \\\"Invalid rotamer library \\\" + \\\\\\n \\\"{}, {}\\\".format(where_1, where_2)\\n\\n assert (all(i == 1 for i in where_1)\\n and all(i == 2 for i in where_2)\\n and len(where_1) == len(EXPECTED_INDICES_1)\\n and len(where_2) == len(EXPECTED_INDICES_2)) or \\\\\\n (all(i == 2 for i in where_1)\\n and all(i == 1 for i in where_2)\\n and len(where_1) == len(EXPECTED_INDICES_2)\\n and len(where_2) == len(EXPECTED_INDICES_1)), \\\"Unexpected \\\" + \\\\\\n \\\"number of rotamers\\\"\",\n \"def test_find_surface_residues():\\n atom_dict_0 = find_surface_residues(protein, max_dist=0, scaling=1)\\n atom_dict_1 = find_surface_residues(protein, max_dist=2, scaling=1)\\n atom_dict_2 = find_surface_residues(protein, max_dist=3, scaling=1)\\n atom_dict_3 = find_surface_residues(protein, max_dist=None, scaling=1)\\n atom_dict_4 = find_surface_residues(protein, max_dist=None, scaling=2)\\n\\n assert atom_dict_0.size == 0\\n assert len(atom_dict_1) > len(atom_dict_0), ('Increasing max_dist should '\\n 'result in more/equal number '\\n 'of atoms found')\\n\\n assert len(atom_dict_2) >= len(atom_dict_1), ('Increasing max_dist should '\\n 'result in more/equal number '\\n 'of atoms found')\\n assert_array_equal(np.intersect1d(atom_dict_1['id'], atom_dict_2['id']), atom_dict_1['id'])\\n\\n if oddt.toolkit.backend == 'ob':\\n ref_len_1 = 762\\n ref_len_2 = 968\\n ref_len_3 = 654\\n ref_len_4 = 379\\n elif oddt.toolkit.backend == 'rdk' and oddt.toolkits.rdk.__version__ >= '2019.09':\\n ref_len_1 = 762\\n ref_len_2 = 968\\n ref_len_3 = 664\\n ref_len_4 = 393\\n else:\\n ref_len_1 = 759\\n ref_len_2 = 966\\n ref_len_3 = 735\\n ref_len_4 = 489\\n\\n assert len(atom_dict_1) == ref_len_1\\n assert len(atom_dict_2) == ref_len_2\\n assert len(atom_dict_3) == ref_len_3\\n assert len(atom_dict_4) == ref_len_4\\n\\n # Adding hydrogen atoms should have no effect on the result\\n protein.addh()\\n atom_dict_addh = find_surface_residues(protein, max_dist=2, scaling=1)\\n assert_array_equal(atom_dict_addh['id'], atom_dict_1['id'])\\n\\n with pytest.raises(TypeError):\\n find_surface_residues(molecule=1)\\n with pytest.raises(ValueError):\\n find_surface_residues(molecule=protein, max_dist='a')\\n with pytest.raises(ValueError):\\n find_surface_residues(molecule=protein, max_dist=[1, 1, 1])\",\n \"def test_single_segment(self):\\n\\n recombination = MagicMock()\\n recombination.bases = np.array([5, 10, 15, 20], dtype = np.uint32)\\n recombination.cm = np.array([0.00000, 0.001, 0.00125, 0.00215])\\n recombination.rates = np.array([0.0002000000, 0.0000500000,\\n 0.0001800000, 0.0002000000])\\n\\n starts = [0]\\n stops = [5]\\n lengths = cm_lengths(starts, stops, recombination)\\n expect = np.array([0.000], dtype = np.float64)\\n np.testing.assert_almost_equal(lengths, expect)\\n\\n starts = [5]\\n stops = [10]\\n lengths = cm_lengths(starts, stops, recombination)\\n expect = np.array([0.001], dtype = np.float64)\\n np.testing.assert_almost_equal(lengths, expect)\\n\\n starts = [10]\\n stops = [15]\\n lengths = cm_lengths(starts, stops, recombination)\\n expect = np.array([0.00025], dtype = np.float64)\\n np.testing.assert_almost_equal(lengths, expect)\\n\\n starts = [15]\\n stops = [20]\\n lengths = cm_lengths(starts, stops, recombination)\\n expect = np.array([0.0009], dtype = np.float64)\\n np.testing.assert_almost_equal(lengths, expect)\\n\\n starts = [11]\\n stops = [14]\\n lengths = cm_lengths(starts, stops, recombination)\\n expect = np.array([0.00015], dtype = np.float64)\\n np.testing.assert_almost_equal(lengths, expect)\\n\\n starts = [11]\\n stops = [19]\\n lengths = cm_lengths(starts, stops, recombination)\\n expect = np.array([0.0009199999999999999], dtype = np.float64)\\n np.testing.assert_almost_equal(lengths, expect)\\n\\n starts = [11]\\n stops = [18]\\n lengths = cm_lengths(starts, stops, recombination)\\n expect = np.array([0.0007399999999999999], dtype = np.float64)\\n np.testing.assert_almost_equal(lengths, expect)\\n\\n starts = [0]\\n stops = [20]\\n lengths = cm_lengths(starts, stops, recombination)\\n expect = np.array([0.00215], dtype = np.float64)\\n np.testing.assert_almost_equal(lengths, expect)\",\n \"def read_resfile(filename):\\n def place_constraints(constraint, init_seq):\\n \\\"\\\"\\\"\\n places the constraints in the appropriate dicts \\n -initial_seq for building the initial sequence with TPIKAA and TNOTAA\\n -constraints for restricting the conditional model with PIKAA, NOTAA, ALLAA, POLAR, etc.\\n \\\"\\\"\\\"\\n if not init_seq:\\n constraints[res_id] = constraint\\n else:\\n initial_seq[res_id] = constraint\\n\\n constraints = dict() # amino acids to restrict in the design\\n header, start_id = check_for_header(filename) # amino acids to use as default for those not specified in constraints\\n initial_seq = dict() # amino acids to use when initializing the sequence\\n\\n with open(filename, \\\"r\\\") as f:\\n # iterate over the lines and extract arguments (residue id, command)\\n lines = f.readlines()\\n for line in lines[start_id + 1:]:\\n args = [arg.strip() for arg in line.split(\\\" \\\")]\\n is_integer(args[0]) # the res id needs to be an integer\\n assert isinstance(args[1], str), \\\"the resfile command needs to be a string\\\"\\n \\n res_id = int(args[0]) - 1\\n if args[1] == \\\"-\\\": # if given a range of residue ids (ex. 31 - 33 NOTAA)\\n is_integer(args[2]) # the res id needs to be an integer\\n for res_id in range(res_id, int(args[2])):\\n constraint, init_seq = check_for_commands(args, 3, 4)\\n place_constraints(constraint, init_seq)\\n else: # if not given a range (ex. 31 NOTAA CA)\\n constraint, init_seq = check_for_commands(args, 1, 2)\\n place_constraints(constraint, init_seq)\\n \\n # update the initial seq dictionary to only have one element per residue id (at random)\\n initial_seq = {res_id : (common.atoms.resfile_commands[\\\"ALLAAwc\\\"] - restricted_aa).pop() for res_id, restricted_aa in initial_seq.items()}\\n\\n return constraints, header, initial_seq\",\n \"def test_empty_with_filter(multi_mol_system_irregular):\\n sequence = \\\"not empty\\\"\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\", sequence, molecule_selector=lambda mol: False\\n )\\n with pytest.raises(ValueError):\\n processor.run_system(multi_mol_system_irregular)\",\n \"def test_special_RR(self):\\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, -0.1).to_matrix(), \\\"RR\\\", {})\\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, 0.2).to_matrix(), \\\"RR\\\", {\\\"r\\\": 2})\\n self.check_oneq_special_cases(U3Gate(-np.pi, 0.2, 0.0).to_matrix(), \\\"RR\\\", {\\\"r\\\": 1})\\n self.check_oneq_special_cases(U3Gate(np.pi, 0.0, 0.2).to_matrix(), \\\"RR\\\", {\\\"r\\\": 1})\\n self.check_oneq_special_cases(U3Gate(0.1, 0.2, 0.3).to_matrix(), \\\"RR\\\", {\\\"r\\\": 2})\",\n \"def test_rotamer_library_builder(self):\\n LIGAND_PATH = 'ligands/oleic_acid.pdb'\\n\\n ligand_path = get_data_file_path(LIGAND_PATH)\\n molecule = Molecule(ligand_path, exclude_terminal_rotamers=False)\\n\\n # rotamer_library = RotamerLibrary(molecule)\\n\\n rotamers_per_branch = molecule.rotamers\\n\\n assert len(rotamers_per_branch) == 2, \\\"Found an invalid number \\\" + \\\\\\n \\\"of branches: {}\\\".format(len(rotamers_per_branch))\\n\\n atom_list_1 = list()\\n atom_list_2 = list()\\n\\n rotamers = rotamers_per_branch[0]\\n for rotamer in rotamers:\\n atom_list_1.append(set([rotamer.index1, rotamer.index2]))\\n\\n rotamers = rotamers_per_branch[1]\\n for rotamer in rotamers:\\n atom_list_2.append(set([rotamer.index1, rotamer.index2]))\\n\\n EXPECTED_INDICES_1 = [set([9, 10]), set([8, 9]), set([7, 8]),\\n set([6, 7]), set([5, 6]), set([2, 5]),\\n set([0, 2]), set([0, 1])]\\n\\n EXPECTED_INDICES_2 = [set([12, 11]), set([12, 13]), set([13, 14]),\\n set([14, 15]), set([15, 16]), set([16, 17]),\\n set([17, 18]), set([18, 19])]\\n\\n where_1 = list()\\n for atom_pair in atom_list_1:\\n if atom_pair in EXPECTED_INDICES_1:\\n where_1.append(1)\\n elif atom_pair in EXPECTED_INDICES_2:\\n where_1.append(2)\\n else:\\n where_1.append(0)\\n\\n where_2 = list()\\n for atom_pair in atom_list_2:\\n if atom_pair in EXPECTED_INDICES_1:\\n where_2.append(1)\\n elif atom_pair in EXPECTED_INDICES_2:\\n where_2.append(2)\\n else:\\n where_2.append(0)\\n\\n assert (all(i == 1 for i in where_1)\\n and all(i == 2 for i in where_2)) or \\\\\\n (all(i == 2 for i in where_1)\\n and all(i == 1 for i in where_2)), \\\"Invalid rotamer library \\\" + \\\\\\n \\\"{}, {}\\\".format(where_1, where_2)\\n\\n assert (all(i == 1 for i in where_1)\\n and all(i == 2 for i in where_2)\\n and len(where_1) == len(EXPECTED_INDICES_1)\\n and len(where_2) == len(EXPECTED_INDICES_2)) or \\\\\\n (all(i == 2 for i in where_1)\\n and all(i == 1 for i in where_2)\\n and len(where_1) == len(EXPECTED_INDICES_2)\\n and len(where_2) == len(EXPECTED_INDICES_1)), \\\"Unexpected \\\" + \\\\\\n \\\"number of rotamers\\\"\",\n \"def run(prefix):\\n # run_tests.assert_folder_is_empty(prefix=prefix)\\n xrs_good,xrs_poor,f_obs,r_free_flags = run_tests.setup_helix_example()\\n # pdb_inp = os.path.join(qr_unit_tests,\\\"data_files\\\",\\\"2lvr.pdb\\\")\\n r = run_tests.run_cmd(prefix,\\n args = [\\\"restraints=cctbx\\\",\\\"mode=gtest\\\",\\\"g_scan=20\\\",\\\"g_mode=1\\\"],\\n pdb_name = 'm00_poor.pdb', mtz_name='')\\n assert os.path.isfile('1-20.npy')\",\n \"def test_repetition_vector():\\n cosimulations = [\\n example.control.gauss_seidel(1., 5., 1.),\\n example.control.gauss_seidel(1., 5., 1., True),\\n example.control.gauss_seidel(1., 5., 1., True, True),\\n example.control.gauss_seidel(1., 5., 1., False, True),\\n example.control.gauss_jacobi(1., 5., 1.),\\n example.control.multi_rate(1., 5., 1.),\\n ]\\n for cosimulation in cosimulations:\\n sdfg = cs.convert_to_sdf(cosimulation)\\n schedule = sdf.calculate_schedule(sdfg)\\n network, hs, _, _ = cosimulation\\n _, connections = network\\n repetitions = cs.repetition_vector(connections, hs)\\n for agent in sdfg[0]:\\n assert sum(agent == executed for executed in schedule) == repetitions[agent]\",\n \"def run_sims_foreach_allele(params_foreach_allele_dirpath, output_dirpath, start_popsize, max_popsize, gens, trials, seq_error_dirpath, use_norm_approx):\\n\\n ################ hard_coded_parameters ###################\\n #this gives the selection coefficient. These are 'neutral'\\n #simulations, so this is set at 0, but if one wants to \\n #simulate alleles under selection, then change this\\n #accordingly\\n s = 0.0\\n ################ hard_coded_parameters ###################\\n\\n if seq_error_dirpath[-1] != '/':\\n seq_error_dirpath += '/'\\n if output_dirpath[-1] != '/':\\n output_dirpath += '/'\\n if params_foreach_allele_dirpath[-1] != '/':\\n params_foreach_allele_dirpath += '/'\\n if not os.path.exists(output_dirpath):\\n os.makedirs(output_dirpath)\\n\\n #get error rate for each possible amino acid\\n error_rate_dic = estimate_error(seq_error_dirpath)\\n\\n #now get the population size at each\\n #generation\\n pop_sizes = get_pop_sizes(start_popsize, max_popsize, gens)\\n\\n #choose the correct parameter file based upon\\n #the value of the global variable 'SGE_TASK_ID'\\n param_filepaths = []\\n for i in os.listdir(params_foreach_allele_dirpath):\\n if i == 'README' or i[0] == '.':\\n continue\\n param_filepaths.append(params_foreach_allele_dirpath + i)\\n sge_task_id = int(os.environ['SGE_TASK_ID'])\\n param_filepath = param_filepaths[sge_task_id-1]\\n\\n #read in parameters from the parameter\\n #file\\n filein = open(param_filepath, \\\"r\\\")\\n filein.readline()#burn header\\n line = filein.readline()[:-1].split('\\\\t')\\n filein.close()\\n gene = line[0]\\n position = line[1]\\n derived_allele = line[3]\\n rep = line[4]\\n start_allele_freq = line[5]\\n ending_num_reads = line[6]\\n\\n #check if sufficient data in param file\\n if start_allele_freq == 'NA' or ending_num_reads == 'NA':\\n output_filepath = '%s%s_%s_%s_%s' % (output_dirpath, gene, derived_allele, position, rep)\\n fileout = open(output_filepath, \\\"w\\\")\\n fileout.write(\\\"No simulations because start allele freq and/or ending number of reads was 'NA'.\\\\nnull\\\\n\\\")\\n fileout.close()\\n return\\n else:\\n start_allele_freq = float(start_allele_freq)\\n ending_num_reads = float(ending_num_reads)\\n #check if the ending number of reads is zero\\n if ending_num_reads == 0.0:\\n output_filepath = '%s%s_%s_%s_%s' % (output_dirpath, gene, derived_allele, position, rep)\\n fileout = open(output_filepath, \\\"w\\\")\\n fileout.write(\\\"No simulations because the ending number of reads was 0 so the ending allele frequency is undefined.\\\\nnull\\\\n\\\")\\n fileout.close()\\n return\\n\\n #this is the mutation rate that the given allele will mutate\\n #to no longer be that allele\\n error_rate_from = error_rate_dic[derived_allele][0]\\n #this is the mutation rate where other alleles will mutate\\n #to become the given allele\\n error_rate_to = error_rate_dic[derived_allele][1]\\n\\n #define the output filepath based on allele identity\\n output_filepath = '%s%s_%s_%s_%s' % (output_dirpath, gene, derived_allele, position, rep)\\n\\n #run simulation!\\n run_sims(output_filepath, pop_sizes, trials, error_rate_from, error_rate_to, start_allele_freq, ending_num_reads, use_norm_approx, s)\\n\\n return\",\n \"def test_multi_molecules_diff_sizes(self, multi_mol_system_irregular, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_irregular)\\n found = self.sequence_from_system(multi_mol_system_irregular, \\\"test\\\")\\n assert found == expected\",\n \"def test_lsr_pairwise():\\n for case in iter_testcases('pairwise'):\\n n_items = case[\\\"n_items\\\"]\\n data = case[\\\"data\\\"]\\n assert np.allclose(\\n case[\\\"lsr_est\\\"], lsr_pairwise(n_items, data),\\n atol=ATOL, rtol=RTOL)\",\n \"def internal_loop(p, i, j, k, l):\\n return _RNAstructure_wrap.internal_loop(p, i, j, k, l)\",\n \"def test_simulationRun(self):\\n self.opt = { 'temperature' : 300.0, 'friction' : 1, 'dt' : 0.00002,\\n 'nIter' : 2, 'nstepsNC' : 2, 'nstepsMD' : 1, 'nprop' : 1,\\n 'nonbondedMethod' : 'NoCutoff', 'constraints': 'HBonds',\\n 'trajectory_interval' : 1, 'reporter_interval' : 1,\\n 'outfname' : 'mc-test',\\n 'platform' : None,\\n 'constraints' : 'HBonds',\\n 'mc_per_iter' : 2 }\\n\\n structure = self.full_struct\\n class SetRotationMove(RandomLigandRotationMove):\\n def __init__(self, structure, resname='LIG'):\\n super(SetRotationMove, self).__init__(structure, resname)\\n\\n def move(self, context):\\n \\\"\\\"\\\"Function that performs a random rotation about the\\n center of mass of the ligand.\\n \\\"\\\"\\\"\\n #TODO: check if we need to deepcopy\\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\\n\\n self.positions = positions[self.atom_indices]\\n self.center_of_mass = self.getCenterOfMass(self.positions, self.masses)\\n reduced_pos = self.positions - self.center_of_mass\\n\\n # Define random rotational move on the ligand\\n #set rotation so that test is reproducible\\n set_rotation_matrix = np.array([[-0.62297988, -0.17349253, 0.7627558 ],\\n [ 0.55082352, -0.78964857, 0.27027502],\\n [ 0.55541834, 0.58851973, 0.58749893]])\\n\\n\\n #set_rotation_matrix = np.array([[1, 0, 0],\\n # [0, 1, 0],\\n # [0, 0, 1]])\\n\\n #multiply lig coordinates by rot matrix and add back COM translation from origin\\n rot_move = np.dot(reduced_pos, set_rotation_matrix) * positions.unit + self.center_of_mass\\n\\n # Update ligand positions in nc_sim\\n for index, atomidx in enumerate(self.atom_indices):\\n positions[atomidx] = rot_move[index]\\n context.setPositions(positions)\\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\\n self.positions = positions[self.atom_indices]\\n return context\\n\\n\\n self.model = SetRotationMove(structure, resname='ALA')\\n #self.model = RandomLigandRotationMove(structure, resname='ALA')\\n\\n self.model.atom_indices = range(22)\\n self.model.topology = structure[self.model.atom_indices].topology\\n self.model.positions = structure[self.model.atom_indices].positions\\n self.model.calculateProperties()\\n\\n self.mover = MoveEngine(self.model)\\n #Initialize the SimulationFactory object\\n sims = SimulationFactory(structure, self.mover, **self.opt)\\n #print(sims)\\n system = sims.generateSystem(structure, **self.opt)\\n simdict = sims.createSimulationSet()\\n alch_system = sims.generateAlchSystem(system, self.model.atom_indices)\\n self.nc_sim = sims.generateSimFromStruct(structure, self.mover, alch_system, ncmc=True, **self.opt)\\n self.model.calculateProperties()\\n self.initial_positions = self.nc_sim.context.getState(getPositions=True).getPositions(asNumpy=True)\\n mc_sim = Simulation(sims, self.mover, **self.opt)\\n #monkeypatch to access acceptance value\\n def nacceptRejectMC(self, temperature=300, **opt):\\n \\\"\\\"\\\"Function that chooses to accept or reject the proposed move.\\n \\\"\\\"\\\"\\n md_state0 = self.current_state['md']['state0']\\n md_state1 = self.current_state['md']['state1']\\n log_mc = (md_state1['potential_energy'] - md_state0['potential_energy']) * (-1.0/self.nc_sim.context._integrator.kT)\\n randnum = math.log(np.random.random())\\n\\n if log_mc > randnum:\\n self.accept += 1\\n print('MC MOVE ACCEPTED: log_mc {} > randnum {}'.format(log_mc, randnum) )\\n self.md_sim.context.setPositions(md_state1['positions'])\\n else:\\n self.reject += 1\\n print('MC MOVE REJECTED: log_mc {} < {}'.format(log_mc, randnum) )\\n self.md_sim.context.setPositions(md_state0['positions'])\\n self.log_mc = log_mc\\n self.md_sim.context.setVelocitiesToTemperature(self.opt['temperature'])\\n mc_sim.acceptRejectMC = nacceptRejectMC\\n nacceptRejectMC.__get__(mc_sim)\\n mc_sim.acceptRejectMC = types.MethodType(nacceptRejectMC, mc_sim)\\n mc_sim.runMC(self.opt['nIter'])\\n #get log acceptance\\n print(mc_sim.log_mc)\\n #if mc is working, should be around -24.1\\n assert mc_sim.log_mc <= -23.8 and mc_sim.log_mc >= -24.3\",\n \"def test_08(self, test):\\r\\n globalConfig.test = test\\r\\n\\r\\n forbiddenRoutes = []\\r\\n outputList = getOutputList()\\r\\n inputList = getInputList()\\r\\n if len(inputList) == 0 or len(outputList) == 0:\\r\\n return test.UNCLEAR(\\\"Not tested. No resources found.\\\")\\r\\n\\r\\n for outputInstance in outputList:\\r\\n sourceID = outputInstance.getSourceID()\\r\\n for inputInstance in inputList:\\r\\n inputParent = inputInstance.getParent()\\r\\n if inputParent['type'] == \\\"source\\\" and sourceID == inputParent['id']:\\r\\n route = {\\r\\n \\\"input\\\": inputInstance,\\r\\n \\\"output\\\": outputInstance\\r\\n }\\r\\n forbiddenRoutes.append(route)\\r\\n\\r\\n for route in forbiddenRoutes:\\r\\n outputCaps = route['output'].getCaps()\\r\\n msg = (\\\"It is possible to create a loop using re-entrant matrices \\\"\\r\\n \\\"between Input {} and Output {}\\\".format(route['input'].id, route['output'].id))\\r\\n try:\\r\\n routableInputs = outputCaps['routable_inputs']\\r\\n except KeyError:\\r\\n return test.FAIL(\\\"Could not find 'routable_inputs' in /caps \\\"\\r\\n \\\"for Output {}\\\".format(route['output'].id))\\r\\n if routableInputs is None or route['input'].id in routableInputs:\\r\\n return test.FAIL(msg)\\r\\n return test.PASS()\",\n \"def test_perceive_residues_natoms_mainchain_alanine(self, strict_chirality):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/MainChain_ALA.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def main():\\n\\n modulus = lambda c: (c.real*c.real + c.imag*c.imag)\\n test_case = 0\\n while True:\\n try:\\n _r, _i, iterations = input().split()\\n except EOFError:\\n break\\n\\n position = complex(float(_r), float(_i))\\n z_value, outside = complex(0.0, 0.0), False\\n for _ in range(int(iterations)):\\n z_next = z_value * z_value + position\\n outside = (modulus(z_next) > 4)\\n if outside:\\n break\\n z_value = z_next\\n\\n test_case += 1\\n print('Case {0}: {1}'.format(test_case, 'OUT' if outside else 'IN'))\",\n \"def test_parallel_resistors(self):\\r\\n self.assertEqual(calc.evaluator({}, {}, '1||1'), 0.5)\\r\\n self.assertEqual(calc.evaluator({}, {}, '1||1||2'), 0.4)\\r\\n self.assertEqual(calc.evaluator({}, {}, \\\"j||1\\\"), 0.5 + 0.5j)\",\n \"def test_template_forloop(self):\\n print \\\"Running: %s - %s\\\" % (self.id(), self.shortDescription())\\n # compare sequence items\\n for i in range(0, 3):\\n input_item = g.config['templates']['sequence'][i]\\n output_item = self.output_config['out_templates']['sequence'][i]\\n\\n self.assertEqual(input_item, output_item,\\n 'sequence items (%i) do not match' % i)\",\n \"def test_ok_mm_primer(self):\\r\\n primers = ['AAAA', 'GGGG']\\r\\n self.assertEqual(ok_mm_primer('AAAA', primers, 0), True)\\r\\n self.assertEqual(ok_mm_primer('AAAA', primers, 3), True)\\r\\n self.assertEqual(ok_mm_primer('CCCC', primers, 0), False)\\r\\n self.assertEqual(ok_mm_primer('CCCA', primers, 3), True)\\r\\n self.assertEqual(ok_mm_primer('CCCA', primers, 2), False)\\r\\n self.assertEqual(ok_mm_primer('CCGG', primers, 2), True)\\r\\n self.assertEqual(ok_mm_primer('CCGA', primers, 2), False)\",\n \"def build_set(ls, dsets):\\n\\n def noh(ls, dsets):\\n \\\"\\\"\\\"\\n This function remove hydrogens from the selection\\n \\\"\\\"\\\"\\n data_set = build_set(ls[1], dsets)\\n\\n noh_set = set()\\n pred = oechem.OEIsHydrogen()\\n\\n for idx in data_set:\\n atom = system.GetAtom(oechem.OEHasAtomIdx(idx))\\n if not pred(atom):\\n noh_set.add(idx)\\n\\n return noh_set\\n\\n def residues(ls):\\n \\\"\\\"\\\"\\n This function select residues based on the residue numbers. An example of\\n selection can be:\\n mask = 'resid A:16 17 19 B:1'\\n \\\"\\\"\\\"\\n # List residue atom index to be restrained\\n res_atom_set = set()\\n\\n # Dictionary of lists with the chain residues selected to be restrained\\n # e.g. {chainA:[res1, res15], chainB:[res19, res17]}\\n chain_dic = {'': []}\\n\\n # Fill out the chain dictionary\\n i = 0\\n while i < len(ls):\\n if ls[i].isdigit():\\n chain_dic[''].append(int(ls[i]))\\n i += 1\\n else:\\n try:\\n chain_dic[ls[i]].append(int(ls[i + 2]))\\n except:\\n chain_dic[ls[i]] = []\\n chain_dic[ls[i]].append(int(ls[i + 2]))\\n i += 3\\n\\n # Loop over the molecular system to select the atom indexes to be selected\\n hv = oechem.OEHierView(system, oechem.OEAssumption_BondedResidue + oechem.OEAssumption_ResPerceived)\\n for chain in hv.GetChains():\\n chain_id = chain.GetChainID()\\n if chain_id not in chain_dic:\\n continue\\n for frag in chain.GetFragments():\\n for hres in frag.GetResidues():\\n res_num = hres.GetOEResidue().GetResidueNumber()\\n if res_num not in chain_dic[chain_id]:\\n continue\\n for oe_at in hres.GetAtoms():\\n res_atom_set.add(oe_at.GetIdx())\\n\\n return res_atom_set\\n\\n def around(dist, ls):\\n \\\"\\\"\\\"\\n This function select atom not far than the threshold distance from\\n the current selection. The threshold distance is in Angstrom\\n\\n selection can be:\\n mask = '5.0 around ligand'\\n \\\"\\\"\\\"\\n # at = system.GetAtom(oechem.OEHasAtomIdx(idx))\\n\\n # Atom set selection\\n atom_set_around = set()\\n\\n # Create a OE bit vector mask for each atoms\\n bv_around = oechem.OEBitVector(system.GetMaxAtomIdx())\\n\\n # Set the mask atom\\n for at in system.GetAtoms():\\n if at.GetIdx() in ls:\\n bv_around.SetBitOn(at.GetIdx())\\n\\n # Predicate\\n pred = oechem.OEAtomIdxSelected(bv_around)\\n\\n # Create the system molecule based on the atom mask\\n molecules = oechem.OEMol()\\n oechem.OESubsetMol(molecules, system, pred)\\n\\n # Create the Nearest neighbours\\n nn = oechem.OENearestNbrs(system, float(dist))\\n\\n for nbrs in nn.GetNbrs(molecules):\\n for atom in oechem.OEGetResidueAtoms(nbrs.GetBgn()):\\n if atom.GetIdx() in ls:\\n continue\\n atom_set_around.add(atom.GetIdx())\\n\\n return atom_set_around\\n\\n # Start Body of the selection function by language\\n\\n # Terminal Literal return the related set\\n if isinstance(ls, str):\\n return dsets[ls]\\n # Not or Noh\\n if len(ls) == 2:\\n if ls[0] == 'noh': # Noh case\\n return noh(ls, dsets)\\n elif ls[0] == 'not': # Not case\\n return dsets['system'] - build_set(ls[1], dsets)\\n else: # Resid case with one index\\n return residues(ls[1])\\n\\n if len(ls) == 3:\\n if ls[1] == 'or': # Or Case (set union)\\n return build_set(ls[0], dsets) | build_set(ls[2], dsets)\\n elif ls[1] == 'and': # And Case (set intersection)\\n return build_set(ls[0], dsets) & build_set(ls[2], dsets)\\n elif ls[1] == 'diff': # Diff case (set difference)\\n return build_set(ls[0], dsets) - build_set(ls[2], dsets)\\n elif ls[1] == 'around': # Around case\\n return around(ls[0], build_set(ls[2], dsets))\\n else:\\n return residues(ls[1:]) # Resid case with one or two indexes\\n else:\\n if ls[0] == 'resid':\\n return residues(ls[1:]) # Resid case with multiple indexes\\n else:\\n raise ValueError(\\\"The passed list have too many tokens: {}\\\".format(ls))\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.81529486","0.7770318","0.7552308","0.6837369","0.674307","0.64884526","0.6445583","0.63936305","0.6344969","0.6327929","0.6228372","0.62093467","0.600957","0.600777","0.59746706","0.59265643","0.59220964","0.5913016","0.5843478","0.5786151","0.57159615","0.56807727","0.5625538","0.5554309","0.5548607","0.5540687","0.549996","0.5496272","0.54451805","0.5388143","0.5370463","0.5361352","0.5360192","0.5338594","0.528698","0.52773064","0.52430755","0.5229965","0.52143705","0.518449","0.51511014","0.5149214","0.5131076","0.5116267","0.5112088","0.5067833","0.50673205","0.5061814","0.5002804","0.49931028","0.49911898","0.496752","0.49483106","0.48976454","0.48827735","0.48697168","0.4863642","0.48611203","0.48517773","0.48404822","0.48380473","0.48247078","0.48225388","0.48148704","0.48114464","0.48068488","0.47923756","0.4786742","0.47821558","0.47782645","0.47751778","0.47748408","0.476773","0.47672987","0.47584593","0.47453806","0.47382137","0.47265646","0.4705853","0.47009864","0.4686668","0.46829948","0.46768412","0.46735716","0.4659582","0.46582213","0.46555677","0.46529537","0.46516097","0.46493986","0.4645552","0.46437606","0.46369123","0.46346718","0.46327996","0.4631565","0.46278232","0.46253476","0.46167725","0.46125627"],"string":"[\n \"0.81529486\",\n \"0.7770318\",\n \"0.7552308\",\n \"0.6837369\",\n \"0.674307\",\n \"0.64884526\",\n \"0.6445583\",\n \"0.63936305\",\n \"0.6344969\",\n \"0.6327929\",\n \"0.6228372\",\n \"0.62093467\",\n \"0.600957\",\n \"0.600777\",\n \"0.59746706\",\n \"0.59265643\",\n \"0.59220964\",\n \"0.5913016\",\n \"0.5843478\",\n \"0.5786151\",\n \"0.57159615\",\n \"0.56807727\",\n \"0.5625538\",\n \"0.5554309\",\n \"0.5548607\",\n \"0.5540687\",\n \"0.549996\",\n \"0.5496272\",\n \"0.54451805\",\n \"0.5388143\",\n \"0.5370463\",\n \"0.5361352\",\n \"0.5360192\",\n \"0.5338594\",\n \"0.528698\",\n \"0.52773064\",\n \"0.52430755\",\n \"0.5229965\",\n \"0.52143705\",\n \"0.518449\",\n \"0.51511014\",\n \"0.5149214\",\n \"0.5131076\",\n \"0.5116267\",\n \"0.5112088\",\n \"0.5067833\",\n \"0.50673205\",\n \"0.5061814\",\n \"0.5002804\",\n \"0.49931028\",\n \"0.49911898\",\n \"0.496752\",\n \"0.49483106\",\n \"0.48976454\",\n \"0.48827735\",\n \"0.48697168\",\n \"0.4863642\",\n \"0.48611203\",\n \"0.48517773\",\n \"0.48404822\",\n \"0.48380473\",\n \"0.48247078\",\n \"0.48225388\",\n \"0.48148704\",\n \"0.48114464\",\n \"0.48068488\",\n \"0.47923756\",\n \"0.4786742\",\n \"0.47821558\",\n \"0.47782645\",\n \"0.47751778\",\n \"0.47748408\",\n \"0.476773\",\n \"0.47672987\",\n \"0.47584593\",\n \"0.47453806\",\n \"0.47382137\",\n \"0.47265646\",\n \"0.4705853\",\n \"0.47009864\",\n \"0.4686668\",\n \"0.46829948\",\n \"0.46768412\",\n \"0.46735716\",\n \"0.4659582\",\n \"0.46582213\",\n \"0.46555677\",\n \"0.46529537\",\n \"0.46516097\",\n \"0.46493986\",\n \"0.4645552\",\n \"0.46437606\",\n \"0.46369123\",\n \"0.46346718\",\n \"0.46327996\",\n \"0.4631565\",\n \"0.46278232\",\n \"0.46253476\",\n \"0.46167725\",\n \"0.46125627\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8213552"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81494,"cells":{"query":{"kind":"string","value":"Test the proper operation of the residue loop when no data is present. The function tested is pipe_control.mol_res_spin.residue_loop()."},"document":{"kind":"string","value":"def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def test_residue_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for residue in mol_res_spin.residue_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_residue_loop(self):\n\n # Loop over the residues.\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\n # Test the selection.\n self.assertEqual(res.num, 2)\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)","def test_molecule_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for molecule in mol_res_spin.molecule_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_molecule_loop_no_selection(self):\n\n # Molecule data.\n name = ['Ap4Aase', 'RNA']\n\n # Loop over the molecules.\n i = 0\n for mol in mol_res_spin.molecule_loop():\n # Test the molecule names.\n self.assertEqual(mol.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)","def test_spin_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for spin in mol_res_spin.spin_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_molecule_loop(self):\n\n # Loop over the molecules.\n for mol in mol_res_spin.molecule_loop('#RNA'):\n # Test the molecule name.\n self.assertEqual(mol.name, 'RNA')\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def test_return_residue_pipe_fail(self):\n\n # Try to get a residue from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')","def test_spin_loop_no_selection(self):\n\n # Spin data.\n select = [0, 1, 0, 0, 1, 1, 0, 1]\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 8)","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_return_residue(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_residue(':1')\n res2 = mol_res_spin.return_residue(selection=':2')\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\n\n # Test the data of residue 1.\n self.assertEqual(res1.num, 1)\n self.assertEqual(res1.name, None)\n\n # Test the data of residue 2.\n self.assertEqual(res2.num, 2)\n self.assertEqual(res2.name, 'Glu')\n\n # Test the data of residue 4.\n self.assertEqual(res4.num, 4)\n self.assertEqual(res4.name, 'Pro')\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5.num, -5)\n self.assertEqual(res5.name, None)\n self.assertEqual(res5.spin[1].name, 'N5')","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_spin_loop(self):\n\n # Spin data.\n select = [1, 0]\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, 'N5')\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 2)","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_return_single_residue_info(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_single_residue_info('1')\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\n res5 = mol_res_spin.return_single_residue_info('-5')\n\n # Test the data of residue 1.\n self.assertEqual(res1, (1, None))\n\n # Test the data of residue 2.\n self.assertEqual(res2, (2, 'Glu'))\n\n # Test the data of residue 4.\n self.assertEqual(res4, (4, 'Pro'))\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5, (-5, None))","def test_spin_loop_multiatom(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_return_single_residue_info_fail(self):\n\n # Ask for a few residues.\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')","def test_empty_with_filter(multi_mol_system_irregular):\n sequence = \"not empty\"\n processor = dssp.AnnotateResidues(\n \"test\", sequence, molecule_selector=lambda mol: False\n )\n with pytest.raises(ValueError):\n processor.run_system(multi_mol_system_irregular)","def test_run_molecule_not_selected(self, single_mol_system):\n sequence = \"ABCDE\"\n processor = dssp.AnnotateResidues(\n \"test\", sequence, molecule_selector=lambda mol: False\n )\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert vermouth.utils.are_all_equal(found)\n assert found[0] is None","def test_spin_loop_wildcard(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N*'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_wrong_length(multi_mol_system_irregular, sequence):\n processor = dssp.AnnotateResidues(\"test\", sequence)\n with pytest.raises(ValueError):\n processor.run_system(multi_mol_system_irregular)","def test_empty_system_empty_sequence():\n system = vermouth.system.System()\n sequence = \"\"\n processor = dssp.AnnotateResidues(\"test\", sequence)\n try:\n processor.run_system(system)\n except ValueError:\n pytest.fail(\"Should not have raised a ValueError.\")","def test_RUMI():\r\n\r\n start = 11051\r\n end = 11902\r\n read_poems(start, end)","def check_residue_callback(self):\n\n if not self.check_for_residue_existance():\n return\n\n self.listbox_current_designs.delete(0, END)\n self.current_residueFull = self.current_residue.get().split(\":\")\n\n if len(self.current_residueFull) > 1:\n self.listbox_restypes.delete(9)\n self.listbox_restypes.insert(9, \"Conserved\")\n else:\n res = self.current_residueFull[0] +\":\"+self.current_chain.get()\n #print res\n if not self.pose.total_residue():\n return\n\n resType = self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get()))\n try:\n resName = self.pose.residue(resType).name()\n except PyRosettaException:\n print \"Residue does not exist in PDB...\"\n return\n\n\n self.current_residue_name_full.set(resName)\n three_letter_name = resName.split(\"_\")[0]; #Fix for Rosetta designated chain endings, His_d\n self.current_residue_name.set(resName)\n\n #Fix for not having data for certain residue types:\n try:\n self.design_accessible_sa.set(self.residue_definitions.resinfo[three_letter_name][0])\n self.design_relative_mutability.set(self.residue_definitions.resinfo[three_letter_name][1])\n self.design_surface_probability.set(self.residue_definitions.resinfo[three_letter_name][2])\n except KeyError:\n print \"No Data for restype\"\n self.design_accessible_sa.set(\"\")\n self.design_relative_mutability.set(\"\")\n self.design_surface_probability.set(\"\")\n\n con = \"Conserved:\" +three_letter_name\n self.listbox_restypes.delete(9)\n self.listbox_restypes.insert(9, con)\n if self.DesignDic.has_key(res):\n for residues in self.DesignDic[res]:\n self.listbox_current_designs.insert(END, residues)","def test_return_molecule_pipe_fail(self):\n\n # Try to get a molecule from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')","def test_empty_system_error():\n system = vermouth.system.System()\n sequence = \"not empty\"\n processor = dssp.AnnotateResidues(\"test\", sequence)\n with pytest.raises(ValueError):\n processor.run_system(system)","def test_multi_molecules_cycle_one(self, multi_mol_system_irregular):\n sequence = \"A\"\n expected = [sequence] * (15 * 3)\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_irregular)\n found = self.sequence_from_system(multi_mol_system_irregular, \"test\")\n assert found == expected","def test_single_molecules_cycle_one(self, single_mol_system):\n sequence = \"A\"\n expected = [sequence] * (5 * 3)\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def test_return_spin_pipe_fail(self):\n\n # Try to get a spin from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')","def check_residue(self, chain_id, resid, resname):\n if resname in PTM_lookup.keys():\n return\n else:\n try:\n ref_resname = PTM_reverse_lookup[resname]\n except KeyError:\n # print \"skipping unrecognized residue\", resname\n return\n ptm_dict = PTM_lookup[ref_resname][resname]\n return (chain_id, resid, ref_resname, ptm_dict[\"goto_atom\"], ptm_dict[\"name\"])","def test_count_spins_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Test for the error.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.count_spins)","def test_run_loop_success(self):\n found = False\n pyint = Interpreter(limit=15)\n try:\n pyint.run(code=BF_CODE_LOOP_TWICE)\n except SystemExit: \n found = True\n self.assertFalse(found)","def test_run_molecule(self, single_mol_system):\n sequence = \"ABCDE\"\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def test_count_no_spins(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 0)","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def test_multi_molecules_cycle(self, multi_mol_system_regular, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n expected = expected * 3\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_regular)\n found = self.sequence_from_system(multi_mol_system_regular, \"test\")\n assert found == expected","def test_perceive_residues_natoms_mainchain_arginine(self, strict_chirality):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/MainChain_ARG.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def check_for_residue_existance(self):\n if not self.pose.total_residue():\n print \"No pose Loaded.\"\n return False\n\n if not self.current_chain.get() or not self.current_residue.get():\n print \"Chain or residue not set\"\n return False\n\n current_region = self.current_residue.get().split(\":\")\n if len(current_region)>1:\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\n\n\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\n print \"Region not found in pose\"\n return False\n else:\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\n\n print \"Residue not found in pose\"\n return False\n\n #If everythig is good then:\n return True","def residual(pars, data= None):\n\n\t\t\tresid = np.array([])\n\n\n\t\t\t# make residual per data set\n\n\t\t\tfor N in range(n_annulus):\n\n\t\t\t\tmdl_ev = 0\n\t\t\t\tr_space_k = rings_pos[N+1] - rings_pos[N] \n\t\t\t\tmask = np.where( (r_n >= rings_pos[N] ) & (r_n < rings_pos[N+1]) )\n\t\t\t\tx,y = XY_mesh[0][mask], XY_mesh[1][mask] \n\t\t\t\tXY = (x,y)\n\n\n\n\n\t\t\t\tfor kk in range(2):\n\t\t\t\t\tVxy,Vsys = vmodel_dataset(pars, N+kk, XY, r_0 = rings_pos[N], r_space = r_space_k )\n\n\t\t\t\t\tmdl_ev = mdl_ev + Vxy[kk]\n\n\n\t\t\t\t\tif N == 0 and kk == 0:\n\t\t\t\t\t\t\n\t\t\t\t\t\tmask1 = np.where( (r_n < rings_pos[0] ) )\n\t\t\t\t\t\tx1,y1 = XY_mesh[0][mask1], XY_mesh[1][mask1] \n\t\t\t\t\t\tXY1 = (x1,y1)\n\n\n\t\t\t\t\t\t#\n\t\t\t\t\t\t#\n\t\t\t\t\t\t# inner interpolation\n\t\t\t\t\t\t#\n\t\t\t\t\t\t#\n\t\t\t\t\t\n\t\t\t\t\t\t#(a) velocity rise linearly from zero\n\n\t\t\t\t\t\tr_space_0 = rings_pos[0]\n\t\t\t\t\t\tVxy,Vsys = vmodel_dataset(pars, 0, XY1, r_0 = 0, r_space = r_space_0)\n\t\t\t\t\t\n\t\t\t\t\t\tinterp_model[mask1] = Vxy[1] + Vsys\n\n\t\t\t\tinterp_model[mask] = mdl_ev + Vsys\n\n\n\n\n\t\t\t\n\t\t\tsigma = np.sqrt(e_vel_map**2 + e_ISM**2)\n\t\t\t#interp_model[interp_model == 0] = np.nan\n\n\n\t\t\tconvolved = 0\n\n\t\t\tif convolved == True:\n\n\t\t\t\tmy_beam = Beam(2.5*u.arcsec, 2.5*u.arcsec, 0*u.deg)\n\t\t\t\tpix_scale = pixel_scale * u.arcsec\n\t\t\t\tgauss_kern = my_beam.as_kernel(pix_scale, x_size = nx, y_size = ny)\n\n\n\t\t\t\textend = np.zeros((3*ny,3*nx))\n\t\t\t\textend[ny:2*ny,nx:2*nx] = interp_model\n\t\t\t\tconvolve_extend = convolve_fft(extend, gauss_kern, mask = extend == 0 )\n\t\t\t\tinterp_model_conv = convolve_extend[ny:2*ny,nx:2*nx]\n\t\t\t\tinterp_model_conv[interp_model == 0] = 0\n\n\n\n\n\t\t\telse:\n\t\t\t\tinterp_model_conv = interp_model\n\n\t\t\tinterp_model_conv[interp_model_conv == 0] = np.nan\n\t\t\tres = vel_map - interp_model_conv\n\t\t\tResid = res/sigma\n\n\n\t\t\treturn Resid.flatten()","def test_78_continue(self):\n\t\tinput = \"\"\"procedure main(); var x:integer;\n\t\tbegin while(true)do begin\n\t\twith x:integer; do with x:real; do begin\n\t\t\tif (x>0) then continue;\n\t\t\twith x:integer; do if (x=0) then return;\n\t\tend{with} continue; end{while} continue; end\"\"\"\n\t\texpect = \"Continue Not In Loop\"\n\t\tself.assertTrue(TestChecker.test(input,expect,478))","def test_single_molecule(self, single_mol_system, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def test_perceive_residues_natoms_mainchain_charged_glutamic_acid(\n self, strict_chirality\n ):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/MainChain_GLH.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def test_boolean_and_selection(self):\n\n # The selection loop:\n sel = list(mol_res_spin.residue_loop(\"#Ap4Aase:4 & :Pro\"))\n\n # Test:\n self.assertEqual(len(sel), 1)\n for res in sel:\n self.assert_(res.name == \"Pro\" and res.num == 4)","def test_boolean_complex_selection(self):\n\n # The residue selection loop.\n sel = list(mol_res_spin.residue_loop(\"#Ap4Aase:4 & :Pro | #RNA\"))\n\n # Residue names and numbers.\n names = ['Pro', None, None]\n numbers = [4, -5, -4]\n\n # The residues.\n self.assertEqual(len(sel), 3)\n for i in range(3):\n self.assertEqual(sel[i].name, names[i])\n self.assertEqual(sel[i].num, numbers[i])","def residual(pars, data= None):\n\n\t\t\tresid = np.array([])\n\n\n\t\t\t# make residual per data set\n\n\t\t\tfor N in range(n_annulus):\n\n\t\t\t\tmdl_ev = 0\n\t\t\t\tr_space_k = rings_pos[N+1] - rings_pos[N] \n\t\t\t\tmask = np.where( (r_n >= rings_pos[N] ) & (r_n < rings_pos[N+1]) )\n\t\t\t\tx,y = XY_mesh[0][mask], XY_mesh[1][mask] \n\t\t\t\tXY = (x,y)\n\n\n\n\n\t\t\t\tfor kk in range(2):\n\t\t\t\t\tVxy,Vsys = vmodel_dataset(pars, N+kk, XY, r_0 = rings_pos[N], r_space = r_space_k)\n\n\t\t\t\t\tmdl_ev = mdl_ev + Vxy[kk]\n\n\n\t\t\t\t\tif N == 0 and kk == 0:\n\t\t\t\t\t\t\n\t\t\t\t\t\tmask1 = np.where( (r_n < rings_pos[0] ) )\n\t\t\t\t\t\tx1,y1 = XY_mesh[0][mask1], XY_mesh[1][mask1] \n\t\t\t\t\t\tXY1 = (x1,y1)\n\n\n\t\t\t\t\t\t#\n\t\t\t\t\t\t#\n\t\t\t\t\t\t# inner interpolation\n\t\t\t\t\t\t#\n\t\t\t\t\t\t#\n\t\t\t\t\t\n\t\t\t\t\t\t#(a) velocity rise linearly from zero\n\n\t\t\t\t\t\tr_space_0 = rings_pos[0]\n\t\t\t\t\t\tVxy,Vsys = vmodel_dataset(pars, 0, XY1, r_0 = 0, r_space = r_space_0)\n\t\t\t\t\t\n\t\t\t\t\t\tinterp_model[mask1] = Vxy[1] + Vsys\n\n\t\t\t\tinterp_model[mask] = mdl_ev + Vsys\n\n\n\n\n\t\t\t\n\t\t\tsigma = np.sqrt(e_vel_map**2 + e_ISM**2)\n\n\n\n\t\t\tconvolved = 0\n\n\t\t\tif convolved == True:\n\n\t\t\t\tmy_beam = Beam(2.5*u.arcsec, 2.5*u.arcsec, 0*u.deg)\n\t\t\t\tpix_scale = pixel_scale * u.arcsec\n\t\t\t\tgauss_kern = my_beam.as_kernel(pix_scale, x_size = nx, y_size = ny)\n\n\n\t\t\t\textend = np.zeros((3*ny,3*nx))\n\t\t\t\textend[ny:2*ny,nx:2*nx] = interp_model\n\t\t\t\tconvolve_extend = convolve_fft(extend, gauss_kern, mask = extend == 0 )\n\t\t\t\tinterp_model_conv = convolve_extend[ny:2*ny,nx:2*nx]\n\t\t\t\tinterp_model_conv[interp_model == 0] = 0\n\n\n\t\t\telse:\n\t\t\t\tinterp_model_conv = interp_model\n\n\n\t\t\tinterp_model_conv[interp_model_conv == 0] = np.nan\n\t\t\tres = vel_map - interp_model_conv\n\t\t\tResid = res/sigma\n\n\t\t\treturn Resid.flatten()","def residual(pars, data= None):\n\n\t\t\tresid = np.array([])\n\n\n\t\t\t# make residual per data set\n\n\t\t\tfor N in range(n_annulus):\n\n\t\t\t\tmdl_ev = 0\n\t\t\t\tr_space_k = rings_pos[N+1] - rings_pos[N] \n\t\t\t\tmask = np.where( (r_n >= rings_pos[N] ) & (r_n < rings_pos[N+1]) )\n\t\t\t\tx,y = XY_mesh[0][mask], XY_mesh[1][mask] \n\t\t\t\tXY = (x,y)\n\n\n\n\n\t\t\t\tfor kk in range(2):\n\t\t\t\t\tVxy,Vsys = vmodel_dataset(pars, N+kk, XY, r_0 = rings_pos[N], r_space = r_space_k)\n\n\t\t\t\t\tmdl_ev = mdl_ev + Vxy[kk]\n\n\n\t\t\t\t\tif N == 0 and kk == 0:\n\t\t\t\t\t\t\n\t\t\t\t\t\tmask1 = np.where( (r_n < rings_pos[0] ) )\n\t\t\t\t\t\tx1,y1 = XY_mesh[0][mask1], XY_mesh[1][mask1] \n\t\t\t\t\t\tXY1 = (x1,y1)\n\n\n\t\t\t\t\t\t#\n\t\t\t\t\t\t#\n\t\t\t\t\t\t# inner interpolation\n\t\t\t\t\t\t#\n\t\t\t\t\t\t#\n\t\t\t\t\t\n\t\t\t\t\t\t#(a) velocity rise linearly from zero\n\n\t\t\t\t\t\tr_space_0 = rings_pos[0]\n\t\t\t\t\t\tVxy,Vsys = vmodel_dataset(pars, 0, XY1, r_0 = 0, r_space = r_space_0)\n\t\t\t\t\t\n\t\t\t\t\t\tinterp_model[mask1] = Vxy[1] + Vsys\n\n\t\t\t\tinterp_model[mask] = mdl_ev + Vsys\n\n\n\n\n\t\t\t\n\t\t\tsigma = np.sqrt(e_vel_map**2 + e_ISM**2)\n\n\n\n\t\t\tconvolved = 0\n\n\t\t\tif convolved == True:\n\n\t\t\t\tmy_beam = Beam(2.5*u.arcsec, 2.5*u.arcsec, 0*u.deg)\n\t\t\t\tpix_scale = pixel_scale * u.arcsec\n\t\t\t\tgauss_kern = my_beam.as_kernel(pix_scale, x_size = nx, y_size = ny)\n\n\n\t\t\t\textend = np.zeros((3*ny,3*nx))\n\t\t\t\textend[ny:2*ny,nx:2*nx] = interp_model\n\t\t\t\tconvolve_extend = convolve_fft(extend, gauss_kern, mask = extend == 0 )\n\t\t\t\tinterp_model_conv = convolve_extend[ny:2*ny,nx:2*nx]\n\t\t\t\tinterp_model_conv[interp_model == 0] = 0\n\n\n\t\t\telse:\n\t\t\t\tinterp_model_conv = interp_model\n\n\t\t\tinterp_model[interp_model == 0] = np.nan\n\t\t\tres = vel_map - interp_model_conv\n\t\t\tResid = res/sigma\n\n\n\n\t\t\treturn Resid.flatten()","def residual(pars, data= None):\n\n\t\t\tresid = np.array([])\n\n\n\t\t\t# make residual per data set\n\n\t\t\tfor N in range(n_annulus):\n\n\t\t\t\tmdl_ev = 0\n\t\t\t\tr_space_k = rings_pos[N+1] - rings_pos[N] \n\t\t\t\tmask = np.where( (r_n >= rings_pos[N] ) & (r_n < rings_pos[N+1]) )\n\t\t\t\tx,y = XY_mesh[0][mask], XY_mesh[1][mask] \n\t\t\t\tXY = (x,y)\n\n\n\n\n\t\t\t\tfor kk in range(2):\n\t\t\t\t\tVxy,Vsys = vmodel_dataset(pars, N+kk, XY, r_0 = rings_pos[N], r_space = r_space_k)\n\n\t\t\t\t\tmdl_ev = mdl_ev + Vxy[kk]\n\n\n\t\t\t\t\tif N == 0 and kk == 0:\n\t\t\t\t\t\t\n\t\t\t\t\t\tmask1 = np.where( (r_n < rings_pos[0] ) )\n\t\t\t\t\t\tx1,y1 = XY_mesh[0][mask1], XY_mesh[1][mask1] \n\t\t\t\t\t\tXY1 = (x1,y1)\n\n\n\t\t\t\t\t\t#\n\t\t\t\t\t\t#\n\t\t\t\t\t\t# inner interpolation\n\t\t\t\t\t\t#\n\t\t\t\t\t\t#\n\t\t\t\t\t\n\t\t\t\t\t\t#(a) velocity rise linearly from zero\n\n\t\t\t\t\t\tr_space_0 = rings_pos[0]\n\t\t\t\t\t\tVxy,Vsys = vmodel_dataset(pars, 0, XY1, r_0 = 0, r_space = r_space_0)\n\t\t\t\t\t\n\t\t\t\t\t\tinterp_model[mask1] = Vxy[1] + Vsys\n\n\t\t\t\tinterp_model[mask] = mdl_ev + Vsys\n\n\n\n\n\t\t\t\n\t\t\tsigma = np.sqrt(e_vel_map**2 + e_ISM**2)\n\n\n\n\t\t\tconvolved = 0\n\n\t\t\tif convolved == True:\n\n\t\t\t\tmy_beam = Beam(2.5*u.arcsec, 2.5*u.arcsec, 0*u.deg)\n\t\t\t\tpix_scale = pixel_scale * u.arcsec\n\t\t\t\tgauss_kern = my_beam.as_kernel(pix_scale, x_size = nx, y_size = ny)\n\n\n\t\t\t\textend = np.zeros((3*ny,3*nx))\n\t\t\t\textend[ny:2*ny,nx:2*nx] = interp_model\n\t\t\t\tconvolve_extend = convolve_fft(extend, gauss_kern, mask = extend == 0 )\n\t\t\t\tinterp_model_conv = convolve_extend[ny:2*ny,nx:2*nx]\n\t\t\t\tinterp_model_conv[interp_model == 0] = 0\n\n\n\t\t\telse:\n\t\t\t\tinterp_model_conv = interp_model\n\n\n\t\t\tinterp_model_conv[interp_model_conv == 0] = np.nan\n\t\t\tres = vel_map - interp_model_conv\n\t\t\tResid = res/sigma\n\n\n\t\t\treturn Resid.flatten()","def algorithm_loop(self):","def test_return_molecule(self):\n\n # Ask for a few molecules.\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\n\n # Test the data of molecule 1.\n self.assertEqual(mol1.name, 'Ap4Aase')\n\n # Test the data of molecule 2.\n self.assertEqual(mol2.name, 'RNA')","def test_wrong_length_with_filter(multi_mol_system_irregular, sequence):\n # We exclude the second molecule. The filter excludes it based on the\n # number of nodes, which is 15 because it has 5 residues with 3 nodes\n # each.\n processor = dssp.AnnotateResidues(\n \"test\",\n sequence,\n molecule_selector=lambda mol: len(mol.nodes) != (5 * 3),\n )\n with pytest.raises(ValueError):\n processor.run_system(multi_mol_system_irregular)","def is_standard_residue(self):\n return False","def test_setup_explicit_solvation_system():\n with mmtools.utils.temporary_directory() as tmp_dir:\n yaml_script = get_template_script(tmp_dir)\n del yaml_script['experiments']\n exp_builder = ExperimentBuilder(yaml_script)\n output_dir = os.path.dirname(\n exp_builder._db.get_system('hydration-system')[0].position_path)\n\n # Test that output file exists and that it has correct components\n expected_resnames = {'solvent1': set(['TOL', 'WAT']), 'solvent2': set(['TOL'])}\n for phase in expected_resnames:\n found_resnames = set()\n pdb_path = os.path.join(output_dir, phase + '.pdb')\n prmtop_path = os.path.join(output_dir, phase + '.prmtop')\n inpcrd_path = os.path.join(output_dir, phase + '.inpcrd')\n\n with open(pdb_path, 'r') as f:\n for line in f:\n if len(line) > 10 and line[:5] != 'CRYST':\n found_resnames.add(line[17:20])\n\n assert os.path.exists(prmtop_path)\n assert os.path.exists(inpcrd_path)\n assert os.path.getsize(prmtop_path) > 0\n assert os.path.getsize(inpcrd_path) > 0\n assert found_resnames == expected_resnames[phase]","def test_nothing_perceived_dipeptide(self):\n from openff.toolkit._tests.create_molecules import dipeptide as create_dipeptide\n\n dipeptide = create_dipeptide()\n\n with pytest.raises(KeyError):\n assert dipeptide.atoms[0].metadata[\"residue_name\"] is None\n with pytest.raises(KeyError):\n assert \"ALA\" == dipeptide.atoms[10].metadata[\"residue_name\"]\n with pytest.raises(KeyError):\n assert 1 == dipeptide.atoms[10].metadata[\"residue_number\"]\n with pytest.raises(KeyError):\n assert \" \" == dipeptide.atoms[10].metadata[\"insertion_code\"]\n with pytest.raises(AttributeError):\n dipeptide.residues[0]","def test_rsp_invalid(self):\n\n def handle(event):\n ds = Dataset()\n ds.PatientName = \"Test^test\"\n return 0x0000, ds\n\n self.ae = ae = AE()\n ae.acse_timeout = 5\n ae.dimse_timeout = 0.4\n ae.network_timeout = 5\n ae.add_supported_context(ModalityPerformedProcedureStep)\n scp = ae.start_server(\n (\"localhost\", 11112), block=False, evt_handlers=[(evt.EVT_N_SET, handle)]\n )\n\n ae.add_requested_context(ModalityPerformedProcedureStep)\n assoc = ae.associate(\"localhost\", 11112)\n assert assoc.is_established\n\n class DummyResponse:\n is_valid_response = False\n\n class DummyDIMSE:\n msg_queue = queue.Queue()\n gotten = False\n\n def send_msg(*args, **kwargs):\n return\n\n def get_msg(self, *args, **kwargs):\n if not self.gotten:\n self.gotten = True\n return None, DummyResponse()\n return None, None\n\n assoc._reactor_checkpoint.clear()\n while not assoc._is_paused:\n time.sleep(0.01)\n assoc.dimse = DummyDIMSE()\n mod_list = Dataset()\n mod_list.PatientName = \"Test^test\"\n status, ds = assoc.send_n_set(\n mod_list, ModalityPerformedProcedureStep, \"1.2.840.10008.5.1.1.40.1\"\n )\n\n assert status == Dataset()\n assert ds is None\n assert assoc.is_aborted\n\n scp.shutdown()","def test_perceive_residues_natoms_mainchain_glutamic_acid(self, strict_chirality):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/MainChain_GLU.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def _loop_raw(raw):\n raise NotImplemented","def assignResonanceResidue(resonance, residue):\n\n\n #print 'assignResonanceResidue', makeResonanceGuiName(resonance), residue.seqId\n if residue:\n # we could be setting the residue to None\n if not setAssignmentMolSystem(residue, resonance=resonance):\n return\n \n resonanceSet = resonance.resonanceSet\n if resonanceSet:\n assignNames = set()\n \n for atomSet in resonanceSet.atomSets:\n assignNames.add(atomSet.name)\n \n else:\n assignNames = set(resonance.assignNames)\n \n assignedResidue = getResonanceResidue(resonance)\n \n if assignNames and (assignedResidue is not residue):\n resonance.setAssignNames(assignNames)\n \n if residue:\n atomSets = []\n isotopeCode = resonance.isotopeCode\n if ('HA' in assignNames) and (residue.ccpCode == 'Gly'):\n assignNames.add('HA2')\n assignNames.add('HA3')\n \n for atom in residue.atoms:\n element = atom.chemAtom.elementSymbol\n \n if isotopeCode[-len(element):] != element:\n continue\n \n atomSet = atom.atomSet\n if atomSet:\n if atomSet.name in assignNames:\n if atomSet not in atomSets:\n atomSets.append(atomSet)\n \n if resonanceSet:\n resonanceSet.delete()\n \n if atomSets:\n # might not always find atom sets\n # e.g. if changing residue types\n assignAtomsToRes(atomSets,resonance,None)\n else:\n if resonanceSet:\n resonanceSet.delete()\n #updateResonanceAnnotation(resonance)\n\n if not resonance.resonanceGroup:\n nmrProject = resonance.nmrProject\n spinSystem = None\n molResidue = residue.molResidue\n ccpCode = molResidue.ccpCode\n molType = molResidue.molType\n spinSystems = nmrProject.findAllResonanceGroups(ccpCode=ccpCode,\n molType=molType)\n \n for extantSpinSystem in spinSystems:\n if extantSpinSystem.residue is residue:\n spinSystem = extantSpinSystem\n break\n \n if not spinSystem:\n spinSystem = nmrProject.newResonanceGroup()\n assignSpinSystemResidue(spinSystem,residue)\n \n if resonance not in spinSystem.resonances:\n spinSystem.addResonance(resonance)\n updateResonanceAnnotation(resonance)\n \n else:\n updateResonanceAnnotation(resonance)","def test_ipam_rirs_read(self):\n pass","def _readloop(self):\r\n\r\n while self._ll_alive:\r\n with self._rx_lock:\r\n data = self._Random(1)\r\n if len(data) != 0: # check for timeout\r\n self._uart_rx_queue.put(data)","def test_perceive_residues_natoms_t4(self, strict_chirality):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/T4-protein.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def next():\n iraw = 0\n run = 0\n seqno = 0\n with db_connection() as conn:\n with conn.cursor() as curs:\n try:\n curs.execute(\"\"\"SELECT rawdata.id,rawdata.run,rawdata.seqno,\n slices.block1,slices.block2,\n jobs.cluster,jobs.process\n FROM rawdata\n LEFT JOIN bindings\n ON bindings.iraw = rawdata.id\n INNER JOIN slices\n ON slices.iraw = rawdata.id\n LEFT JOIN jobs\n ON slices.ijob = jobs.id\n AND jobs.exitcode = 0\n WHERE bindings.id IS NULL\n ORDER BY rawdata.id,slices.block1\n LIMIT 2000;\n \"\"\")\n slices_missing = 1\n for row in curs.fetchall():\n i = int(row[0])\n if i != iraw:\n if slices_missing == 0:\n break\n else:\n run = int(row[1])\n seqno = int(row[2])\n slices_missing = 0\n slices = []\n iraw = i\n block1 = int(row[3])\n block2 = int(row[4])\n if row[5] is not None and row[6] is not None:\n cluster = int(row[5])\n process = int(row[6])\n slices.append((block1,block2,cluster,process))\n else:\n print(\"slices missing on\", row[5], row[6])\n slices_missing += 1\n if slices_missing:\n return 0\n else:\n curs.execute(\"SELECT TIMEZONE('GMT', NOW());\")\n now = curs.fetchone()[0]\n curs.execute(\"\"\"INSERT INTO bindings\n (iraw,starttime)\n VALUES (%s,%s)\n RETURNING id;\n \"\"\", (iraw, now))\n row = curs.fetchone()\n if row:\n ibind = int(row[0])\n else:\n return 0\n except:\n iraw = 0\n if iraw == 0:\n time.sleep(random.randint(1,30))\n return -9 # collision\n\n workdir = str(iraw)\n os.mkdir(workdir)\n os.chdir(workdir)\n badslices = []\n for sl in slices:\n sdir = str(sl[0]) + \",\" + str(sl[1])\n os.mkdir(sdir)\n tarfile = \"job_{0}_{1}.tar.gz\".format(sl[2], sl[3])\n tarpath = input_area + \"/\" + tarfile\n try:\n subprocess.check_output([\"gfal-copy\", src_url + tarpath,\n \"file://\" + os.getcwd() + \"/\" + tarfile])\n except:\n sys.stderr.write(\"Error -999 on rawdata id {0}\".format(iraw) +\n \" - job output \" + tarfile + \" is missing!\\n\")\n sys.stderr.flush()\n badslices.append(sdir)\n continue\n try:\n subprocess.check_output([\"tar\", \"zxf\", tarfile, \"-C\", sdir])\n except:\n sys.stderr.write(\"Error -999 on rawdata id {0}\".format(iraw) +\n \" - job output \" + tarfile + \" is not readable!\\n\")\n sys.stderr.flush()\n badslices.append(sdir)\n finally:\n os.remove(tarfile)\n if len(badslices) > 0:\n with db_connection() as conn:\n with conn.cursor() as curs:\n curs.execute(\"SELECT TIMEZONE('GMT', NOW());\")\n now = curs.fetchone()[0]\n curs.execute(\"\"\"UPDATE bindings\n SET endtime=%s, \n exitcode=%s,\n details=%s\n WHERE id = %s;\n \"\"\", (now, -999, \":\".join(badslices), ibind))\n os.chdir(\"..\")\n shutil.rmtree(workdir)\n return 1\n\n badslices += merge_evio_skims(run, seqno, slices)\n badslices += merge_hddm_output(run, seqno, slices)\n badslices += merge_job_info(run, seqno, slices)\n badslices += merge_root_histos(run, seqno, slices)\n exitcode = -len(badslices)\n with db_connection() as comm:\n with conn.cursor() as curs:\n curs.execute(\"SELECT TIMEZONE('GMT', NOW());\")\n now = curs.fetchone()[0]\n curs.execute(\"\"\"UPDATE bindings\n SET endtime=%s,\n exitcode=%s,\n details=%s\n WHERE id = %s;\n \"\"\", (now, exitcode, \":\".join(badslices), ibind))\n os.chdir(\"..\")\n shutil.rmtree(workdir)\n return 1","def residual_processor(self):\n def get_file(field, solver):\n \"\"\"Helper method to get the file handle for a field.\n\n On first invocation, it creates the file with headers. On\n subsequent invocations it just returns the relevant file handle.\n \"\"\"\n if not field in self.res_files:\n fh = open(join(self.logs_dir, field+\".dat\"), 'w')\n fh.write(\"# Field: %s; Solver: %s\\n\"%(field, solver))\n fh.write(\"Time SubIteration InitialResidual FinalResidual NoIterations\\n\")\n self.res_files[field] = fh\n return self.res_files[field]\n # end get_file\n\n try:\n while True:\n rexp = (yield)\n solver = rexp.group(1) # e.g., PCB, GAMG, etc.\n field = rexp.group(2) # Ux, Uy, p, etc.\n\n icorr = self.subiter_map.get(field, 0) + 1\n self.subiter_map[field] = icorr\n fh = get_file(field, solver)\n fh.write(\n self.time_str + \"\\t%d\\t\"%icorr +\n \"\\t\".join([rexp.group(i) for i in range(3, 6)]) + \"\\n\")\n except GeneratorExit:\n for fh in self.res_files.values():\n if not fh.closed:\n fh.close()","def fatal_error_processor(self):\n while True:\n _ = (yield)\n self.failed = True\n self.converged = False\n self.solve_completed = False","def nextRes(self):\n\n self.current_residueFull = self.current_residue.get().split(\":\")\n if len(self.current_residueFull) < 2:\n res = int(self.current_residue.get())+1\n self.current_residue.set(res)\n self.check_residue_callback()\n else:\n print \"Please Change selection to get info...\"","def test_rescore_unmask(self):\r\n module = CapaFactory.create(xml=self.common_shuffle_xml)\r\n get_request_dict = {CapaFactory.input_key(): 'mask_0'}\r\n module.check_problem(get_request_dict)\r\n # On rescore, state/student_answers should use unmasked names\r\n with patch.object(module.runtime, 'track_function') as mock_track_function:\r\n module.rescore_problem()\r\n mock_call = mock_track_function.mock_calls[0]\r\n event_info = mock_call[1][1]\r\n self.assertEquals(mock_call[1][0], 'problem_rescore')\r\n self.assertEquals(event_info['state']['student_answers'][CapaFactory.answer_key()], 'choice_2')\r\n self.assertIsNotNone(event_info['permutation'][CapaFactory.answer_key()])","def iter_non_standard_residues(self):\n fpred = lambda f: f.is_standard_residue()\n return itertools.ifilterfalse(fpred, self.iter_fragments())","def getResAromaticVectors(residues):\n for res in residues.keys():\n rtype = res.split(\":\")[1][0:3] # A:GLY48 => GLY\n try:\n if rtype == \"PHE\" or rtype == \"TYR\":\n if len(residues[res]) == 6:\n pass\n else:\n if DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n elif rtype == \"TRP\":\n if len(residues[res]) >= 9:\n residues[res] = purgeTrp(residues[res])\n else:\n if DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n elif rtype == \"HIS\":\n if len(residues[res]) >= 5:\n residues[res] = purgeHis(residues[res])\n else:\n if DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n elif rtype == \"ARG\":\n residues[res] = purgeArg(residues[res])\n if not residues[res] and DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n elif rtype == \"DA\" or rtype == \"A\":\n if len(residues[res]) >= 10:\n residues[res] = purgeAdenine(residues[res])\n else:\n if DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n elif rtype == \"DC\" or rtype == \"C\":\n if len(residues[res]) >= 6:\n residues[res] = purgeAdenine(residues[res])\n else:\n if DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n elif rtype == \"DG\" or rtype == \"G\":\n if len(residues[res]) >= 10:\n residues[res] = purgeAdenine(residues[res])\n else:\n if DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n if residues[res]:\n residues[res] = atomsToVec(residues[res])\n else:\n del residues[res]\n except:\n if DEBUG: print \"Fatal error in processing residue [ %s ]\"% res\n del residues[res]\n return residues","def test_find_surface_residues():\n atom_dict_0 = find_surface_residues(protein, max_dist=0, scaling=1)\n atom_dict_1 = find_surface_residues(protein, max_dist=2, scaling=1)\n atom_dict_2 = find_surface_residues(protein, max_dist=3, scaling=1)\n atom_dict_3 = find_surface_residues(protein, max_dist=None, scaling=1)\n atom_dict_4 = find_surface_residues(protein, max_dist=None, scaling=2)\n\n assert atom_dict_0.size == 0\n assert len(atom_dict_1) > len(atom_dict_0), ('Increasing max_dist should '\n 'result in more/equal number '\n 'of atoms found')\n\n assert len(atom_dict_2) >= len(atom_dict_1), ('Increasing max_dist should '\n 'result in more/equal number '\n 'of atoms found')\n assert_array_equal(np.intersect1d(atom_dict_1['id'], atom_dict_2['id']), atom_dict_1['id'])\n\n if oddt.toolkit.backend == 'ob':\n ref_len_1 = 762\n ref_len_2 = 968\n ref_len_3 = 654\n ref_len_4 = 379\n elif oddt.toolkit.backend == 'rdk' and oddt.toolkits.rdk.__version__ >= '2019.09':\n ref_len_1 = 762\n ref_len_2 = 968\n ref_len_3 = 664\n ref_len_4 = 393\n else:\n ref_len_1 = 759\n ref_len_2 = 966\n ref_len_3 = 735\n ref_len_4 = 489\n\n assert len(atom_dict_1) == ref_len_1\n assert len(atom_dict_2) == ref_len_2\n assert len(atom_dict_3) == ref_len_3\n assert len(atom_dict_4) == ref_len_4\n\n # Adding hydrogen atoms should have no effect on the result\n protein.addh()\n atom_dict_addh = find_surface_residues(protein, max_dist=2, scaling=1)\n assert_array_equal(atom_dict_addh['id'], atom_dict_1['id'])\n\n with pytest.raises(TypeError):\n find_surface_residues(molecule=1)\n with pytest.raises(ValueError):\n find_surface_residues(molecule=protein, max_dist='a')\n with pytest.raises(ValueError):\n find_surface_residues(molecule=protein, max_dist=[1, 1, 1])","def is_standard_residue(self):\n return True","def is_standard_residue(self):\n return True","def test_is_in_ring(self):\n molecule = Molecule.from_smiles(\"c1ccccc1\")\n\n for atom in molecule.atoms:\n if atom.atomic_number == 6:\n assert atom.is_in_ring()\n\n for bond in molecule.bonds:\n if 1 in (bond.atom1.atomic_number, bond.atom2.atomic_number):\n continue\n assert bond.is_in_ring()","def simulate_read(self):\n\n fastafile = ps.FastaFile(self.genome_fa)\n # left split read\n\n insert = int(np.random.normal(self.insert_size, (self.insert_size / 12), 1))\n start = int(np.random.randint(self.chr_pos_start, (self.chr_pos_end + 1)))\n left_end = start + self.read_length\n total_end = start + int(np.round(insert))\n right_start = total_end - self.read_length\n if total_end > self.chr_pos_end:\n # split read scenario or insert spanning split read scenario\n if left_end > self.chr_pos_end:\n # left read spanning split read scenario\n # left_read\n left_dntps = self.chr_pos_end - start\n right_dntps = self.read_length - left_dntps\n\n # the error could be here\n left_split_read = fastafile.fetch(self.chr, start, self.chr_pos_end)\n right_split_read = fastafile.fetch(self.chr, self.chr_pos_start, (self.chr_pos_start + right_dntps))\n left_read = left_split_read + right_split_read\n\n # right_read\n right_start = self.chr_pos_start + int(round(self.insert_size - left_dntps - self.read_length))\n right_read = fastafile.fetch(self.chr, right_start, (right_start + self.read_length))\n\n # assertion to check the error here\n\n common_id = \"%s|%s|%s:%s-%s:%s|%s:%s|1|%s\" % (\n self.read_number,\n self.chr,\n start,\n self.chr_pos_end,\n self.chr_pos_start,\n (self.chr_pos_start + right_dntps),\n right_start,\n (right_start + self.read_length),\n self.circle_id,\n )\n\n else:\n if right_start > self.chr_pos_end:\n # insert spanning split read scenario\n left_read = fastafile.fetch(self.chr, start, (start + self.read_length))\n right_start = self.chr_pos_start + (right_start - self.chr_pos_end)\n right_read = fastafile.fetch(self.chr, right_start, (right_start + self.read_length))\n common_id = \"%s|%s|%s:%s|%s:%s|3|%s\" % (\n self.read_number,\n self.chr,\n start,\n (start + self.read_length),\n right_start,\n (right_start + self.read_length),\n self.circle_id,\n )\n else:\n # right split read scenario\n assert right_start <= self.chr_pos_end\n assert (right_start + self.read_length) > self.chr_pos_end\n left_read = fastafile.fetch(self.chr, start, (start + self.read_length))\n\n # compute right dntps\n left_dntps = self.chr_pos_end - right_start\n right_dntps = self.read_length - left_dntps\n left_split_read = fastafile.fetch(self.chr, right_start, self.chr_pos_end)\n right_split_read = fastafile.fetch(self.chr, self.chr_pos_start, (self.chr_pos_start + right_dntps))\n right_read = left_split_read + right_split_read\n common_id = \"%s|%s|%s:%s|%s:%s-%s:%s|2|%s\" % (\n self.read_number,\n self.chr,\n start,\n (start + self.read_length),\n right_start,\n self.chr_pos_end,\n self.chr_pos_start,\n (self.chr_pos_start, right_dntps),\n self.circle_id,\n )\n\n else:\n # non split read scenario\n left_read = fastafile.fetch(self.chr, start, (start + self.read_length))\n # correct right read start\n right_read = fastafile.fetch(self.chr, right_start, (right_start + self.read_length))\n common_id = \"%s|%s|%s:%s|%s:%s|0|%s\" % (\n self.read_number,\n self.chr,\n start,\n (start + self.read_length),\n right_start,\n (right_start + self.read_length),\n self.circle_id,\n )\n\n return (right_read, left_read, common_id)","def test_function_fuel_sum(data, mode_constrained, space_heating_enduses):\n fuel_in = 0\n fuel_in_solid_fuel = 0\n fuel_in_gas = 0\n fuel_in_elec = 0\n fuel_in_oil = 0\n fuel_in_heat = 0\n fuel_in_hydrogen = 0\n fuel_in_biomass = 0\n\n fuel_heating_all_fueltypes = 0\n fuel_heating_gas = 0\n tot_heating = 0\n #mode_constrained = True #SCRAP\n\n for region in data['rs_fuel_disagg']:\n for enduse in data['rs_fuel_disagg'][region]:\n fuel_in += np.sum(data['rs_fuel_disagg'][region][enduse])\n fuel_in_heat += np.sum(data['rs_fuel_disagg'][region][enduse][data['lookups']['fueltypes']['heat']])\n\n if mode_constrained == False and enduse in space_heating_enduses: #Exclude inputs for heating\n tot_heating += np.sum(data['rs_fuel_disagg'][region][enduse])\n #pass\n else:\n fuel_in_elec += np.sum(data['rs_fuel_disagg'][region][enduse][data['lookups']['fueltypes']['electricity']])\n fuel_in_gas += np.sum(data['rs_fuel_disagg'][region][enduse][data['lookups']['fueltypes']['gas']])\n fuel_in_hydrogen += np.sum(data['rs_fuel_disagg'][region][enduse][data['lookups']['fueltypes']['hydrogen']])\n fuel_in_oil += np.sum(data['rs_fuel_disagg'][region][enduse][data['lookups']['fueltypes']['oil']])\n fuel_in_solid_fuel += np.sum(data['rs_fuel_disagg'][region][enduse][data['lookups']['fueltypes']['solid_fuel']])\n fuel_in_biomass += np.sum(data['rs_fuel_disagg'][region][enduse][data['lookups']['fueltypes']['biomass']])\n \n for region in data['ss_fuel_disagg']:\n for enduse in data['ss_fuel_disagg'][region]:\n for sector in data['ss_fuel_disagg'][region][enduse]:\n fuel_in += np.sum(data['ss_fuel_disagg'][region][enduse][sector])\n fuel_in_heat += np.sum(data['ss_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['heat']])\n\n if mode_constrained == False and enduse in space_heating_enduses:\n tot_heating += np.sum(data['ss_fuel_disagg'][region][enduse][sector])\n else:\n fuel_in_elec += np.sum(data['ss_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['electricity']])\n fuel_in_gas += np.sum(data['ss_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['gas']])\n fuel_in_hydrogen += np.sum(data['ss_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['hydrogen']])\n fuel_in_oil += np.sum(data['ss_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['oil']])\n fuel_in_solid_fuel += np.sum(data['ss_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['solid_fuel']])\n fuel_in_biomass += np.sum(data['ss_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['biomass']])\n \n for region in data['is_fuel_disagg']:\n for enduse in data['is_fuel_disagg'][region]:\n for sector in data['is_fuel_disagg'][region][enduse]:\n fuel_in += np.sum(data['is_fuel_disagg'][region][enduse][sector])\n fuel_in_heat += np.sum(data['is_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['heat']])\n\n if mode_constrained == False and enduse in space_heating_enduses:\n tot_heating += np.sum(data['is_fuel_disagg'][region][enduse][sector])\n else:\n fuel_in_elec += np.sum(data['is_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['electricity']])\n fuel_in_gas += np.sum(data['is_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['gas']])\n fuel_in_hydrogen += np.sum(data['is_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['hydrogen']])\n fuel_in_oil += np.sum(data['is_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['oil']])\n fuel_in_solid_fuel += np.sum(data['is_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['solid_fuel']])\n fuel_in_biomass += np.sum(data['is_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['biomass']])\n \n return fuel_in, fuel_in_biomass, fuel_in_elec, fuel_in_gas, fuel_in_heat, fuel_in_hydrogen, fuel_in_solid_fuel, fuel_in_oil, tot_heating","def test_reset(self):\n ran = []\n def foo():\n ran.append(None)\n\n c = task.Clock()\n lc = TestableLoopingCall(c, foo)\n lc.start(2, now=False)\n c.advance(1)\n lc.reset()\n c.advance(1)\n self.assertEqual(ran, [])\n c.advance(1)\n self.assertEqual(ran, [None])","def test_exception_list_empty(self):\n complex_id_list = range(1,4) #1~3\n dataloader = lambda d: d\n calc_func = lambda d1,d2: d1 + d2\n \n _, actual = complex_pairwise_calc(complex_id_list, dataloader, calc_func, symmetry=False)\n expected = []\n\n self.assertEqual(actual, expected)","def test_residues(parse_mmtf):\n parse_mmtf.assertEqual(len(parse_mmtf.mmcif_res), len(parse_mmtf.mmtf_res))\n for i, e in enumerate(parse_mmtf.mmcif_res):\n mmcif_r = parse_mmtf.mmcif_res[i]\n mmtf_r = parse_mmtf.mmtf_res[i]\n parse_mmtf.assertEqual(mmtf_r.level, mmcif_r.level)\n parse_mmtf.assertEqual(mmtf_r.disordered, mmcif_r.disordered)\n parse_mmtf.assertEqual(mmtf_r.resname, mmcif_r.resname)\n parse_mmtf.assertEqual(mmtf_r.segid, mmcif_r.segid)\n parse_mmtf.mmcif_atoms = [x for x in mmcif_r.get_atom()]\n parse_mmtf.mmtf_atoms = [x for x in mmtf_r.get_atom()]\n test_atoms(parse_mmtf=parse_mmtf)","def test_run_loop_exc(self):\n with self.assertRaises(ExecutionException):\n pyint = Interpreter(limit=1)\n pyint.run(code=BF_CODE_LOOP_TWICE)","def test_fleur_relax_continue_converged(self, run_with_cache, mock_code_factory):\n assert False","def isResidueAssigned(residue):\n\n for atom in residue.atoms:\n if atom.atomSet:\n if atom.atomSet.resonanceSets:\n return True\n \n return False","def test_stop_resume(self):\n self.create_sample_data_set_dir(\"node59p1_step1.dat\", TELEM_DIR, \"node59p1.dat\",\n copy_metadata=False)\n driver_config = self._driver_config()['startup_config']\n sio_mule_config = driver_config['harvester'][DataSourceKey.PHSEN_ABCDEF_SIO_MULE]\n fullfile = os.path.join(sio_mule_config['directory'], sio_mule_config['pattern'])\n mod_time = os.path.getmtime(fullfile)\n\n # Create and store the new driver state\n self.memento = {DataSourceKey.PHSEN_ABCDEF_SIO_MULE: {\n \"node59p1.dat\": {\n DriverStateKey.FILE_SIZE: 911,\n DriverStateKey.FILE_CHECKSUM: '8b7cf73895eded0198b3f3621f962abc',\n DriverStateKey.FILE_MOD_DATE: mod_time,\n DriverStateKey.PARSER_STATE: {\n StateKey.IN_PROCESS_DATA: [],\n StateKey.UNPROCESSED_DATA:[[0, 172]],\n StateKey.FILE_SIZE: 911\n }\n }\n }}\n\n self.driver = self._get_driver_object(memento=self.memento)\n\n # create some data to parse\n self.clear_async_data()\n self.create_sample_data_set_dir(\"node59p1_step2.dat\", TELEM_DIR, \"node59p1.dat\",\n copy_metadata=False)\n\n self.driver.start_sampling()\n\n # verify data is produced\n self.assert_data(PhsenParserDataParticle, 'test_data_2.txt.result.yml',\n count=2, timeout=10)","def run(self):\n while True:\n if self.job_q.empty():\n self.message_q.put(False)\n return\n try:\n smolecule = self.job_q.get()\n self.data_pointer[smolecule].get_adp(self.Temp)\n except IndexError:\n self.message_q.put((smolecule, None))\n try:\n self.message_q.put((smolecule, [j.adp['cart_int'] for j in self.data_pointer[smolecule].atoms]))\n except KeyError:\n # =======================================================\n # self.message_q.put((molecule,[0 for i in self.data_pointer[molecule].atoms]))\n #=======================================================\n pass","def test_ipam_rirs_partial_update(self):\n pass","def test_resids(self):\n cr = CaseReader(self.filename)\n last_case = cr.get_case(-1)\n self.assertIsNone(last_case.resids,\n \"Case erroneously contains resids.\")","def testrescorr():\n tau = np.zeros((2,50))\n tau[0,25] = 2\n tau[1,23] = 3\n tau2 = spec_utils.res_corr(tau, 2, 8)\n #Check flux conserved\n assert np.abs(np.sum(tau2[0,:])/ np.sum(tau[0,:]) -1) < 1e-6\n assert np.abs(np.sum(tau2[1,:])/ np.sum(tau[1,:]) -1) < 1e-6\n #Check expanded by expected amount\n for i in (0,1):\n assert np.size(np.where(tau2[i,:]> 0)) == 15","def waitOverlappedDone(self, count, timeout):\n startTime = time.time()\n while True: #wait until measuring flag goes to 0\n try:\n measured = self.handle.ask(\":DATA:POIN?;\")\n measured = measured.strip() #remove CR \n measured = int(measured) #convert to number\n if measured == count: #final number of samples achieved\n break;\n except Exception:\n print('Dvm34411.waitOverlappedDone() polling failed !')\n raise\n \n if time.time() - startTime > timeout:\n print('Dvm34411.waitOverlappedDone() timeout !')\n return False\n \n samples = [] \n for i in range(0, count):\n try:\n reading = self.handle.ask('R? 1;') #definite-Length block format\n except Exception: \n print('Dvm34411.Reading results failed !')\n raise;\n #DLB: '#' followed by number od decimal digits to follow\n #the decimal number is length of data in bytes\n if reading[0] != '#':\n print('Dvm34411.DLB format error - # expected !')\n return False\n digits = int(reading[1])\n reading = reading[2 + digits:]\n samples.append(reading.strip())\n \n return samples","def test_08(self, test):\r\n globalConfig.test = test\r\n\r\n forbiddenRoutes = []\r\n outputList = getOutputList()\r\n inputList = getInputList()\r\n if len(inputList) == 0 or len(outputList) == 0:\r\n return test.UNCLEAR(\"Not tested. No resources found.\")\r\n\r\n for outputInstance in outputList:\r\n sourceID = outputInstance.getSourceID()\r\n for inputInstance in inputList:\r\n inputParent = inputInstance.getParent()\r\n if inputParent['type'] == \"source\" and sourceID == inputParent['id']:\r\n route = {\r\n \"input\": inputInstance,\r\n \"output\": outputInstance\r\n }\r\n forbiddenRoutes.append(route)\r\n\r\n for route in forbiddenRoutes:\r\n outputCaps = route['output'].getCaps()\r\n msg = (\"It is possible to create a loop using re-entrant matrices \"\r\n \"between Input {} and Output {}\".format(route['input'].id, route['output'].id))\r\n try:\r\n routableInputs = outputCaps['routable_inputs']\r\n except KeyError:\r\n return test.FAIL(\"Could not find 'routable_inputs' in /caps \"\r\n \"for Output {}\".format(route['output'].id))\r\n if routableInputs is None or route['input'].id in routableInputs:\r\n return test.FAIL(msg)\r\n return test.PASS()","def test_get_counturingErr(self):\n for app_num, servo_type in app_nr.items():\n try:\n par = self.get_parameter(servo_type, app_num, COUNTURING_ERR_IDX, COUNTURING_ERR_SUB)\n param_obj = self.__dict__[servo_type]._get_counturingErr()\n acs_par, completion = param_obj.get_sync()\n if(completion.code):\n print \"\\nError code found in counturingErr...\"\n continue\n self.data_match(acs_par, par)\n except NackEx:\n continue","def test_apply_ridit(self):\n x, x_rand, s = self.create_testdata()\n task = mmRDTR()\n s = task.check_sparse(s)\n\n for data in [x, x_rand, s]:\n #get ecdf for data\n Fn=task.make_ECDF(data)\n out=task.apply_ridit( data, Fn )\n # check same dimension\n self.assertEqual(np.all(data.shape==out.shape),True)\n # check mean almost equal to 0\n for i in range(data.shape[1]):\n self.assertEqual(round(out[:,i].mean(),8),0)\n # check if works with newdata\n newdata=data[:2]\n out=task.apply_ridit( newdata, Fn )\n # check same dimension\n self.assertEqual(np.all(newdata.shape==out.shape),True)","def test_check_for_max_rmsd():\n phil_groups = ncs_group_master_phil.fetch(\n iotbx.phil.parse(phil_str)).extract()\n pdb_inp = iotbx.pdb.input(source_info=None, lines=test_pdb_str_2)\n ncs_obj_phil = ncs.input(\n hierarchy=pdb_inp.construct_hierarchy(),\n ncs_phil_groups=phil_groups.ncs_group)\n nrgl = ncs_obj_phil.get_ncs_restraints_group_list()\n pdb_inp = iotbx.pdb.input(lines=test_pdb_str_2,source_info=None)\n ph = pdb_inp.construct_hierarchy()\n # passing test\n assert nrgl.check_for_max_rmsd(ph.atoms().extract_xyz() ,chain_max_rmsd=1)\n # make sure test fails when it suppose to\n nrgl[0].copies[1].t = matrix.col([100, -89.7668, 5.8996])\n assert not nrgl.check_for_max_rmsd(ph.atoms().extract_xyz(),chain_max_rmsd=1)","def test_pure_prisoners_dilemma(_):\n game = gamegen.sym_2p2s_game(2, 0, 3, 1) # prisoners dilemma\n eqm = [0, 2]\n\n assert (\n regret.pure_strategy_regret(game, eqm) == 0\n ), \"Known equilibrium was not zero regret\"","def check_termination(self) :\n\t\trc_all = self.rc1[-1]+self.rc2[-1]\n\t\tif rc_all == 0 and self.ssep[-1] < self.tol \\\n\t\t\t and self.ssed[-1] < self.tol : \n\t\t\tself.converged = True\n\t\t\tself.continueLoop = False \n\t\n\t\tif self.loopiter >= self.maxiter : \n\t\t\tself.maxiter_exceeded = True\n\t\t\tself.converged = False\n\t\t\tself.continueLoop = False\n\t\n\t# Check any obvious SSE inconsistencies\n\t\tif self.ssep[-1] > self.sseMax or self.ssed[-1] > self.sseMax : \n\t\t\tself.continueLoop = False","def test_perceive_residues_natoms_mainchain_alanine(self, strict_chirality):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/MainChain_ALA.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def test_read_fail1(self):\n mod_fn = os.path.join(tests.TEST_DATA_PATH, 'segmentations', 'test_bad_data1.mod')\n with self.assertRaises(ValueError):\n modreader.get_data(mod_fn) # missing 'IMOD' start"],"string":"[\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def test_residue_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for residue in mol_res_spin.residue_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_molecule_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the molecules.\\n i = 0\\n for molecule in mol_res_spin.molecule_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_residue_loop(self):\\n\\n # Loop over the residues.\\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\\n # Test the selection.\\n self.assertEqual(res.num, 2)\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)\",\n \"def test_molecule_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for molecule in mol_res_spin.molecule_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_molecule_loop_no_selection(self):\\n\\n # Molecule data.\\n name = ['Ap4Aase', 'RNA']\\n\\n # Loop over the molecules.\\n i = 0\\n for mol in mol_res_spin.molecule_loop():\\n # Test the molecule names.\\n self.assertEqual(mol.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)\",\n \"def test_spin_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for spin in mol_res_spin.spin_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_molecule_loop(self):\\n\\n # Loop over the molecules.\\n for mol in mol_res_spin.molecule_loop('#RNA'):\\n # Test the molecule name.\\n self.assertEqual(mol.name, 'RNA')\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_return_residue_pipe_fail(self):\\n\\n # Try to get a residue from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')\",\n \"def test_spin_loop_no_selection(self):\\n\\n # Spin data.\\n select = [0, 1, 0, 0, 1, 1, 0, 1]\\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 8)\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_return_residue(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_residue(':1')\\n res2 = mol_res_spin.return_residue(selection=':2')\\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1.num, 1)\\n self.assertEqual(res1.name, None)\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2.num, 2)\\n self.assertEqual(res2.name, 'Glu')\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4.num, 4)\\n self.assertEqual(res4.name, 'Pro')\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5.num, -5)\\n self.assertEqual(res5.name, None)\\n self.assertEqual(res5.spin[1].name, 'N5')\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_spin_loop(self):\\n\\n # Spin data.\\n select = [1, 0]\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, 'N5')\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 2)\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_return_single_residue_info(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_single_residue_info('1')\\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\\n res5 = mol_res_spin.return_single_residue_info('-5')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1, (1, None))\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2, (2, 'Glu'))\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4, (4, 'Pro'))\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5, (-5, None))\",\n \"def test_spin_loop_multiatom(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_return_single_residue_info_fail(self):\\n\\n # Ask for a few residues.\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')\",\n \"def test_empty_with_filter(multi_mol_system_irregular):\\n sequence = \\\"not empty\\\"\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\", sequence, molecule_selector=lambda mol: False\\n )\\n with pytest.raises(ValueError):\\n processor.run_system(multi_mol_system_irregular)\",\n \"def test_run_molecule_not_selected(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\", sequence, molecule_selector=lambda mol: False\\n )\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert vermouth.utils.are_all_equal(found)\\n assert found[0] is None\",\n \"def test_spin_loop_wildcard(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N*'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_wrong_length(multi_mol_system_irregular, sequence):\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n with pytest.raises(ValueError):\\n processor.run_system(multi_mol_system_irregular)\",\n \"def test_empty_system_empty_sequence():\\n system = vermouth.system.System()\\n sequence = \\\"\\\"\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n try:\\n processor.run_system(system)\\n except ValueError:\\n pytest.fail(\\\"Should not have raised a ValueError.\\\")\",\n \"def test_RUMI():\\r\\n\\r\\n start = 11051\\r\\n end = 11902\\r\\n read_poems(start, end)\",\n \"def check_residue_callback(self):\\n\\n if not self.check_for_residue_existance():\\n return\\n\\n self.listbox_current_designs.delete(0, END)\\n self.current_residueFull = self.current_residue.get().split(\\\":\\\")\\n\\n if len(self.current_residueFull) > 1:\\n self.listbox_restypes.delete(9)\\n self.listbox_restypes.insert(9, \\\"Conserved\\\")\\n else:\\n res = self.current_residueFull[0] +\\\":\\\"+self.current_chain.get()\\n #print res\\n if not self.pose.total_residue():\\n return\\n\\n resType = self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get()))\\n try:\\n resName = self.pose.residue(resType).name()\\n except PyRosettaException:\\n print \\\"Residue does not exist in PDB...\\\"\\n return\\n\\n\\n self.current_residue_name_full.set(resName)\\n three_letter_name = resName.split(\\\"_\\\")[0]; #Fix for Rosetta designated chain endings, His_d\\n self.current_residue_name.set(resName)\\n\\n #Fix for not having data for certain residue types:\\n try:\\n self.design_accessible_sa.set(self.residue_definitions.resinfo[three_letter_name][0])\\n self.design_relative_mutability.set(self.residue_definitions.resinfo[three_letter_name][1])\\n self.design_surface_probability.set(self.residue_definitions.resinfo[three_letter_name][2])\\n except KeyError:\\n print \\\"No Data for restype\\\"\\n self.design_accessible_sa.set(\\\"\\\")\\n self.design_relative_mutability.set(\\\"\\\")\\n self.design_surface_probability.set(\\\"\\\")\\n\\n con = \\\"Conserved:\\\" +three_letter_name\\n self.listbox_restypes.delete(9)\\n self.listbox_restypes.insert(9, con)\\n if self.DesignDic.has_key(res):\\n for residues in self.DesignDic[res]:\\n self.listbox_current_designs.insert(END, residues)\",\n \"def test_return_molecule_pipe_fail(self):\\n\\n # Try to get a molecule from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')\",\n \"def test_empty_system_error():\\n system = vermouth.system.System()\\n sequence = \\\"not empty\\\"\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n with pytest.raises(ValueError):\\n processor.run_system(system)\",\n \"def test_multi_molecules_cycle_one(self, multi_mol_system_irregular):\\n sequence = \\\"A\\\"\\n expected = [sequence] * (15 * 3)\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_irregular)\\n found = self.sequence_from_system(multi_mol_system_irregular, \\\"test\\\")\\n assert found == expected\",\n \"def test_single_molecules_cycle_one(self, single_mol_system):\\n sequence = \\\"A\\\"\\n expected = [sequence] * (5 * 3)\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def test_return_spin_pipe_fail(self):\\n\\n # Try to get a spin from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')\",\n \"def check_residue(self, chain_id, resid, resname):\\n if resname in PTM_lookup.keys():\\n return\\n else:\\n try:\\n ref_resname = PTM_reverse_lookup[resname]\\n except KeyError:\\n # print \\\"skipping unrecognized residue\\\", resname\\n return\\n ptm_dict = PTM_lookup[ref_resname][resname]\\n return (chain_id, resid, ref_resname, ptm_dict[\\\"goto_atom\\\"], ptm_dict[\\\"name\\\"])\",\n \"def test_count_spins_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Test for the error.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.count_spins)\",\n \"def test_run_loop_success(self):\\n found = False\\n pyint = Interpreter(limit=15)\\n try:\\n pyint.run(code=BF_CODE_LOOP_TWICE)\\n except SystemExit: \\n found = True\\n self.assertFalse(found)\",\n \"def test_run_molecule(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def test_count_no_spins(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Test the number of spins counted.\\n self.assertEqual(mol_res_spin.count_spins(), 0)\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def test_multi_molecules_cycle(self, multi_mol_system_regular, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n expected = expected * 3\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_regular)\\n found = self.sequence_from_system(multi_mol_system_regular, \\\"test\\\")\\n assert found == expected\",\n \"def test_perceive_residues_natoms_mainchain_arginine(self, strict_chirality):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/MainChain_ARG.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def check_for_residue_existance(self):\\n if not self.pose.total_residue():\\n print \\\"No pose Loaded.\\\"\\n return False\\n\\n if not self.current_chain.get() or not self.current_residue.get():\\n print \\\"Chain or residue not set\\\"\\n return False\\n\\n current_region = self.current_residue.get().split(\\\":\\\")\\n if len(current_region)>1:\\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\\n\\n\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\\n print \\\"Region not found in pose\\\"\\n return False\\n else:\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\\n\\n print \\\"Residue not found in pose\\\"\\n return False\\n\\n #If everythig is good then:\\n return True\",\n \"def residual(pars, data= None):\\n\\n\\t\\t\\tresid = np.array([])\\n\\n\\n\\t\\t\\t# make residual per data set\\n\\n\\t\\t\\tfor N in range(n_annulus):\\n\\n\\t\\t\\t\\tmdl_ev = 0\\n\\t\\t\\t\\tr_space_k = rings_pos[N+1] - rings_pos[N] \\n\\t\\t\\t\\tmask = np.where( (r_n >= rings_pos[N] ) & (r_n < rings_pos[N+1]) )\\n\\t\\t\\t\\tx,y = XY_mesh[0][mask], XY_mesh[1][mask] \\n\\t\\t\\t\\tXY = (x,y)\\n\\n\\n\\n\\n\\t\\t\\t\\tfor kk in range(2):\\n\\t\\t\\t\\t\\tVxy,Vsys = vmodel_dataset(pars, N+kk, XY, r_0 = rings_pos[N], r_space = r_space_k )\\n\\n\\t\\t\\t\\t\\tmdl_ev = mdl_ev + Vxy[kk]\\n\\n\\n\\t\\t\\t\\t\\tif N == 0 and kk == 0:\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tmask1 = np.where( (r_n < rings_pos[0] ) )\\n\\t\\t\\t\\t\\t\\tx1,y1 = XY_mesh[0][mask1], XY_mesh[1][mask1] \\n\\t\\t\\t\\t\\t\\tXY1 = (x1,y1)\\n\\n\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t# inner interpolation\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t#(a) velocity rise linearly from zero\\n\\n\\t\\t\\t\\t\\t\\tr_space_0 = rings_pos[0]\\n\\t\\t\\t\\t\\t\\tVxy,Vsys = vmodel_dataset(pars, 0, XY1, r_0 = 0, r_space = r_space_0)\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tinterp_model[mask1] = Vxy[1] + Vsys\\n\\n\\t\\t\\t\\tinterp_model[mask] = mdl_ev + Vsys\\n\\n\\n\\n\\n\\t\\t\\t\\n\\t\\t\\tsigma = np.sqrt(e_vel_map**2 + e_ISM**2)\\n\\t\\t\\t#interp_model[interp_model == 0] = np.nan\\n\\n\\n\\t\\t\\tconvolved = 0\\n\\n\\t\\t\\tif convolved == True:\\n\\n\\t\\t\\t\\tmy_beam = Beam(2.5*u.arcsec, 2.5*u.arcsec, 0*u.deg)\\n\\t\\t\\t\\tpix_scale = pixel_scale * u.arcsec\\n\\t\\t\\t\\tgauss_kern = my_beam.as_kernel(pix_scale, x_size = nx, y_size = ny)\\n\\n\\n\\t\\t\\t\\textend = np.zeros((3*ny,3*nx))\\n\\t\\t\\t\\textend[ny:2*ny,nx:2*nx] = interp_model\\n\\t\\t\\t\\tconvolve_extend = convolve_fft(extend, gauss_kern, mask = extend == 0 )\\n\\t\\t\\t\\tinterp_model_conv = convolve_extend[ny:2*ny,nx:2*nx]\\n\\t\\t\\t\\tinterp_model_conv[interp_model == 0] = 0\\n\\n\\n\\n\\n\\t\\t\\telse:\\n\\t\\t\\t\\tinterp_model_conv = interp_model\\n\\n\\t\\t\\tinterp_model_conv[interp_model_conv == 0] = np.nan\\n\\t\\t\\tres = vel_map - interp_model_conv\\n\\t\\t\\tResid = res/sigma\\n\\n\\n\\t\\t\\treturn Resid.flatten()\",\n \"def test_78_continue(self):\\n\\t\\tinput = \\\"\\\"\\\"procedure main(); var x:integer;\\n\\t\\tbegin while(true)do begin\\n\\t\\twith x:integer; do with x:real; do begin\\n\\t\\t\\tif (x>0) then continue;\\n\\t\\t\\twith x:integer; do if (x=0) then return;\\n\\t\\tend{with} continue; end{while} continue; end\\\"\\\"\\\"\\n\\t\\texpect = \\\"Continue Not In Loop\\\"\\n\\t\\tself.assertTrue(TestChecker.test(input,expect,478))\",\n \"def test_single_molecule(self, single_mol_system, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def test_perceive_residues_natoms_mainchain_charged_glutamic_acid(\\n self, strict_chirality\\n ):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/MainChain_GLH.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def test_boolean_and_selection(self):\\n\\n # The selection loop:\\n sel = list(mol_res_spin.residue_loop(\\\"#Ap4Aase:4 & :Pro\\\"))\\n\\n # Test:\\n self.assertEqual(len(sel), 1)\\n for res in sel:\\n self.assert_(res.name == \\\"Pro\\\" and res.num == 4)\",\n \"def test_boolean_complex_selection(self):\\n\\n # The residue selection loop.\\n sel = list(mol_res_spin.residue_loop(\\\"#Ap4Aase:4 & :Pro | #RNA\\\"))\\n\\n # Residue names and numbers.\\n names = ['Pro', None, None]\\n numbers = [4, -5, -4]\\n\\n # The residues.\\n self.assertEqual(len(sel), 3)\\n for i in range(3):\\n self.assertEqual(sel[i].name, names[i])\\n self.assertEqual(sel[i].num, numbers[i])\",\n \"def residual(pars, data= None):\\n\\n\\t\\t\\tresid = np.array([])\\n\\n\\n\\t\\t\\t# make residual per data set\\n\\n\\t\\t\\tfor N in range(n_annulus):\\n\\n\\t\\t\\t\\tmdl_ev = 0\\n\\t\\t\\t\\tr_space_k = rings_pos[N+1] - rings_pos[N] \\n\\t\\t\\t\\tmask = np.where( (r_n >= rings_pos[N] ) & (r_n < rings_pos[N+1]) )\\n\\t\\t\\t\\tx,y = XY_mesh[0][mask], XY_mesh[1][mask] \\n\\t\\t\\t\\tXY = (x,y)\\n\\n\\n\\n\\n\\t\\t\\t\\tfor kk in range(2):\\n\\t\\t\\t\\t\\tVxy,Vsys = vmodel_dataset(pars, N+kk, XY, r_0 = rings_pos[N], r_space = r_space_k)\\n\\n\\t\\t\\t\\t\\tmdl_ev = mdl_ev + Vxy[kk]\\n\\n\\n\\t\\t\\t\\t\\tif N == 0 and kk == 0:\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tmask1 = np.where( (r_n < rings_pos[0] ) )\\n\\t\\t\\t\\t\\t\\tx1,y1 = XY_mesh[0][mask1], XY_mesh[1][mask1] \\n\\t\\t\\t\\t\\t\\tXY1 = (x1,y1)\\n\\n\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t# inner interpolation\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t#(a) velocity rise linearly from zero\\n\\n\\t\\t\\t\\t\\t\\tr_space_0 = rings_pos[0]\\n\\t\\t\\t\\t\\t\\tVxy,Vsys = vmodel_dataset(pars, 0, XY1, r_0 = 0, r_space = r_space_0)\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tinterp_model[mask1] = Vxy[1] + Vsys\\n\\n\\t\\t\\t\\tinterp_model[mask] = mdl_ev + Vsys\\n\\n\\n\\n\\n\\t\\t\\t\\n\\t\\t\\tsigma = np.sqrt(e_vel_map**2 + e_ISM**2)\\n\\n\\n\\n\\t\\t\\tconvolved = 0\\n\\n\\t\\t\\tif convolved == True:\\n\\n\\t\\t\\t\\tmy_beam = Beam(2.5*u.arcsec, 2.5*u.arcsec, 0*u.deg)\\n\\t\\t\\t\\tpix_scale = pixel_scale * u.arcsec\\n\\t\\t\\t\\tgauss_kern = my_beam.as_kernel(pix_scale, x_size = nx, y_size = ny)\\n\\n\\n\\t\\t\\t\\textend = np.zeros((3*ny,3*nx))\\n\\t\\t\\t\\textend[ny:2*ny,nx:2*nx] = interp_model\\n\\t\\t\\t\\tconvolve_extend = convolve_fft(extend, gauss_kern, mask = extend == 0 )\\n\\t\\t\\t\\tinterp_model_conv = convolve_extend[ny:2*ny,nx:2*nx]\\n\\t\\t\\t\\tinterp_model_conv[interp_model == 0] = 0\\n\\n\\n\\t\\t\\telse:\\n\\t\\t\\t\\tinterp_model_conv = interp_model\\n\\n\\n\\t\\t\\tinterp_model_conv[interp_model_conv == 0] = np.nan\\n\\t\\t\\tres = vel_map - interp_model_conv\\n\\t\\t\\tResid = res/sigma\\n\\n\\t\\t\\treturn Resid.flatten()\",\n \"def residual(pars, data= None):\\n\\n\\t\\t\\tresid = np.array([])\\n\\n\\n\\t\\t\\t# make residual per data set\\n\\n\\t\\t\\tfor N in range(n_annulus):\\n\\n\\t\\t\\t\\tmdl_ev = 0\\n\\t\\t\\t\\tr_space_k = rings_pos[N+1] - rings_pos[N] \\n\\t\\t\\t\\tmask = np.where( (r_n >= rings_pos[N] ) & (r_n < rings_pos[N+1]) )\\n\\t\\t\\t\\tx,y = XY_mesh[0][mask], XY_mesh[1][mask] \\n\\t\\t\\t\\tXY = (x,y)\\n\\n\\n\\n\\n\\t\\t\\t\\tfor kk in range(2):\\n\\t\\t\\t\\t\\tVxy,Vsys = vmodel_dataset(pars, N+kk, XY, r_0 = rings_pos[N], r_space = r_space_k)\\n\\n\\t\\t\\t\\t\\tmdl_ev = mdl_ev + Vxy[kk]\\n\\n\\n\\t\\t\\t\\t\\tif N == 0 and kk == 0:\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tmask1 = np.where( (r_n < rings_pos[0] ) )\\n\\t\\t\\t\\t\\t\\tx1,y1 = XY_mesh[0][mask1], XY_mesh[1][mask1] \\n\\t\\t\\t\\t\\t\\tXY1 = (x1,y1)\\n\\n\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t# inner interpolation\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t#(a) velocity rise linearly from zero\\n\\n\\t\\t\\t\\t\\t\\tr_space_0 = rings_pos[0]\\n\\t\\t\\t\\t\\t\\tVxy,Vsys = vmodel_dataset(pars, 0, XY1, r_0 = 0, r_space = r_space_0)\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tinterp_model[mask1] = Vxy[1] + Vsys\\n\\n\\t\\t\\t\\tinterp_model[mask] = mdl_ev + Vsys\\n\\n\\n\\n\\n\\t\\t\\t\\n\\t\\t\\tsigma = np.sqrt(e_vel_map**2 + e_ISM**2)\\n\\n\\n\\n\\t\\t\\tconvolved = 0\\n\\n\\t\\t\\tif convolved == True:\\n\\n\\t\\t\\t\\tmy_beam = Beam(2.5*u.arcsec, 2.5*u.arcsec, 0*u.deg)\\n\\t\\t\\t\\tpix_scale = pixel_scale * u.arcsec\\n\\t\\t\\t\\tgauss_kern = my_beam.as_kernel(pix_scale, x_size = nx, y_size = ny)\\n\\n\\n\\t\\t\\t\\textend = np.zeros((3*ny,3*nx))\\n\\t\\t\\t\\textend[ny:2*ny,nx:2*nx] = interp_model\\n\\t\\t\\t\\tconvolve_extend = convolve_fft(extend, gauss_kern, mask = extend == 0 )\\n\\t\\t\\t\\tinterp_model_conv = convolve_extend[ny:2*ny,nx:2*nx]\\n\\t\\t\\t\\tinterp_model_conv[interp_model == 0] = 0\\n\\n\\n\\t\\t\\telse:\\n\\t\\t\\t\\tinterp_model_conv = interp_model\\n\\n\\t\\t\\tinterp_model[interp_model == 0] = np.nan\\n\\t\\t\\tres = vel_map - interp_model_conv\\n\\t\\t\\tResid = res/sigma\\n\\n\\n\\n\\t\\t\\treturn Resid.flatten()\",\n \"def residual(pars, data= None):\\n\\n\\t\\t\\tresid = np.array([])\\n\\n\\n\\t\\t\\t# make residual per data set\\n\\n\\t\\t\\tfor N in range(n_annulus):\\n\\n\\t\\t\\t\\tmdl_ev = 0\\n\\t\\t\\t\\tr_space_k = rings_pos[N+1] - rings_pos[N] \\n\\t\\t\\t\\tmask = np.where( (r_n >= rings_pos[N] ) & (r_n < rings_pos[N+1]) )\\n\\t\\t\\t\\tx,y = XY_mesh[0][mask], XY_mesh[1][mask] \\n\\t\\t\\t\\tXY = (x,y)\\n\\n\\n\\n\\n\\t\\t\\t\\tfor kk in range(2):\\n\\t\\t\\t\\t\\tVxy,Vsys = vmodel_dataset(pars, N+kk, XY, r_0 = rings_pos[N], r_space = r_space_k)\\n\\n\\t\\t\\t\\t\\tmdl_ev = mdl_ev + Vxy[kk]\\n\\n\\n\\t\\t\\t\\t\\tif N == 0 and kk == 0:\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tmask1 = np.where( (r_n < rings_pos[0] ) )\\n\\t\\t\\t\\t\\t\\tx1,y1 = XY_mesh[0][mask1], XY_mesh[1][mask1] \\n\\t\\t\\t\\t\\t\\tXY1 = (x1,y1)\\n\\n\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t# inner interpolation\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t#(a) velocity rise linearly from zero\\n\\n\\t\\t\\t\\t\\t\\tr_space_0 = rings_pos[0]\\n\\t\\t\\t\\t\\t\\tVxy,Vsys = vmodel_dataset(pars, 0, XY1, r_0 = 0, r_space = r_space_0)\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tinterp_model[mask1] = Vxy[1] + Vsys\\n\\n\\t\\t\\t\\tinterp_model[mask] = mdl_ev + Vsys\\n\\n\\n\\n\\n\\t\\t\\t\\n\\t\\t\\tsigma = np.sqrt(e_vel_map**2 + e_ISM**2)\\n\\n\\n\\n\\t\\t\\tconvolved = 0\\n\\n\\t\\t\\tif convolved == True:\\n\\n\\t\\t\\t\\tmy_beam = Beam(2.5*u.arcsec, 2.5*u.arcsec, 0*u.deg)\\n\\t\\t\\t\\tpix_scale = pixel_scale * u.arcsec\\n\\t\\t\\t\\tgauss_kern = my_beam.as_kernel(pix_scale, x_size = nx, y_size = ny)\\n\\n\\n\\t\\t\\t\\textend = np.zeros((3*ny,3*nx))\\n\\t\\t\\t\\textend[ny:2*ny,nx:2*nx] = interp_model\\n\\t\\t\\t\\tconvolve_extend = convolve_fft(extend, gauss_kern, mask = extend == 0 )\\n\\t\\t\\t\\tinterp_model_conv = convolve_extend[ny:2*ny,nx:2*nx]\\n\\t\\t\\t\\tinterp_model_conv[interp_model == 0] = 0\\n\\n\\n\\t\\t\\telse:\\n\\t\\t\\t\\tinterp_model_conv = interp_model\\n\\n\\n\\t\\t\\tinterp_model_conv[interp_model_conv == 0] = np.nan\\n\\t\\t\\tres = vel_map - interp_model_conv\\n\\t\\t\\tResid = res/sigma\\n\\n\\n\\t\\t\\treturn Resid.flatten()\",\n \"def algorithm_loop(self):\",\n \"def test_return_molecule(self):\\n\\n # Ask for a few molecules.\\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\\n\\n # Test the data of molecule 1.\\n self.assertEqual(mol1.name, 'Ap4Aase')\\n\\n # Test the data of molecule 2.\\n self.assertEqual(mol2.name, 'RNA')\",\n \"def test_wrong_length_with_filter(multi_mol_system_irregular, sequence):\\n # We exclude the second molecule. The filter excludes it based on the\\n # number of nodes, which is 15 because it has 5 residues with 3 nodes\\n # each.\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\",\\n sequence,\\n molecule_selector=lambda mol: len(mol.nodes) != (5 * 3),\\n )\\n with pytest.raises(ValueError):\\n processor.run_system(multi_mol_system_irregular)\",\n \"def is_standard_residue(self):\\n return False\",\n \"def test_setup_explicit_solvation_system():\\n with mmtools.utils.temporary_directory() as tmp_dir:\\n yaml_script = get_template_script(tmp_dir)\\n del yaml_script['experiments']\\n exp_builder = ExperimentBuilder(yaml_script)\\n output_dir = os.path.dirname(\\n exp_builder._db.get_system('hydration-system')[0].position_path)\\n\\n # Test that output file exists and that it has correct components\\n expected_resnames = {'solvent1': set(['TOL', 'WAT']), 'solvent2': set(['TOL'])}\\n for phase in expected_resnames:\\n found_resnames = set()\\n pdb_path = os.path.join(output_dir, phase + '.pdb')\\n prmtop_path = os.path.join(output_dir, phase + '.prmtop')\\n inpcrd_path = os.path.join(output_dir, phase + '.inpcrd')\\n\\n with open(pdb_path, 'r') as f:\\n for line in f:\\n if len(line) > 10 and line[:5] != 'CRYST':\\n found_resnames.add(line[17:20])\\n\\n assert os.path.exists(prmtop_path)\\n assert os.path.exists(inpcrd_path)\\n assert os.path.getsize(prmtop_path) > 0\\n assert os.path.getsize(inpcrd_path) > 0\\n assert found_resnames == expected_resnames[phase]\",\n \"def test_nothing_perceived_dipeptide(self):\\n from openff.toolkit._tests.create_molecules import dipeptide as create_dipeptide\\n\\n dipeptide = create_dipeptide()\\n\\n with pytest.raises(KeyError):\\n assert dipeptide.atoms[0].metadata[\\\"residue_name\\\"] is None\\n with pytest.raises(KeyError):\\n assert \\\"ALA\\\" == dipeptide.atoms[10].metadata[\\\"residue_name\\\"]\\n with pytest.raises(KeyError):\\n assert 1 == dipeptide.atoms[10].metadata[\\\"residue_number\\\"]\\n with pytest.raises(KeyError):\\n assert \\\" \\\" == dipeptide.atoms[10].metadata[\\\"insertion_code\\\"]\\n with pytest.raises(AttributeError):\\n dipeptide.residues[0]\",\n \"def test_rsp_invalid(self):\\n\\n def handle(event):\\n ds = Dataset()\\n ds.PatientName = \\\"Test^test\\\"\\n return 0x0000, ds\\n\\n self.ae = ae = AE()\\n ae.acse_timeout = 5\\n ae.dimse_timeout = 0.4\\n ae.network_timeout = 5\\n ae.add_supported_context(ModalityPerformedProcedureStep)\\n scp = ae.start_server(\\n (\\\"localhost\\\", 11112), block=False, evt_handlers=[(evt.EVT_N_SET, handle)]\\n )\\n\\n ae.add_requested_context(ModalityPerformedProcedureStep)\\n assoc = ae.associate(\\\"localhost\\\", 11112)\\n assert assoc.is_established\\n\\n class DummyResponse:\\n is_valid_response = False\\n\\n class DummyDIMSE:\\n msg_queue = queue.Queue()\\n gotten = False\\n\\n def send_msg(*args, **kwargs):\\n return\\n\\n def get_msg(self, *args, **kwargs):\\n if not self.gotten:\\n self.gotten = True\\n return None, DummyResponse()\\n return None, None\\n\\n assoc._reactor_checkpoint.clear()\\n while not assoc._is_paused:\\n time.sleep(0.01)\\n assoc.dimse = DummyDIMSE()\\n mod_list = Dataset()\\n mod_list.PatientName = \\\"Test^test\\\"\\n status, ds = assoc.send_n_set(\\n mod_list, ModalityPerformedProcedureStep, \\\"1.2.840.10008.5.1.1.40.1\\\"\\n )\\n\\n assert status == Dataset()\\n assert ds is None\\n assert assoc.is_aborted\\n\\n scp.shutdown()\",\n \"def test_perceive_residues_natoms_mainchain_glutamic_acid(self, strict_chirality):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/MainChain_GLU.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def _loop_raw(raw):\\n raise NotImplemented\",\n \"def assignResonanceResidue(resonance, residue):\\n\\n\\n #print 'assignResonanceResidue', makeResonanceGuiName(resonance), residue.seqId\\n if residue:\\n # we could be setting the residue to None\\n if not setAssignmentMolSystem(residue, resonance=resonance):\\n return\\n \\n resonanceSet = resonance.resonanceSet\\n if resonanceSet:\\n assignNames = set()\\n \\n for atomSet in resonanceSet.atomSets:\\n assignNames.add(atomSet.name)\\n \\n else:\\n assignNames = set(resonance.assignNames)\\n \\n assignedResidue = getResonanceResidue(resonance)\\n \\n if assignNames and (assignedResidue is not residue):\\n resonance.setAssignNames(assignNames)\\n \\n if residue:\\n atomSets = []\\n isotopeCode = resonance.isotopeCode\\n if ('HA' in assignNames) and (residue.ccpCode == 'Gly'):\\n assignNames.add('HA2')\\n assignNames.add('HA3')\\n \\n for atom in residue.atoms:\\n element = atom.chemAtom.elementSymbol\\n \\n if isotopeCode[-len(element):] != element:\\n continue\\n \\n atomSet = atom.atomSet\\n if atomSet:\\n if atomSet.name in assignNames:\\n if atomSet not in atomSets:\\n atomSets.append(atomSet)\\n \\n if resonanceSet:\\n resonanceSet.delete()\\n \\n if atomSets:\\n # might not always find atom sets\\n # e.g. if changing residue types\\n assignAtomsToRes(atomSets,resonance,None)\\n else:\\n if resonanceSet:\\n resonanceSet.delete()\\n #updateResonanceAnnotation(resonance)\\n\\n if not resonance.resonanceGroup:\\n nmrProject = resonance.nmrProject\\n spinSystem = None\\n molResidue = residue.molResidue\\n ccpCode = molResidue.ccpCode\\n molType = molResidue.molType\\n spinSystems = nmrProject.findAllResonanceGroups(ccpCode=ccpCode,\\n molType=molType)\\n \\n for extantSpinSystem in spinSystems:\\n if extantSpinSystem.residue is residue:\\n spinSystem = extantSpinSystem\\n break\\n \\n if not spinSystem:\\n spinSystem = nmrProject.newResonanceGroup()\\n assignSpinSystemResidue(spinSystem,residue)\\n \\n if resonance not in spinSystem.resonances:\\n spinSystem.addResonance(resonance)\\n updateResonanceAnnotation(resonance)\\n \\n else:\\n updateResonanceAnnotation(resonance)\",\n \"def test_ipam_rirs_read(self):\\n pass\",\n \"def _readloop(self):\\r\\n\\r\\n while self._ll_alive:\\r\\n with self._rx_lock:\\r\\n data = self._Random(1)\\r\\n if len(data) != 0: # check for timeout\\r\\n self._uart_rx_queue.put(data)\",\n \"def test_perceive_residues_natoms_t4(self, strict_chirality):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/T4-protein.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def next():\\n iraw = 0\\n run = 0\\n seqno = 0\\n with db_connection() as conn:\\n with conn.cursor() as curs:\\n try:\\n curs.execute(\\\"\\\"\\\"SELECT rawdata.id,rawdata.run,rawdata.seqno,\\n slices.block1,slices.block2,\\n jobs.cluster,jobs.process\\n FROM rawdata\\n LEFT JOIN bindings\\n ON bindings.iraw = rawdata.id\\n INNER JOIN slices\\n ON slices.iraw = rawdata.id\\n LEFT JOIN jobs\\n ON slices.ijob = jobs.id\\n AND jobs.exitcode = 0\\n WHERE bindings.id IS NULL\\n ORDER BY rawdata.id,slices.block1\\n LIMIT 2000;\\n \\\"\\\"\\\")\\n slices_missing = 1\\n for row in curs.fetchall():\\n i = int(row[0])\\n if i != iraw:\\n if slices_missing == 0:\\n break\\n else:\\n run = int(row[1])\\n seqno = int(row[2])\\n slices_missing = 0\\n slices = []\\n iraw = i\\n block1 = int(row[3])\\n block2 = int(row[4])\\n if row[5] is not None and row[6] is not None:\\n cluster = int(row[5])\\n process = int(row[6])\\n slices.append((block1,block2,cluster,process))\\n else:\\n print(\\\"slices missing on\\\", row[5], row[6])\\n slices_missing += 1\\n if slices_missing:\\n return 0\\n else:\\n curs.execute(\\\"SELECT TIMEZONE('GMT', NOW());\\\")\\n now = curs.fetchone()[0]\\n curs.execute(\\\"\\\"\\\"INSERT INTO bindings\\n (iraw,starttime)\\n VALUES (%s,%s)\\n RETURNING id;\\n \\\"\\\"\\\", (iraw, now))\\n row = curs.fetchone()\\n if row:\\n ibind = int(row[0])\\n else:\\n return 0\\n except:\\n iraw = 0\\n if iraw == 0:\\n time.sleep(random.randint(1,30))\\n return -9 # collision\\n\\n workdir = str(iraw)\\n os.mkdir(workdir)\\n os.chdir(workdir)\\n badslices = []\\n for sl in slices:\\n sdir = str(sl[0]) + \\\",\\\" + str(sl[1])\\n os.mkdir(sdir)\\n tarfile = \\\"job_{0}_{1}.tar.gz\\\".format(sl[2], sl[3])\\n tarpath = input_area + \\\"/\\\" + tarfile\\n try:\\n subprocess.check_output([\\\"gfal-copy\\\", src_url + tarpath,\\n \\\"file://\\\" + os.getcwd() + \\\"/\\\" + tarfile])\\n except:\\n sys.stderr.write(\\\"Error -999 on rawdata id {0}\\\".format(iraw) +\\n \\\" - job output \\\" + tarfile + \\\" is missing!\\\\n\\\")\\n sys.stderr.flush()\\n badslices.append(sdir)\\n continue\\n try:\\n subprocess.check_output([\\\"tar\\\", \\\"zxf\\\", tarfile, \\\"-C\\\", sdir])\\n except:\\n sys.stderr.write(\\\"Error -999 on rawdata id {0}\\\".format(iraw) +\\n \\\" - job output \\\" + tarfile + \\\" is not readable!\\\\n\\\")\\n sys.stderr.flush()\\n badslices.append(sdir)\\n finally:\\n os.remove(tarfile)\\n if len(badslices) > 0:\\n with db_connection() as conn:\\n with conn.cursor() as curs:\\n curs.execute(\\\"SELECT TIMEZONE('GMT', NOW());\\\")\\n now = curs.fetchone()[0]\\n curs.execute(\\\"\\\"\\\"UPDATE bindings\\n SET endtime=%s, \\n exitcode=%s,\\n details=%s\\n WHERE id = %s;\\n \\\"\\\"\\\", (now, -999, \\\":\\\".join(badslices), ibind))\\n os.chdir(\\\"..\\\")\\n shutil.rmtree(workdir)\\n return 1\\n\\n badslices += merge_evio_skims(run, seqno, slices)\\n badslices += merge_hddm_output(run, seqno, slices)\\n badslices += merge_job_info(run, seqno, slices)\\n badslices += merge_root_histos(run, seqno, slices)\\n exitcode = -len(badslices)\\n with db_connection() as comm:\\n with conn.cursor() as curs:\\n curs.execute(\\\"SELECT TIMEZONE('GMT', NOW());\\\")\\n now = curs.fetchone()[0]\\n curs.execute(\\\"\\\"\\\"UPDATE bindings\\n SET endtime=%s,\\n exitcode=%s,\\n details=%s\\n WHERE id = %s;\\n \\\"\\\"\\\", (now, exitcode, \\\":\\\".join(badslices), ibind))\\n os.chdir(\\\"..\\\")\\n shutil.rmtree(workdir)\\n return 1\",\n \"def residual_processor(self):\\n def get_file(field, solver):\\n \\\"\\\"\\\"Helper method to get the file handle for a field.\\n\\n On first invocation, it creates the file with headers. On\\n subsequent invocations it just returns the relevant file handle.\\n \\\"\\\"\\\"\\n if not field in self.res_files:\\n fh = open(join(self.logs_dir, field+\\\".dat\\\"), 'w')\\n fh.write(\\\"# Field: %s; Solver: %s\\\\n\\\"%(field, solver))\\n fh.write(\\\"Time SubIteration InitialResidual FinalResidual NoIterations\\\\n\\\")\\n self.res_files[field] = fh\\n return self.res_files[field]\\n # end get_file\\n\\n try:\\n while True:\\n rexp = (yield)\\n solver = rexp.group(1) # e.g., PCB, GAMG, etc.\\n field = rexp.group(2) # Ux, Uy, p, etc.\\n\\n icorr = self.subiter_map.get(field, 0) + 1\\n self.subiter_map[field] = icorr\\n fh = get_file(field, solver)\\n fh.write(\\n self.time_str + \\\"\\\\t%d\\\\t\\\"%icorr +\\n \\\"\\\\t\\\".join([rexp.group(i) for i in range(3, 6)]) + \\\"\\\\n\\\")\\n except GeneratorExit:\\n for fh in self.res_files.values():\\n if not fh.closed:\\n fh.close()\",\n \"def fatal_error_processor(self):\\n while True:\\n _ = (yield)\\n self.failed = True\\n self.converged = False\\n self.solve_completed = False\",\n \"def nextRes(self):\\n\\n self.current_residueFull = self.current_residue.get().split(\\\":\\\")\\n if len(self.current_residueFull) < 2:\\n res = int(self.current_residue.get())+1\\n self.current_residue.set(res)\\n self.check_residue_callback()\\n else:\\n print \\\"Please Change selection to get info...\\\"\",\n \"def test_rescore_unmask(self):\\r\\n module = CapaFactory.create(xml=self.common_shuffle_xml)\\r\\n get_request_dict = {CapaFactory.input_key(): 'mask_0'}\\r\\n module.check_problem(get_request_dict)\\r\\n # On rescore, state/student_answers should use unmasked names\\r\\n with patch.object(module.runtime, 'track_function') as mock_track_function:\\r\\n module.rescore_problem()\\r\\n mock_call = mock_track_function.mock_calls[0]\\r\\n event_info = mock_call[1][1]\\r\\n self.assertEquals(mock_call[1][0], 'problem_rescore')\\r\\n self.assertEquals(event_info['state']['student_answers'][CapaFactory.answer_key()], 'choice_2')\\r\\n self.assertIsNotNone(event_info['permutation'][CapaFactory.answer_key()])\",\n \"def iter_non_standard_residues(self):\\n fpred = lambda f: f.is_standard_residue()\\n return itertools.ifilterfalse(fpred, self.iter_fragments())\",\n \"def getResAromaticVectors(residues):\\n for res in residues.keys():\\n rtype = res.split(\\\":\\\")[1][0:3] # A:GLY48 => GLY\\n try:\\n if rtype == \\\"PHE\\\" or rtype == \\\"TYR\\\":\\n if len(residues[res]) == 6:\\n pass\\n else:\\n if DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n elif rtype == \\\"TRP\\\":\\n if len(residues[res]) >= 9:\\n residues[res] = purgeTrp(residues[res])\\n else:\\n if DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n elif rtype == \\\"HIS\\\":\\n if len(residues[res]) >= 5:\\n residues[res] = purgeHis(residues[res])\\n else:\\n if DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n elif rtype == \\\"ARG\\\":\\n residues[res] = purgeArg(residues[res])\\n if not residues[res] and DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n elif rtype == \\\"DA\\\" or rtype == \\\"A\\\":\\n if len(residues[res]) >= 10:\\n residues[res] = purgeAdenine(residues[res])\\n else:\\n if DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n elif rtype == \\\"DC\\\" or rtype == \\\"C\\\":\\n if len(residues[res]) >= 6:\\n residues[res] = purgeAdenine(residues[res])\\n else:\\n if DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n elif rtype == \\\"DG\\\" or rtype == \\\"G\\\":\\n if len(residues[res]) >= 10:\\n residues[res] = purgeAdenine(residues[res])\\n else:\\n if DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n if residues[res]:\\n residues[res] = atomsToVec(residues[res])\\n else:\\n del residues[res]\\n except:\\n if DEBUG: print \\\"Fatal error in processing residue [ %s ]\\\"% res\\n del residues[res]\\n return residues\",\n \"def test_find_surface_residues():\\n atom_dict_0 = find_surface_residues(protein, max_dist=0, scaling=1)\\n atom_dict_1 = find_surface_residues(protein, max_dist=2, scaling=1)\\n atom_dict_2 = find_surface_residues(protein, max_dist=3, scaling=1)\\n atom_dict_3 = find_surface_residues(protein, max_dist=None, scaling=1)\\n atom_dict_4 = find_surface_residues(protein, max_dist=None, scaling=2)\\n\\n assert atom_dict_0.size == 0\\n assert len(atom_dict_1) > len(atom_dict_0), ('Increasing max_dist should '\\n 'result in more/equal number '\\n 'of atoms found')\\n\\n assert len(atom_dict_2) >= len(atom_dict_1), ('Increasing max_dist should '\\n 'result in more/equal number '\\n 'of atoms found')\\n assert_array_equal(np.intersect1d(atom_dict_1['id'], atom_dict_2['id']), atom_dict_1['id'])\\n\\n if oddt.toolkit.backend == 'ob':\\n ref_len_1 = 762\\n ref_len_2 = 968\\n ref_len_3 = 654\\n ref_len_4 = 379\\n elif oddt.toolkit.backend == 'rdk' and oddt.toolkits.rdk.__version__ >= '2019.09':\\n ref_len_1 = 762\\n ref_len_2 = 968\\n ref_len_3 = 664\\n ref_len_4 = 393\\n else:\\n ref_len_1 = 759\\n ref_len_2 = 966\\n ref_len_3 = 735\\n ref_len_4 = 489\\n\\n assert len(atom_dict_1) == ref_len_1\\n assert len(atom_dict_2) == ref_len_2\\n assert len(atom_dict_3) == ref_len_3\\n assert len(atom_dict_4) == ref_len_4\\n\\n # Adding hydrogen atoms should have no effect on the result\\n protein.addh()\\n atom_dict_addh = find_surface_residues(protein, max_dist=2, scaling=1)\\n assert_array_equal(atom_dict_addh['id'], atom_dict_1['id'])\\n\\n with pytest.raises(TypeError):\\n find_surface_residues(molecule=1)\\n with pytest.raises(ValueError):\\n find_surface_residues(molecule=protein, max_dist='a')\\n with pytest.raises(ValueError):\\n find_surface_residues(molecule=protein, max_dist=[1, 1, 1])\",\n \"def is_standard_residue(self):\\n return True\",\n \"def is_standard_residue(self):\\n return True\",\n \"def test_is_in_ring(self):\\n molecule = Molecule.from_smiles(\\\"c1ccccc1\\\")\\n\\n for atom in molecule.atoms:\\n if atom.atomic_number == 6:\\n assert atom.is_in_ring()\\n\\n for bond in molecule.bonds:\\n if 1 in (bond.atom1.atomic_number, bond.atom2.atomic_number):\\n continue\\n assert bond.is_in_ring()\",\n \"def simulate_read(self):\\n\\n fastafile = ps.FastaFile(self.genome_fa)\\n # left split read\\n\\n insert = int(np.random.normal(self.insert_size, (self.insert_size / 12), 1))\\n start = int(np.random.randint(self.chr_pos_start, (self.chr_pos_end + 1)))\\n left_end = start + self.read_length\\n total_end = start + int(np.round(insert))\\n right_start = total_end - self.read_length\\n if total_end > self.chr_pos_end:\\n # split read scenario or insert spanning split read scenario\\n if left_end > self.chr_pos_end:\\n # left read spanning split read scenario\\n # left_read\\n left_dntps = self.chr_pos_end - start\\n right_dntps = self.read_length - left_dntps\\n\\n # the error could be here\\n left_split_read = fastafile.fetch(self.chr, start, self.chr_pos_end)\\n right_split_read = fastafile.fetch(self.chr, self.chr_pos_start, (self.chr_pos_start + right_dntps))\\n left_read = left_split_read + right_split_read\\n\\n # right_read\\n right_start = self.chr_pos_start + int(round(self.insert_size - left_dntps - self.read_length))\\n right_read = fastafile.fetch(self.chr, right_start, (right_start + self.read_length))\\n\\n # assertion to check the error here\\n\\n common_id = \\\"%s|%s|%s:%s-%s:%s|%s:%s|1|%s\\\" % (\\n self.read_number,\\n self.chr,\\n start,\\n self.chr_pos_end,\\n self.chr_pos_start,\\n (self.chr_pos_start + right_dntps),\\n right_start,\\n (right_start + self.read_length),\\n self.circle_id,\\n )\\n\\n else:\\n if right_start > self.chr_pos_end:\\n # insert spanning split read scenario\\n left_read = fastafile.fetch(self.chr, start, (start + self.read_length))\\n right_start = self.chr_pos_start + (right_start - self.chr_pos_end)\\n right_read = fastafile.fetch(self.chr, right_start, (right_start + self.read_length))\\n common_id = \\\"%s|%s|%s:%s|%s:%s|3|%s\\\" % (\\n self.read_number,\\n self.chr,\\n start,\\n (start + self.read_length),\\n right_start,\\n (right_start + self.read_length),\\n self.circle_id,\\n )\\n else:\\n # right split read scenario\\n assert right_start <= self.chr_pos_end\\n assert (right_start + self.read_length) > self.chr_pos_end\\n left_read = fastafile.fetch(self.chr, start, (start + self.read_length))\\n\\n # compute right dntps\\n left_dntps = self.chr_pos_end - right_start\\n right_dntps = self.read_length - left_dntps\\n left_split_read = fastafile.fetch(self.chr, right_start, self.chr_pos_end)\\n right_split_read = fastafile.fetch(self.chr, self.chr_pos_start, (self.chr_pos_start + right_dntps))\\n right_read = left_split_read + right_split_read\\n common_id = \\\"%s|%s|%s:%s|%s:%s-%s:%s|2|%s\\\" % (\\n self.read_number,\\n self.chr,\\n start,\\n (start + self.read_length),\\n right_start,\\n self.chr_pos_end,\\n self.chr_pos_start,\\n (self.chr_pos_start, right_dntps),\\n self.circle_id,\\n )\\n\\n else:\\n # non split read scenario\\n left_read = fastafile.fetch(self.chr, start, (start + self.read_length))\\n # correct right read start\\n right_read = fastafile.fetch(self.chr, right_start, (right_start + self.read_length))\\n common_id = \\\"%s|%s|%s:%s|%s:%s|0|%s\\\" % (\\n self.read_number,\\n self.chr,\\n start,\\n (start + self.read_length),\\n right_start,\\n (right_start + self.read_length),\\n self.circle_id,\\n )\\n\\n return (right_read, left_read, common_id)\",\n \"def test_function_fuel_sum(data, mode_constrained, space_heating_enduses):\\n fuel_in = 0\\n fuel_in_solid_fuel = 0\\n fuel_in_gas = 0\\n fuel_in_elec = 0\\n fuel_in_oil = 0\\n fuel_in_heat = 0\\n fuel_in_hydrogen = 0\\n fuel_in_biomass = 0\\n\\n fuel_heating_all_fueltypes = 0\\n fuel_heating_gas = 0\\n tot_heating = 0\\n #mode_constrained = True #SCRAP\\n\\n for region in data['rs_fuel_disagg']:\\n for enduse in data['rs_fuel_disagg'][region]:\\n fuel_in += np.sum(data['rs_fuel_disagg'][region][enduse])\\n fuel_in_heat += np.sum(data['rs_fuel_disagg'][region][enduse][data['lookups']['fueltypes']['heat']])\\n\\n if mode_constrained == False and enduse in space_heating_enduses: #Exclude inputs for heating\\n tot_heating += np.sum(data['rs_fuel_disagg'][region][enduse])\\n #pass\\n else:\\n fuel_in_elec += np.sum(data['rs_fuel_disagg'][region][enduse][data['lookups']['fueltypes']['electricity']])\\n fuel_in_gas += np.sum(data['rs_fuel_disagg'][region][enduse][data['lookups']['fueltypes']['gas']])\\n fuel_in_hydrogen += np.sum(data['rs_fuel_disagg'][region][enduse][data['lookups']['fueltypes']['hydrogen']])\\n fuel_in_oil += np.sum(data['rs_fuel_disagg'][region][enduse][data['lookups']['fueltypes']['oil']])\\n fuel_in_solid_fuel += np.sum(data['rs_fuel_disagg'][region][enduse][data['lookups']['fueltypes']['solid_fuel']])\\n fuel_in_biomass += np.sum(data['rs_fuel_disagg'][region][enduse][data['lookups']['fueltypes']['biomass']])\\n \\n for region in data['ss_fuel_disagg']:\\n for enduse in data['ss_fuel_disagg'][region]:\\n for sector in data['ss_fuel_disagg'][region][enduse]:\\n fuel_in += np.sum(data['ss_fuel_disagg'][region][enduse][sector])\\n fuel_in_heat += np.sum(data['ss_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['heat']])\\n\\n if mode_constrained == False and enduse in space_heating_enduses:\\n tot_heating += np.sum(data['ss_fuel_disagg'][region][enduse][sector])\\n else:\\n fuel_in_elec += np.sum(data['ss_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['electricity']])\\n fuel_in_gas += np.sum(data['ss_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['gas']])\\n fuel_in_hydrogen += np.sum(data['ss_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['hydrogen']])\\n fuel_in_oil += np.sum(data['ss_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['oil']])\\n fuel_in_solid_fuel += np.sum(data['ss_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['solid_fuel']])\\n fuel_in_biomass += np.sum(data['ss_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['biomass']])\\n \\n for region in data['is_fuel_disagg']:\\n for enduse in data['is_fuel_disagg'][region]:\\n for sector in data['is_fuel_disagg'][region][enduse]:\\n fuel_in += np.sum(data['is_fuel_disagg'][region][enduse][sector])\\n fuel_in_heat += np.sum(data['is_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['heat']])\\n\\n if mode_constrained == False and enduse in space_heating_enduses:\\n tot_heating += np.sum(data['is_fuel_disagg'][region][enduse][sector])\\n else:\\n fuel_in_elec += np.sum(data['is_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['electricity']])\\n fuel_in_gas += np.sum(data['is_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['gas']])\\n fuel_in_hydrogen += np.sum(data['is_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['hydrogen']])\\n fuel_in_oil += np.sum(data['is_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['oil']])\\n fuel_in_solid_fuel += np.sum(data['is_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['solid_fuel']])\\n fuel_in_biomass += np.sum(data['is_fuel_disagg'][region][enduse][sector][data['lookups']['fueltypes']['biomass']])\\n \\n return fuel_in, fuel_in_biomass, fuel_in_elec, fuel_in_gas, fuel_in_heat, fuel_in_hydrogen, fuel_in_solid_fuel, fuel_in_oil, tot_heating\",\n \"def test_reset(self):\\n ran = []\\n def foo():\\n ran.append(None)\\n\\n c = task.Clock()\\n lc = TestableLoopingCall(c, foo)\\n lc.start(2, now=False)\\n c.advance(1)\\n lc.reset()\\n c.advance(1)\\n self.assertEqual(ran, [])\\n c.advance(1)\\n self.assertEqual(ran, [None])\",\n \"def test_exception_list_empty(self):\\n complex_id_list = range(1,4) #1~3\\n dataloader = lambda d: d\\n calc_func = lambda d1,d2: d1 + d2\\n \\n _, actual = complex_pairwise_calc(complex_id_list, dataloader, calc_func, symmetry=False)\\n expected = []\\n\\n self.assertEqual(actual, expected)\",\n \"def test_residues(parse_mmtf):\\n parse_mmtf.assertEqual(len(parse_mmtf.mmcif_res), len(parse_mmtf.mmtf_res))\\n for i, e in enumerate(parse_mmtf.mmcif_res):\\n mmcif_r = parse_mmtf.mmcif_res[i]\\n mmtf_r = parse_mmtf.mmtf_res[i]\\n parse_mmtf.assertEqual(mmtf_r.level, mmcif_r.level)\\n parse_mmtf.assertEqual(mmtf_r.disordered, mmcif_r.disordered)\\n parse_mmtf.assertEqual(mmtf_r.resname, mmcif_r.resname)\\n parse_mmtf.assertEqual(mmtf_r.segid, mmcif_r.segid)\\n parse_mmtf.mmcif_atoms = [x for x in mmcif_r.get_atom()]\\n parse_mmtf.mmtf_atoms = [x for x in mmtf_r.get_atom()]\\n test_atoms(parse_mmtf=parse_mmtf)\",\n \"def test_run_loop_exc(self):\\n with self.assertRaises(ExecutionException):\\n pyint = Interpreter(limit=1)\\n pyint.run(code=BF_CODE_LOOP_TWICE)\",\n \"def test_fleur_relax_continue_converged(self, run_with_cache, mock_code_factory):\\n assert False\",\n \"def isResidueAssigned(residue):\\n\\n for atom in residue.atoms:\\n if atom.atomSet:\\n if atom.atomSet.resonanceSets:\\n return True\\n \\n return False\",\n \"def test_stop_resume(self):\\n self.create_sample_data_set_dir(\\\"node59p1_step1.dat\\\", TELEM_DIR, \\\"node59p1.dat\\\",\\n copy_metadata=False)\\n driver_config = self._driver_config()['startup_config']\\n sio_mule_config = driver_config['harvester'][DataSourceKey.PHSEN_ABCDEF_SIO_MULE]\\n fullfile = os.path.join(sio_mule_config['directory'], sio_mule_config['pattern'])\\n mod_time = os.path.getmtime(fullfile)\\n\\n # Create and store the new driver state\\n self.memento = {DataSourceKey.PHSEN_ABCDEF_SIO_MULE: {\\n \\\"node59p1.dat\\\": {\\n DriverStateKey.FILE_SIZE: 911,\\n DriverStateKey.FILE_CHECKSUM: '8b7cf73895eded0198b3f3621f962abc',\\n DriverStateKey.FILE_MOD_DATE: mod_time,\\n DriverStateKey.PARSER_STATE: {\\n StateKey.IN_PROCESS_DATA: [],\\n StateKey.UNPROCESSED_DATA:[[0, 172]],\\n StateKey.FILE_SIZE: 911\\n }\\n }\\n }}\\n\\n self.driver = self._get_driver_object(memento=self.memento)\\n\\n # create some data to parse\\n self.clear_async_data()\\n self.create_sample_data_set_dir(\\\"node59p1_step2.dat\\\", TELEM_DIR, \\\"node59p1.dat\\\",\\n copy_metadata=False)\\n\\n self.driver.start_sampling()\\n\\n # verify data is produced\\n self.assert_data(PhsenParserDataParticle, 'test_data_2.txt.result.yml',\\n count=2, timeout=10)\",\n \"def run(self):\\n while True:\\n if self.job_q.empty():\\n self.message_q.put(False)\\n return\\n try:\\n smolecule = self.job_q.get()\\n self.data_pointer[smolecule].get_adp(self.Temp)\\n except IndexError:\\n self.message_q.put((smolecule, None))\\n try:\\n self.message_q.put((smolecule, [j.adp['cart_int'] for j in self.data_pointer[smolecule].atoms]))\\n except KeyError:\\n # =======================================================\\n # self.message_q.put((molecule,[0 for i in self.data_pointer[molecule].atoms]))\\n #=======================================================\\n pass\",\n \"def test_ipam_rirs_partial_update(self):\\n pass\",\n \"def test_resids(self):\\n cr = CaseReader(self.filename)\\n last_case = cr.get_case(-1)\\n self.assertIsNone(last_case.resids,\\n \\\"Case erroneously contains resids.\\\")\",\n \"def testrescorr():\\n tau = np.zeros((2,50))\\n tau[0,25] = 2\\n tau[1,23] = 3\\n tau2 = spec_utils.res_corr(tau, 2, 8)\\n #Check flux conserved\\n assert np.abs(np.sum(tau2[0,:])/ np.sum(tau[0,:]) -1) < 1e-6\\n assert np.abs(np.sum(tau2[1,:])/ np.sum(tau[1,:]) -1) < 1e-6\\n #Check expanded by expected amount\\n for i in (0,1):\\n assert np.size(np.where(tau2[i,:]> 0)) == 15\",\n \"def waitOverlappedDone(self, count, timeout):\\n startTime = time.time()\\n while True: #wait until measuring flag goes to 0\\n try:\\n measured = self.handle.ask(\\\":DATA:POIN?;\\\")\\n measured = measured.strip() #remove CR \\n measured = int(measured) #convert to number\\n if measured == count: #final number of samples achieved\\n break;\\n except Exception:\\n print('Dvm34411.waitOverlappedDone() polling failed !')\\n raise\\n \\n if time.time() - startTime > timeout:\\n print('Dvm34411.waitOverlappedDone() timeout !')\\n return False\\n \\n samples = [] \\n for i in range(0, count):\\n try:\\n reading = self.handle.ask('R? 1;') #definite-Length block format\\n except Exception: \\n print('Dvm34411.Reading results failed !')\\n raise;\\n #DLB: '#' followed by number od decimal digits to follow\\n #the decimal number is length of data in bytes\\n if reading[0] != '#':\\n print('Dvm34411.DLB format error - # expected !')\\n return False\\n digits = int(reading[1])\\n reading = reading[2 + digits:]\\n samples.append(reading.strip())\\n \\n return samples\",\n \"def test_08(self, test):\\r\\n globalConfig.test = test\\r\\n\\r\\n forbiddenRoutes = []\\r\\n outputList = getOutputList()\\r\\n inputList = getInputList()\\r\\n if len(inputList) == 0 or len(outputList) == 0:\\r\\n return test.UNCLEAR(\\\"Not tested. No resources found.\\\")\\r\\n\\r\\n for outputInstance in outputList:\\r\\n sourceID = outputInstance.getSourceID()\\r\\n for inputInstance in inputList:\\r\\n inputParent = inputInstance.getParent()\\r\\n if inputParent['type'] == \\\"source\\\" and sourceID == inputParent['id']:\\r\\n route = {\\r\\n \\\"input\\\": inputInstance,\\r\\n \\\"output\\\": outputInstance\\r\\n }\\r\\n forbiddenRoutes.append(route)\\r\\n\\r\\n for route in forbiddenRoutes:\\r\\n outputCaps = route['output'].getCaps()\\r\\n msg = (\\\"It is possible to create a loop using re-entrant matrices \\\"\\r\\n \\\"between Input {} and Output {}\\\".format(route['input'].id, route['output'].id))\\r\\n try:\\r\\n routableInputs = outputCaps['routable_inputs']\\r\\n except KeyError:\\r\\n return test.FAIL(\\\"Could not find 'routable_inputs' in /caps \\\"\\r\\n \\\"for Output {}\\\".format(route['output'].id))\\r\\n if routableInputs is None or route['input'].id in routableInputs:\\r\\n return test.FAIL(msg)\\r\\n return test.PASS()\",\n \"def test_get_counturingErr(self):\\n for app_num, servo_type in app_nr.items():\\n try:\\n par = self.get_parameter(servo_type, app_num, COUNTURING_ERR_IDX, COUNTURING_ERR_SUB)\\n param_obj = self.__dict__[servo_type]._get_counturingErr()\\n acs_par, completion = param_obj.get_sync()\\n if(completion.code):\\n print \\\"\\\\nError code found in counturingErr...\\\"\\n continue\\n self.data_match(acs_par, par)\\n except NackEx:\\n continue\",\n \"def test_apply_ridit(self):\\n x, x_rand, s = self.create_testdata()\\n task = mmRDTR()\\n s = task.check_sparse(s)\\n\\n for data in [x, x_rand, s]:\\n #get ecdf for data\\n Fn=task.make_ECDF(data)\\n out=task.apply_ridit( data, Fn )\\n # check same dimension\\n self.assertEqual(np.all(data.shape==out.shape),True)\\n # check mean almost equal to 0\\n for i in range(data.shape[1]):\\n self.assertEqual(round(out[:,i].mean(),8),0)\\n # check if works with newdata\\n newdata=data[:2]\\n out=task.apply_ridit( newdata, Fn )\\n # check same dimension\\n self.assertEqual(np.all(newdata.shape==out.shape),True)\",\n \"def test_check_for_max_rmsd():\\n phil_groups = ncs_group_master_phil.fetch(\\n iotbx.phil.parse(phil_str)).extract()\\n pdb_inp = iotbx.pdb.input(source_info=None, lines=test_pdb_str_2)\\n ncs_obj_phil = ncs.input(\\n hierarchy=pdb_inp.construct_hierarchy(),\\n ncs_phil_groups=phil_groups.ncs_group)\\n nrgl = ncs_obj_phil.get_ncs_restraints_group_list()\\n pdb_inp = iotbx.pdb.input(lines=test_pdb_str_2,source_info=None)\\n ph = pdb_inp.construct_hierarchy()\\n # passing test\\n assert nrgl.check_for_max_rmsd(ph.atoms().extract_xyz() ,chain_max_rmsd=1)\\n # make sure test fails when it suppose to\\n nrgl[0].copies[1].t = matrix.col([100, -89.7668, 5.8996])\\n assert not nrgl.check_for_max_rmsd(ph.atoms().extract_xyz(),chain_max_rmsd=1)\",\n \"def test_pure_prisoners_dilemma(_):\\n game = gamegen.sym_2p2s_game(2, 0, 3, 1) # prisoners dilemma\\n eqm = [0, 2]\\n\\n assert (\\n regret.pure_strategy_regret(game, eqm) == 0\\n ), \\\"Known equilibrium was not zero regret\\\"\",\n \"def check_termination(self) :\\n\\t\\trc_all = self.rc1[-1]+self.rc2[-1]\\n\\t\\tif rc_all == 0 and self.ssep[-1] < self.tol \\\\\\n\\t\\t\\t and self.ssed[-1] < self.tol : \\n\\t\\t\\tself.converged = True\\n\\t\\t\\tself.continueLoop = False \\n\\t\\n\\t\\tif self.loopiter >= self.maxiter : \\n\\t\\t\\tself.maxiter_exceeded = True\\n\\t\\t\\tself.converged = False\\n\\t\\t\\tself.continueLoop = False\\n\\t\\n\\t# Check any obvious SSE inconsistencies\\n\\t\\tif self.ssep[-1] > self.sseMax or self.ssed[-1] > self.sseMax : \\n\\t\\t\\tself.continueLoop = False\",\n \"def test_perceive_residues_natoms_mainchain_alanine(self, strict_chirality):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/MainChain_ALA.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def test_read_fail1(self):\\n mod_fn = os.path.join(tests.TEST_DATA_PATH, 'segmentations', 'test_bad_data1.mod')\\n with self.assertRaises(ValueError):\\n modreader.get_data(mod_fn) # missing 'IMOD' start\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.8301634","0.82040375","0.7788324","0.7710455","0.7556808","0.72358716","0.70310825","0.6912135","0.66328","0.66025203","0.6565843","0.6549843","0.6462473","0.6374776","0.6350188","0.6347619","0.6336793","0.61492753","0.6104927","0.58747214","0.5848667","0.5838961","0.57871944","0.5696865","0.56319976","0.5603985","0.55891556","0.55723614","0.55177695","0.5511375","0.5455901","0.54265225","0.54154843","0.53988224","0.53899276","0.5322307","0.53133273","0.5307116","0.52630764","0.51878285","0.51856154","0.5144574","0.5112594","0.5077262","0.50525016","0.50430244","0.5041752","0.50359803","0.5033721","0.5032536","0.5016672","0.50151837","0.50151837","0.50151837","0.5014408","0.49742487","0.4972277","0.49434987","0.49430272","0.49362162","0.49268603","0.4926499","0.49057844","0.49032328","0.48893884","0.48856795","0.488518","0.4878607","0.4878486","0.48740137","0.48726046","0.48406285","0.48383096","0.48327056","0.48313946","0.48085028","0.48085028","0.48040533","0.47988105","0.47907937","0.47895837","0.47780162","0.4775549","0.47695065","0.47630373","0.476262","0.47618702","0.4755937","0.4754138","0.47402424","0.47388387","0.47377974","0.47214335","0.47116947","0.47094905","0.47031036","0.4702393","0.4701867","0.46973667","0.4690105"],"string":"[\n \"0.8301634\",\n \"0.82040375\",\n \"0.7788324\",\n \"0.7710455\",\n \"0.7556808\",\n \"0.72358716\",\n \"0.70310825\",\n \"0.6912135\",\n \"0.66328\",\n \"0.66025203\",\n \"0.6565843\",\n \"0.6549843\",\n \"0.6462473\",\n \"0.6374776\",\n \"0.6350188\",\n \"0.6347619\",\n \"0.6336793\",\n \"0.61492753\",\n \"0.6104927\",\n \"0.58747214\",\n \"0.5848667\",\n \"0.5838961\",\n \"0.57871944\",\n \"0.5696865\",\n \"0.56319976\",\n \"0.5603985\",\n \"0.55891556\",\n \"0.55723614\",\n \"0.55177695\",\n \"0.5511375\",\n \"0.5455901\",\n \"0.54265225\",\n \"0.54154843\",\n \"0.53988224\",\n \"0.53899276\",\n \"0.5322307\",\n \"0.53133273\",\n \"0.5307116\",\n \"0.52630764\",\n \"0.51878285\",\n \"0.51856154\",\n \"0.5144574\",\n \"0.5112594\",\n \"0.5077262\",\n \"0.50525016\",\n \"0.50430244\",\n \"0.5041752\",\n \"0.50359803\",\n \"0.5033721\",\n \"0.5032536\",\n \"0.5016672\",\n \"0.50151837\",\n \"0.50151837\",\n \"0.50151837\",\n \"0.5014408\",\n \"0.49742487\",\n \"0.4972277\",\n \"0.49434987\",\n \"0.49430272\",\n \"0.49362162\",\n \"0.49268603\",\n \"0.4926499\",\n \"0.49057844\",\n \"0.49032328\",\n \"0.48893884\",\n \"0.48856795\",\n \"0.488518\",\n \"0.4878607\",\n \"0.4878486\",\n \"0.48740137\",\n \"0.48726046\",\n \"0.48406285\",\n \"0.48383096\",\n \"0.48327056\",\n \"0.48313946\",\n \"0.48085028\",\n \"0.48085028\",\n \"0.48040533\",\n \"0.47988105\",\n \"0.47907937\",\n \"0.47895837\",\n \"0.47780162\",\n \"0.4775549\",\n \"0.47695065\",\n \"0.47630373\",\n \"0.476262\",\n \"0.47618702\",\n \"0.4755937\",\n \"0.4754138\",\n \"0.47402424\",\n \"0.47388387\",\n \"0.47377974\",\n \"0.47214335\",\n \"0.47116947\",\n \"0.47094905\",\n \"0.47031036\",\n \"0.4702393\",\n \"0.4701867\",\n \"0.46973667\",\n \"0.4690105\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8984354"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81495,"cells":{"query":{"kind":"string","value":"Test the proper operation of the residue loop when no data pipe is present. The function tested is pipe_control.mol_res_spin.residue_loop()."},"document":{"kind":"string","value":"def test_residue_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for residue in mol_res_spin.residue_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_molecule_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for molecule in mol_res_spin.molecule_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def test_spin_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for spin in mol_res_spin.spin_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_residue_loop(self):\n\n # Loop over the residues.\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\n # Test the selection.\n self.assertEqual(res.num, 2)\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)","def test_return_residue_pipe_fail(self):\n\n # Try to get a residue from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def test_molecule_loop_no_selection(self):\n\n # Molecule data.\n name = ['Ap4Aase', 'RNA']\n\n # Loop over the molecules.\n i = 0\n for mol in mol_res_spin.molecule_loop():\n # Test the molecule names.\n self.assertEqual(mol.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def test_molecule_loop(self):\n\n # Loop over the molecules.\n for mol in mol_res_spin.molecule_loop('#RNA'):\n # Test the molecule name.\n self.assertEqual(mol.name, 'RNA')\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_spin_loop_no_selection(self):\n\n # Spin data.\n select = [0, 1, 0, 0, 1, 1, 0, 1]\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 8)","def test_spin_loop(self):\n\n # Spin data.\n select = [1, 0]\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, 'N5')\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 2)","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_return_molecule_pipe_fail(self):\n\n # Try to get a molecule from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')","def test_return_spin_pipe_fail(self):\n\n # Try to get a spin from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')","def test_count_spins_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Test for the error.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.count_spins)","def test_spin_loop_multiatom(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_return_residue(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_residue(':1')\n res2 = mol_res_spin.return_residue(selection=':2')\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\n\n # Test the data of residue 1.\n self.assertEqual(res1.num, 1)\n self.assertEqual(res1.name, None)\n\n # Test the data of residue 2.\n self.assertEqual(res2.num, 2)\n self.assertEqual(res2.name, 'Glu')\n\n # Test the data of residue 4.\n self.assertEqual(res4.num, 4)\n self.assertEqual(res4.name, 'Pro')\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5.num, -5)\n self.assertEqual(res5.name, None)\n self.assertEqual(res5.spin[1].name, 'N5')","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_spin_loop_wildcard(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N*'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_wrong_length(multi_mol_system_irregular, sequence):\n processor = dssp.AnnotateResidues(\"test\", sequence)\n with pytest.raises(ValueError):\n processor.run_system(multi_mol_system_irregular)","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_empty_with_filter(multi_mol_system_irregular):\n sequence = \"not empty\"\n processor = dssp.AnnotateResidues(\n \"test\", sequence, molecule_selector=lambda mol: False\n )\n with pytest.raises(ValueError):\n processor.run_system(multi_mol_system_irregular)","def test_count_no_spins(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 0)","def test_multi_molecules_cycle_one(self, multi_mol_system_irregular):\n sequence = \"A\"\n expected = [sequence] * (15 * 3)\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_irregular)\n found = self.sequence_from_system(multi_mol_system_irregular, \"test\")\n assert found == expected","def test_run_loop_success(self):\n found = False\n pyint = Interpreter(limit=15)\n try:\n pyint.run(code=BF_CODE_LOOP_TWICE)\n except SystemExit: \n found = True\n self.assertFalse(found)","def test_empty_system_empty_sequence():\n system = vermouth.system.System()\n sequence = \"\"\n processor = dssp.AnnotateResidues(\"test\", sequence)\n try:\n processor.run_system(system)\n except ValueError:\n pytest.fail(\"Should not have raised a ValueError.\")","def test_run_molecule_not_selected(self, single_mol_system):\n sequence = \"ABCDE\"\n processor = dssp.AnnotateResidues(\n \"test\", sequence, molecule_selector=lambda mol: False\n )\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert vermouth.utils.are_all_equal(found)\n assert found[0] is None","def test_RUMI():\r\n\r\n start = 11051\r\n end = 11902\r\n read_poems(start, end)","def test_single_molecules_cycle_one(self, single_mol_system):\n sequence = \"A\"\n expected = [sequence] * (5 * 3)\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def test_return_single_residue_info(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_single_residue_info('1')\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\n res5 = mol_res_spin.return_single_residue_info('-5')\n\n # Test the data of residue 1.\n self.assertEqual(res1, (1, None))\n\n # Test the data of residue 2.\n self.assertEqual(res2, (2, 'Glu'))\n\n # Test the data of residue 4.\n self.assertEqual(res4, (4, 'Pro'))\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5, (-5, None))","def test_empty_system_error():\n system = vermouth.system.System()\n sequence = \"not empty\"\n processor = dssp.AnnotateResidues(\"test\", sequence)\n with pytest.raises(ValueError):\n processor.run_system(system)","def test_multi_molecules_cycle(self, multi_mol_system_regular, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n expected = expected * 3\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_regular)\n found = self.sequence_from_system(multi_mol_system_regular, \"test\")\n assert found == expected","def test_wrong_length_with_filter(multi_mol_system_irregular, sequence):\n # We exclude the second molecule. The filter excludes it based on the\n # number of nodes, which is 15 because it has 5 residues with 3 nodes\n # each.\n processor = dssp.AnnotateResidues(\n \"test\",\n sequence,\n molecule_selector=lambda mol: len(mol.nodes) != (5 * 3),\n )\n with pytest.raises(ValueError):\n processor.run_system(multi_mol_system_irregular)","def test_return_single_residue_info_fail(self):\n\n # Ask for a few residues.\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')","def test_invoke_pipe_not_found():\n\n testapp = holocron.Application()\n\n with pytest.raises(ValueError) as excinfo:\n next(testapp.invoke(\"test\"))\n\n assert str(excinfo.value) == \"no such pipe: 'test'\"","def test_perceive_residues_natoms_mainchain_arginine(self, strict_chirality):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/MainChain_ARG.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def check_residue_callback(self):\n\n if not self.check_for_residue_existance():\n return\n\n self.listbox_current_designs.delete(0, END)\n self.current_residueFull = self.current_residue.get().split(\":\")\n\n if len(self.current_residueFull) > 1:\n self.listbox_restypes.delete(9)\n self.listbox_restypes.insert(9, \"Conserved\")\n else:\n res = self.current_residueFull[0] +\":\"+self.current_chain.get()\n #print res\n if not self.pose.total_residue():\n return\n\n resType = self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get()))\n try:\n resName = self.pose.residue(resType).name()\n except PyRosettaException:\n print \"Residue does not exist in PDB...\"\n return\n\n\n self.current_residue_name_full.set(resName)\n three_letter_name = resName.split(\"_\")[0]; #Fix for Rosetta designated chain endings, His_d\n self.current_residue_name.set(resName)\n\n #Fix for not having data for certain residue types:\n try:\n self.design_accessible_sa.set(self.residue_definitions.resinfo[three_letter_name][0])\n self.design_relative_mutability.set(self.residue_definitions.resinfo[three_letter_name][1])\n self.design_surface_probability.set(self.residue_definitions.resinfo[three_letter_name][2])\n except KeyError:\n print \"No Data for restype\"\n self.design_accessible_sa.set(\"\")\n self.design_relative_mutability.set(\"\")\n self.design_surface_probability.set(\"\")\n\n con = \"Conserved:\" +three_letter_name\n self.listbox_restypes.delete(9)\n self.listbox_restypes.insert(9, con)\n if self.DesignDic.has_key(res):\n for residues in self.DesignDic[res]:\n self.listbox_current_designs.insert(END, residues)","def test_circularloop(self):\n cmd = f\"{SRC_LISTER} -i {PWD}/main\"\n with subprocess.Popen(\n shlex.split(cmd), stdout=subprocess.PIPE, stderr=subprocess.PIPE\n ) as proc:\n try:\n out, err = proc.communicate(timeout=5)\n assert len(err.strip()) > 0, \"Expected a circular reference error\"\n except subprocess.TimeoutExpired as te:\n print(\"Unexpected parser timeout during infinite loop test\")","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def test_78_continue(self):\n\t\tinput = \"\"\"procedure main(); var x:integer;\n\t\tbegin while(true)do begin\n\t\twith x:integer; do with x:real; do begin\n\t\t\tif (x>0) then continue;\n\t\t\twith x:integer; do if (x=0) then return;\n\t\tend{with} continue; end{while} continue; end\"\"\"\n\t\texpect = \"Continue Not In Loop\"\n\t\tself.assertTrue(TestChecker.test(input,expect,478))","def waitOverlappedDone(self, count, timeout):\n startTime = time.time()\n while True: #wait until measuring flag goes to 0\n try:\n measured = self.handle.ask(\":DATA:POIN?;\")\n measured = measured.strip() #remove CR \n measured = int(measured) #convert to number\n if measured == count: #final number of samples achieved\n break;\n except Exception:\n print('Dvm34411.waitOverlappedDone() polling failed !')\n raise\n \n if time.time() - startTime > timeout:\n print('Dvm34411.waitOverlappedDone() timeout !')\n return False\n \n samples = [] \n for i in range(0, count):\n try:\n reading = self.handle.ask('R? 1;') #definite-Length block format\n except Exception: \n print('Dvm34411.Reading results failed !')\n raise;\n #DLB: '#' followed by number od decimal digits to follow\n #the decimal number is length of data in bytes\n if reading[0] != '#':\n print('Dvm34411.DLB format error - # expected !')\n return False\n digits = int(reading[1])\n reading = reading[2 + digits:]\n samples.append(reading.strip())\n \n return samples","def test_boolean_and_selection(self):\n\n # The selection loop:\n sel = list(mol_res_spin.residue_loop(\"#Ap4Aase:4 & :Pro\"))\n\n # Test:\n self.assertEqual(len(sel), 1)\n for res in sel:\n self.assert_(res.name == \"Pro\" and res.num == 4)","def test_test(self):\n\n # The following should do nothing as the pipes exist.\n pipes.check_pipe()\n pipes.check_pipe('orig')\n pipes.check_pipe('empty')\n\n # Assert that a RelaxNoPipeError occurs when the pipe doesn't exist.\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe, 'x')\n\n # Reset relax.\n reset()\n\n # Now none of the following pipes exist, hence errors should be thrown.\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe)\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe, 'orig')\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe, 'empty')","def test_run_molecule(self, single_mol_system):\n sequence = \"ABCDE\"\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def test_setup_explicit_solvation_system():\n with mmtools.utils.temporary_directory() as tmp_dir:\n yaml_script = get_template_script(tmp_dir)\n del yaml_script['experiments']\n exp_builder = ExperimentBuilder(yaml_script)\n output_dir = os.path.dirname(\n exp_builder._db.get_system('hydration-system')[0].position_path)\n\n # Test that output file exists and that it has correct components\n expected_resnames = {'solvent1': set(['TOL', 'WAT']), 'solvent2': set(['TOL'])}\n for phase in expected_resnames:\n found_resnames = set()\n pdb_path = os.path.join(output_dir, phase + '.pdb')\n prmtop_path = os.path.join(output_dir, phase + '.prmtop')\n inpcrd_path = os.path.join(output_dir, phase + '.inpcrd')\n\n with open(pdb_path, 'r') as f:\n for line in f:\n if len(line) > 10 and line[:5] != 'CRYST':\n found_resnames.add(line[17:20])\n\n assert os.path.exists(prmtop_path)\n assert os.path.exists(inpcrd_path)\n assert os.path.getsize(prmtop_path) > 0\n assert os.path.getsize(inpcrd_path) > 0\n assert found_resnames == expected_resnames[phase]","def testPipeFound(self):\n safeFoundHelper(self)\n self.assertCurrentState(safe.Seeking)","def test_pump_bypass_on_reverse_flow(use_numba):\n net = pandapipes.create_empty_network(\"net\", add_stdtypes=True)\n\n j1 = pandapipes.create_junction(net, pn_bar=5, tfluid_k=283.15)\n j2 = pandapipes.create_junction(net, pn_bar=5, tfluid_k=283.15)\n j3 = pandapipes.create_junction(net, pn_bar=5, tfluid_k=283.15)\n j4 = pandapipes.create_junction(net, pn_bar=5, tfluid_k=283.15)\n\n pandapipes.create_pipe(net, j1, j2, std_type='125_PE_80_SDR_11', k_mm=1., length_km=10)\n pandapipes.create_pipe(net, j3, j4, std_type='125_PE_80_SDR_11', k_mm=1., length_km=12)\n pandapipes.create_ext_grid(net, j1, 5, 283.15, type=\"p\")\n pandapipes.create_pump(net, j2, j3, std_type='P1')\n pandapipes.create_source(net, j4, 0.02333)\n\n pandapipes.create_fluid_from_lib(net, \"hgas\", overwrite=True)\n\n pandapipes.pipeflow(net, stop_condition=\"tol\", iter=3, friction_model=\"nikuradse\",\n mode=\"hydraulics\", transient=False, nonlinear_method=\"automatic\",\n tol_p=1e-4, tol_v=1e-4, use_numba=use_numba)\n\n assert net.res_pump.deltap_bar.isin([0]).all()\n assert np.isclose(net.res_junction.loc[1, \"p_bar\"], net.res_junction.loc[2, \"p_bar\"])","def test_halts_if_halt_on_next(self, get_pipe_manager, raise_error):\n pm = get_pipe_manager(name=\"TestPM\")\n pm.halt_on_next = True\n if raise_error:\n with pytest.raises(PipelineHalt):\n pm.timestamp(\"testing\")\n else:\n pm.timestamp(\"testing\", raise_error=False)\n assert pm.halted","def check_residue(self, chain_id, resid, resname):\n if resname in PTM_lookup.keys():\n return\n else:\n try:\n ref_resname = PTM_reverse_lookup[resname]\n except KeyError:\n # print \"skipping unrecognized residue\", resname\n return\n ptm_dict = PTM_lookup[ref_resname][resname]\n return (chain_id, resid, ref_resname, ptm_dict[\"goto_atom\"], ptm_dict[\"name\"])","def check_pipe_setup(pipe=None, sequence=False, j=False):\n\n # The data pipe.\n if pipe == None:\n pipe = pipes.cdp_name()\n\n # Get the data pipe.\n dp = pipes.get_pipe(pipe)\n\n # Test if the current data pipe exists.\n check_pipe(pipe)\n\n # Test if sequence data exists.\n if sequence and not exists_mol_res_spin_data(pipe):\n raise RelaxNoSequenceError(pipe)\n\n # Test if J coupling data exists.\n if j:\n # Search for interatomic data.\n data = False\n for interatom in interatomic_loop():\n if hasattr(interatom, 'j_coupling'):\n data = True\n break\n\n # No data.\n if not data:\n raise RelaxNoJError()","def setUp(self):\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Name the first molecule.\n cdp.mol[0].name = 'Ap4Aase'\n\n # Add a second molecule to the system.\n cdp.mol.add_item(mol_name='RNA')\n\n # Add two more residues to the first molecule (and set the residue number of the first).\n cdp.mol[0].res[0].num = 1\n cdp.mol[0].res.add_item(res_num=2, res_name='Glu')\n cdp.mol[0].res.add_item(res_num=4, res_name='Pro')\n\n # Add some spin info to this molecule.\n cdp.mol[0].res[0].spin[0].name = 'NH'\n cdp.mol[0].res[0].spin[0].num = 60\n cdp.mol[0].res[1].spin[0].name = 'NH'\n cdp.mol[0].res[1].spin[0].num = 63\n\n # Add one more residue to the second molecule (and set the residue number of the first).\n cdp.mol[1].res[0].num = -5\n cdp.mol[1].res.add_item(res_num=-4)\n\n # Add a second set of spins to the second molecule (naming the first set first).\n cdp.mol[1].res[0].spin[0].name = 'C8'\n cdp.mol[1].res[1].spin[0].name = 'C8'\n cdp.mol[1].res[0].spin.add_item(spin_name='N5')\n cdp.mol[1].res[1].spin.add_item(spin_name='N5')\n cdp.mol[1].res[1].spin.add_item(spin_name='2H', spin_num=132)\n\n # Deselect a number of spins.\n cdp.mol[0].res[0].spin[0].select = 0\n cdp.mol[0].res[2].spin[0].select = 0\n cdp.mol[1].res[0].spin[0].select = 0\n cdp.mol[1].res[1].spin[1].select = 0\n\n # Update the metadata.\n mol_res_spin.metadata_update()","def _loop_raw(raw):\n raise NotImplemented","def test_run_loop_exc(self):\n with self.assertRaises(ExecutionException):\n pyint = Interpreter(limit=1)\n pyint.run(code=BF_CODE_LOOP_TWICE)","def test_stop_resume(self):\n self.create_sample_data_set_dir(\"node59p1_step1.dat\", TELEM_DIR, \"node59p1.dat\",\n copy_metadata=False)\n driver_config = self._driver_config()['startup_config']\n sio_mule_config = driver_config['harvester'][DataSourceKey.PHSEN_ABCDEF_SIO_MULE]\n fullfile = os.path.join(sio_mule_config['directory'], sio_mule_config['pattern'])\n mod_time = os.path.getmtime(fullfile)\n\n # Create and store the new driver state\n self.memento = {DataSourceKey.PHSEN_ABCDEF_SIO_MULE: {\n \"node59p1.dat\": {\n DriverStateKey.FILE_SIZE: 911,\n DriverStateKey.FILE_CHECKSUM: '8b7cf73895eded0198b3f3621f962abc',\n DriverStateKey.FILE_MOD_DATE: mod_time,\n DriverStateKey.PARSER_STATE: {\n StateKey.IN_PROCESS_DATA: [],\n StateKey.UNPROCESSED_DATA:[[0, 172]],\n StateKey.FILE_SIZE: 911\n }\n }\n }}\n\n self.driver = self._get_driver_object(memento=self.memento)\n\n # create some data to parse\n self.clear_async_data()\n self.create_sample_data_set_dir(\"node59p1_step2.dat\", TELEM_DIR, \"node59p1.dat\",\n copy_metadata=False)\n\n self.driver.start_sampling()\n\n # verify data is produced\n self.assert_data(PhsenParserDataParticle, 'test_data_2.txt.result.yml',\n count=2, timeout=10)","def test_ipam_rirs_read(self):\n pass","def residual(pars, data= None):\n\n\t\t\tresid = np.array([])\n\n\n\t\t\t# make residual per data set\n\n\t\t\tfor N in range(n_annulus):\n\n\t\t\t\tmdl_ev = 0\n\t\t\t\tr_space_k = rings_pos[N+1] - rings_pos[N] \n\t\t\t\tmask = np.where( (r_n >= rings_pos[N] ) & (r_n < rings_pos[N+1]) )\n\t\t\t\tx,y = XY_mesh[0][mask], XY_mesh[1][mask] \n\t\t\t\tXY = (x,y)\n\n\n\n\n\t\t\t\tfor kk in range(2):\n\t\t\t\t\tVxy,Vsys = vmodel_dataset(pars, N+kk, XY, r_0 = rings_pos[N], r_space = r_space_k )\n\n\t\t\t\t\tmdl_ev = mdl_ev + Vxy[kk]\n\n\n\t\t\t\t\tif N == 0 and kk == 0:\n\t\t\t\t\t\t\n\t\t\t\t\t\tmask1 = np.where( (r_n < rings_pos[0] ) )\n\t\t\t\t\t\tx1,y1 = XY_mesh[0][mask1], XY_mesh[1][mask1] \n\t\t\t\t\t\tXY1 = (x1,y1)\n\n\n\t\t\t\t\t\t#\n\t\t\t\t\t\t#\n\t\t\t\t\t\t# inner interpolation\n\t\t\t\t\t\t#\n\t\t\t\t\t\t#\n\t\t\t\t\t\n\t\t\t\t\t\t#(a) velocity rise linearly from zero\n\n\t\t\t\t\t\tr_space_0 = rings_pos[0]\n\t\t\t\t\t\tVxy,Vsys = vmodel_dataset(pars, 0, XY1, r_0 = 0, r_space = r_space_0)\n\t\t\t\t\t\n\t\t\t\t\t\tinterp_model[mask1] = Vxy[1] + Vsys\n\n\t\t\t\tinterp_model[mask] = mdl_ev + Vsys\n\n\n\n\n\t\t\t\n\t\t\tsigma = np.sqrt(e_vel_map**2 + e_ISM**2)\n\t\t\t#interp_model[interp_model == 0] = np.nan\n\n\n\t\t\tconvolved = 0\n\n\t\t\tif convolved == True:\n\n\t\t\t\tmy_beam = Beam(2.5*u.arcsec, 2.5*u.arcsec, 0*u.deg)\n\t\t\t\tpix_scale = pixel_scale * u.arcsec\n\t\t\t\tgauss_kern = my_beam.as_kernel(pix_scale, x_size = nx, y_size = ny)\n\n\n\t\t\t\textend = np.zeros((3*ny,3*nx))\n\t\t\t\textend[ny:2*ny,nx:2*nx] = interp_model\n\t\t\t\tconvolve_extend = convolve_fft(extend, gauss_kern, mask = extend == 0 )\n\t\t\t\tinterp_model_conv = convolve_extend[ny:2*ny,nx:2*nx]\n\t\t\t\tinterp_model_conv[interp_model == 0] = 0\n\n\n\n\n\t\t\telse:\n\t\t\t\tinterp_model_conv = interp_model\n\n\t\t\tinterp_model_conv[interp_model_conv == 0] = np.nan\n\t\t\tres = vel_map - interp_model_conv\n\t\t\tResid = res/sigma\n\n\n\t\t\treturn Resid.flatten()","def test_08(self, test):\r\n globalConfig.test = test\r\n\r\n forbiddenRoutes = []\r\n outputList = getOutputList()\r\n inputList = getInputList()\r\n if len(inputList) == 0 or len(outputList) == 0:\r\n return test.UNCLEAR(\"Not tested. No resources found.\")\r\n\r\n for outputInstance in outputList:\r\n sourceID = outputInstance.getSourceID()\r\n for inputInstance in inputList:\r\n inputParent = inputInstance.getParent()\r\n if inputParent['type'] == \"source\" and sourceID == inputParent['id']:\r\n route = {\r\n \"input\": inputInstance,\r\n \"output\": outputInstance\r\n }\r\n forbiddenRoutes.append(route)\r\n\r\n for route in forbiddenRoutes:\r\n outputCaps = route['output'].getCaps()\r\n msg = (\"It is possible to create a loop using re-entrant matrices \"\r\n \"between Input {} and Output {}\".format(route['input'].id, route['output'].id))\r\n try:\r\n routableInputs = outputCaps['routable_inputs']\r\n except KeyError:\r\n return test.FAIL(\"Could not find 'routable_inputs' in /caps \"\r\n \"for Output {}\".format(route['output'].id))\r\n if routableInputs is None or route['input'].id in routableInputs:\r\n return test.FAIL(msg)\r\n return test.PASS()","def residual_processor(self):\n def get_file(field, solver):\n \"\"\"Helper method to get the file handle for a field.\n\n On first invocation, it creates the file with headers. On\n subsequent invocations it just returns the relevant file handle.\n \"\"\"\n if not field in self.res_files:\n fh = open(join(self.logs_dir, field+\".dat\"), 'w')\n fh.write(\"# Field: %s; Solver: %s\\n\"%(field, solver))\n fh.write(\"Time SubIteration InitialResidual FinalResidual NoIterations\\n\")\n self.res_files[field] = fh\n return self.res_files[field]\n # end get_file\n\n try:\n while True:\n rexp = (yield)\n solver = rexp.group(1) # e.g., PCB, GAMG, etc.\n field = rexp.group(2) # Ux, Uy, p, etc.\n\n icorr = self.subiter_map.get(field, 0) + 1\n self.subiter_map[field] = icorr\n fh = get_file(field, solver)\n fh.write(\n self.time_str + \"\\t%d\\t\"%icorr +\n \"\\t\".join([rexp.group(i) for i in range(3, 6)]) + \"\\n\")\n except GeneratorExit:\n for fh in self.res_files.values():\n if not fh.closed:\n fh.close()","def test_perceive_residues_natoms_mainchain_charged_glutamic_acid(\n self, strict_chirality\n ):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/MainChain_GLH.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def fatal_error_processor(self):\n while True:\n _ = (yield)\n self.failed = True\n self.converged = False\n self.solve_completed = False","def test_wrong_turn_results_in_inf_loop():\n\t\n\t# chceme vystup v citelny podobe pro PIPE\n\tcp = subprocess.run([sys.executable, 'game.py'],\n\t\t\t\t\t\t# misto encoding, kvuli Python3.5, pouziju univ_new\n\t\t\t\t\t\tuniversal_newlines=True,\n\t\t\t\t\t\tstdout=subprocess.PIPE,\n\t\t\t\t\t\tinput='doggie\\nrock\\n',\n\t\t\t\t\t\tcheck=True)\n\n\tassert cp.stdout.count('Choice: rock, scissors, paper: ') == 2 # 2x True value","def residual(pars, data= None):\n\n\t\t\tresid = np.array([])\n\n\n\t\t\t# make residual per data set\n\n\t\t\tfor N in range(n_annulus):\n\n\t\t\t\tmdl_ev = 0\n\t\t\t\tr_space_k = rings_pos[N+1] - rings_pos[N] \n\t\t\t\tmask = np.where( (r_n >= rings_pos[N] ) & (r_n < rings_pos[N+1]) )\n\t\t\t\tx,y = XY_mesh[0][mask], XY_mesh[1][mask] \n\t\t\t\tXY = (x,y)\n\n\n\n\n\t\t\t\tfor kk in range(2):\n\t\t\t\t\tVxy,Vsys = vmodel_dataset(pars, N+kk, XY, r_0 = rings_pos[N], r_space = r_space_k)\n\n\t\t\t\t\tmdl_ev = mdl_ev + Vxy[kk]\n\n\n\t\t\t\t\tif N == 0 and kk == 0:\n\t\t\t\t\t\t\n\t\t\t\t\t\tmask1 = np.where( (r_n < rings_pos[0] ) )\n\t\t\t\t\t\tx1,y1 = XY_mesh[0][mask1], XY_mesh[1][mask1] \n\t\t\t\t\t\tXY1 = (x1,y1)\n\n\n\t\t\t\t\t\t#\n\t\t\t\t\t\t#\n\t\t\t\t\t\t# inner interpolation\n\t\t\t\t\t\t#\n\t\t\t\t\t\t#\n\t\t\t\t\t\n\t\t\t\t\t\t#(a) velocity rise linearly from zero\n\n\t\t\t\t\t\tr_space_0 = rings_pos[0]\n\t\t\t\t\t\tVxy,Vsys = vmodel_dataset(pars, 0, XY1, r_0 = 0, r_space = r_space_0)\n\t\t\t\t\t\n\t\t\t\t\t\tinterp_model[mask1] = Vxy[1] + Vsys\n\n\t\t\t\tinterp_model[mask] = mdl_ev + Vsys\n\n\n\n\n\t\t\t\n\t\t\tsigma = np.sqrt(e_vel_map**2 + e_ISM**2)\n\n\n\n\t\t\tconvolved = 0\n\n\t\t\tif convolved == True:\n\n\t\t\t\tmy_beam = Beam(2.5*u.arcsec, 2.5*u.arcsec, 0*u.deg)\n\t\t\t\tpix_scale = pixel_scale * u.arcsec\n\t\t\t\tgauss_kern = my_beam.as_kernel(pix_scale, x_size = nx, y_size = ny)\n\n\n\t\t\t\textend = np.zeros((3*ny,3*nx))\n\t\t\t\textend[ny:2*ny,nx:2*nx] = interp_model\n\t\t\t\tconvolve_extend = convolve_fft(extend, gauss_kern, mask = extend == 0 )\n\t\t\t\tinterp_model_conv = convolve_extend[ny:2*ny,nx:2*nx]\n\t\t\t\tinterp_model_conv[interp_model == 0] = 0\n\n\n\t\t\telse:\n\t\t\t\tinterp_model_conv = interp_model\n\n\n\t\t\tinterp_model_conv[interp_model_conv == 0] = np.nan\n\t\t\tres = vel_map - interp_model_conv\n\t\t\tResid = res/sigma\n\n\n\t\t\treturn Resid.flatten()","def residual(pars, data= None):\n\n\t\t\tresid = np.array([])\n\n\n\t\t\t# make residual per data set\n\n\t\t\tfor N in range(n_annulus):\n\n\t\t\t\tmdl_ev = 0\n\t\t\t\tr_space_k = rings_pos[N+1] - rings_pos[N] \n\t\t\t\tmask = np.where( (r_n >= rings_pos[N] ) & (r_n < rings_pos[N+1]) )\n\t\t\t\tx,y = XY_mesh[0][mask], XY_mesh[1][mask] \n\t\t\t\tXY = (x,y)\n\n\n\n\n\t\t\t\tfor kk in range(2):\n\t\t\t\t\tVxy,Vsys = vmodel_dataset(pars, N+kk, XY, r_0 = rings_pos[N], r_space = r_space_k)\n\n\t\t\t\t\tmdl_ev = mdl_ev + Vxy[kk]\n\n\n\t\t\t\t\tif N == 0 and kk == 0:\n\t\t\t\t\t\t\n\t\t\t\t\t\tmask1 = np.where( (r_n < rings_pos[0] ) )\n\t\t\t\t\t\tx1,y1 = XY_mesh[0][mask1], XY_mesh[1][mask1] \n\t\t\t\t\t\tXY1 = (x1,y1)\n\n\n\t\t\t\t\t\t#\n\t\t\t\t\t\t#\n\t\t\t\t\t\t# inner interpolation\n\t\t\t\t\t\t#\n\t\t\t\t\t\t#\n\t\t\t\t\t\n\t\t\t\t\t\t#(a) velocity rise linearly from zero\n\n\t\t\t\t\t\tr_space_0 = rings_pos[0]\n\t\t\t\t\t\tVxy,Vsys = vmodel_dataset(pars, 0, XY1, r_0 = 0, r_space = r_space_0)\n\t\t\t\t\t\n\t\t\t\t\t\tinterp_model[mask1] = Vxy[1] + Vsys\n\n\t\t\t\tinterp_model[mask] = mdl_ev + Vsys\n\n\n\n\n\t\t\t\n\t\t\tsigma = np.sqrt(e_vel_map**2 + e_ISM**2)\n\n\n\n\t\t\tconvolved = 0\n\n\t\t\tif convolved == True:\n\n\t\t\t\tmy_beam = Beam(2.5*u.arcsec, 2.5*u.arcsec, 0*u.deg)\n\t\t\t\tpix_scale = pixel_scale * u.arcsec\n\t\t\t\tgauss_kern = my_beam.as_kernel(pix_scale, x_size = nx, y_size = ny)\n\n\n\t\t\t\textend = np.zeros((3*ny,3*nx))\n\t\t\t\textend[ny:2*ny,nx:2*nx] = interp_model\n\t\t\t\tconvolve_extend = convolve_fft(extend, gauss_kern, mask = extend == 0 )\n\t\t\t\tinterp_model_conv = convolve_extend[ny:2*ny,nx:2*nx]\n\t\t\t\tinterp_model_conv[interp_model == 0] = 0\n\n\n\t\t\telse:\n\t\t\t\tinterp_model_conv = interp_model\n\n\n\t\t\tinterp_model_conv[interp_model_conv == 0] = np.nan\n\t\t\tres = vel_map - interp_model_conv\n\t\t\tResid = res/sigma\n\n\t\t\treturn Resid.flatten()","def residual(pars, data= None):\n\n\t\t\tresid = np.array([])\n\n\n\t\t\t# make residual per data set\n\n\t\t\tfor N in range(n_annulus):\n\n\t\t\t\tmdl_ev = 0\n\t\t\t\tr_space_k = rings_pos[N+1] - rings_pos[N] \n\t\t\t\tmask = np.where( (r_n >= rings_pos[N] ) & (r_n < rings_pos[N+1]) )\n\t\t\t\tx,y = XY_mesh[0][mask], XY_mesh[1][mask] \n\t\t\t\tXY = (x,y)\n\n\n\n\n\t\t\t\tfor kk in range(2):\n\t\t\t\t\tVxy,Vsys = vmodel_dataset(pars, N+kk, XY, r_0 = rings_pos[N], r_space = r_space_k)\n\n\t\t\t\t\tmdl_ev = mdl_ev + Vxy[kk]\n\n\n\t\t\t\t\tif N == 0 and kk == 0:\n\t\t\t\t\t\t\n\t\t\t\t\t\tmask1 = np.where( (r_n < rings_pos[0] ) )\n\t\t\t\t\t\tx1,y1 = XY_mesh[0][mask1], XY_mesh[1][mask1] \n\t\t\t\t\t\tXY1 = (x1,y1)\n\n\n\t\t\t\t\t\t#\n\t\t\t\t\t\t#\n\t\t\t\t\t\t# inner interpolation\n\t\t\t\t\t\t#\n\t\t\t\t\t\t#\n\t\t\t\t\t\n\t\t\t\t\t\t#(a) velocity rise linearly from zero\n\n\t\t\t\t\t\tr_space_0 = rings_pos[0]\n\t\t\t\t\t\tVxy,Vsys = vmodel_dataset(pars, 0, XY1, r_0 = 0, r_space = r_space_0)\n\t\t\t\t\t\n\t\t\t\t\t\tinterp_model[mask1] = Vxy[1] + Vsys\n\n\t\t\t\tinterp_model[mask] = mdl_ev + Vsys\n\n\n\n\n\t\t\t\n\t\t\tsigma = np.sqrt(e_vel_map**2 + e_ISM**2)\n\n\n\n\t\t\tconvolved = 0\n\n\t\t\tif convolved == True:\n\n\t\t\t\tmy_beam = Beam(2.5*u.arcsec, 2.5*u.arcsec, 0*u.deg)\n\t\t\t\tpix_scale = pixel_scale * u.arcsec\n\t\t\t\tgauss_kern = my_beam.as_kernel(pix_scale, x_size = nx, y_size = ny)\n\n\n\t\t\t\textend = np.zeros((3*ny,3*nx))\n\t\t\t\textend[ny:2*ny,nx:2*nx] = interp_model\n\t\t\t\tconvolve_extend = convolve_fft(extend, gauss_kern, mask = extend == 0 )\n\t\t\t\tinterp_model_conv = convolve_extend[ny:2*ny,nx:2*nx]\n\t\t\t\tinterp_model_conv[interp_model == 0] = 0\n\n\n\t\t\telse:\n\t\t\t\tinterp_model_conv = interp_model\n\n\t\t\tinterp_model[interp_model == 0] = np.nan\n\t\t\tres = vel_map - interp_model_conv\n\t\t\tResid = res/sigma\n\n\n\n\t\t\treturn Resid.flatten()","def test_invoke_passthrough_items_empty_pipe():\n\n testapp = holocron.Application()\n testapp.add_pipe(\"test\", [])\n\n stream = testapp.invoke(\n \"test\",\n [\n holocron.Item(name=\"yoda\", rank=\"master\"),\n holocron.Item(name=\"skywalker\"),\n ],\n )\n\n assert next(stream) == holocron.Item(name=\"yoda\", rank=\"master\")\n assert next(stream) == holocron.Item(name=\"skywalker\")\n\n with pytest.raises(StopIteration):\n next(testapp.invoke(\"test\"))","def compile_loop(self, use_context=True):\n missings = set()\n errors = {}\n root_vars = self.external_vars.copy()\n\n # Local vars computation.\n for name, formula in self.local_vars.iteritems():\n if name not in self._evaluated_vars:\n try:\n val = eval_entry(formula, root_vars, missings)\n self._evaluated_vars[name] = val\n except Exception as e:\n errors['root_' + name] = repr(e)\n\n root_vars.update(self._evaluated_vars)\n\n if self.time_constrained:\n try:\n duration = eval_entry(self.sequence_duration, root_vars,\n missings)\n root_vars['sequence_end'] = duration\n except Exception as e:\n errors['root_seq_duration'] = repr(e)\n\n res, pulses = self._compile_items(root_vars, root_vars,\n missings, errors)\n\n if not res:\n return False, (missings, errors), None\n\n if self.time_constrained:\n err = [p for p in pulses if p.stop > duration]\n\n if err:\n mess = cleandoc('''The stop time of the following pulses {}\n is larger than the duration of the sequence.''')\n ind = [p.index for p in err]\n errors['Root-stop'] = mess.format(ind)\n return False, (missings, errors), None\n\n if not use_context:\n return True, pulses, None\n\n else:\n kwargs = {}\n if self.time_constrained:\n kwargs['sequence_duration'] = duration\n return self.context.compile_loop(pulses, **kwargs)","def test_rsp_invalid(self):\n\n def handle(event):\n ds = Dataset()\n ds.PatientName = \"Test^test\"\n return 0x0000, ds\n\n self.ae = ae = AE()\n ae.acse_timeout = 5\n ae.dimse_timeout = 0.4\n ae.network_timeout = 5\n ae.add_supported_context(ModalityPerformedProcedureStep)\n scp = ae.start_server(\n (\"localhost\", 11112), block=False, evt_handlers=[(evt.EVT_N_SET, handle)]\n )\n\n ae.add_requested_context(ModalityPerformedProcedureStep)\n assoc = ae.associate(\"localhost\", 11112)\n assert assoc.is_established\n\n class DummyResponse:\n is_valid_response = False\n\n class DummyDIMSE:\n msg_queue = queue.Queue()\n gotten = False\n\n def send_msg(*args, **kwargs):\n return\n\n def get_msg(self, *args, **kwargs):\n if not self.gotten:\n self.gotten = True\n return None, DummyResponse()\n return None, None\n\n assoc._reactor_checkpoint.clear()\n while not assoc._is_paused:\n time.sleep(0.01)\n assoc.dimse = DummyDIMSE()\n mod_list = Dataset()\n mod_list.PatientName = \"Test^test\"\n status, ds = assoc.send_n_set(\n mod_list, ModalityPerformedProcedureStep, \"1.2.840.10008.5.1.1.40.1\"\n )\n\n assert status == Dataset()\n assert ds is None\n assert assoc.is_aborted\n\n scp.shutdown()","def next():\n iraw = 0\n run = 0\n seqno = 0\n with db_connection() as conn:\n with conn.cursor() as curs:\n try:\n curs.execute(\"\"\"SELECT rawdata.id,rawdata.run,rawdata.seqno,\n slices.block1,slices.block2,\n jobs.cluster,jobs.process\n FROM rawdata\n LEFT JOIN bindings\n ON bindings.iraw = rawdata.id\n INNER JOIN slices\n ON slices.iraw = rawdata.id\n LEFT JOIN jobs\n ON slices.ijob = jobs.id\n AND jobs.exitcode = 0\n WHERE bindings.id IS NULL\n ORDER BY rawdata.id,slices.block1\n LIMIT 2000;\n \"\"\")\n slices_missing = 1\n for row in curs.fetchall():\n i = int(row[0])\n if i != iraw:\n if slices_missing == 0:\n break\n else:\n run = int(row[1])\n seqno = int(row[2])\n slices_missing = 0\n slices = []\n iraw = i\n block1 = int(row[3])\n block2 = int(row[4])\n if row[5] is not None and row[6] is not None:\n cluster = int(row[5])\n process = int(row[6])\n slices.append((block1,block2,cluster,process))\n else:\n print(\"slices missing on\", row[5], row[6])\n slices_missing += 1\n if slices_missing:\n return 0\n else:\n curs.execute(\"SELECT TIMEZONE('GMT', NOW());\")\n now = curs.fetchone()[0]\n curs.execute(\"\"\"INSERT INTO bindings\n (iraw,starttime)\n VALUES (%s,%s)\n RETURNING id;\n \"\"\", (iraw, now))\n row = curs.fetchone()\n if row:\n ibind = int(row[0])\n else:\n return 0\n except:\n iraw = 0\n if iraw == 0:\n time.sleep(random.randint(1,30))\n return -9 # collision\n\n workdir = str(iraw)\n os.mkdir(workdir)\n os.chdir(workdir)\n badslices = []\n for sl in slices:\n sdir = str(sl[0]) + \",\" + str(sl[1])\n os.mkdir(sdir)\n tarfile = \"job_{0}_{1}.tar.gz\".format(sl[2], sl[3])\n tarpath = input_area + \"/\" + tarfile\n try:\n subprocess.check_output([\"gfal-copy\", src_url + tarpath,\n \"file://\" + os.getcwd() + \"/\" + tarfile])\n except:\n sys.stderr.write(\"Error -999 on rawdata id {0}\".format(iraw) +\n \" - job output \" + tarfile + \" is missing!\\n\")\n sys.stderr.flush()\n badslices.append(sdir)\n continue\n try:\n subprocess.check_output([\"tar\", \"zxf\", tarfile, \"-C\", sdir])\n except:\n sys.stderr.write(\"Error -999 on rawdata id {0}\".format(iraw) +\n \" - job output \" + tarfile + \" is not readable!\\n\")\n sys.stderr.flush()\n badslices.append(sdir)\n finally:\n os.remove(tarfile)\n if len(badslices) > 0:\n with db_connection() as conn:\n with conn.cursor() as curs:\n curs.execute(\"SELECT TIMEZONE('GMT', NOW());\")\n now = curs.fetchone()[0]\n curs.execute(\"\"\"UPDATE bindings\n SET endtime=%s, \n exitcode=%s,\n details=%s\n WHERE id = %s;\n \"\"\", (now, -999, \":\".join(badslices), ibind))\n os.chdir(\"..\")\n shutil.rmtree(workdir)\n return 1\n\n badslices += merge_evio_skims(run, seqno, slices)\n badslices += merge_hddm_output(run, seqno, slices)\n badslices += merge_job_info(run, seqno, slices)\n badslices += merge_root_histos(run, seqno, slices)\n exitcode = -len(badslices)\n with db_connection() as comm:\n with conn.cursor() as curs:\n curs.execute(\"SELECT TIMEZONE('GMT', NOW());\")\n now = curs.fetchone()[0]\n curs.execute(\"\"\"UPDATE bindings\n SET endtime=%s,\n exitcode=%s,\n details=%s\n WHERE id = %s;\n \"\"\", (now, exitcode, \":\".join(badslices), ibind))\n os.chdir(\"..\")\n shutil.rmtree(workdir)\n return 1","def test_boolean_complex_selection(self):\n\n # The residue selection loop.\n sel = list(mol_res_spin.residue_loop(\"#Ap4Aase:4 & :Pro | #RNA\"))\n\n # Residue names and numbers.\n names = ['Pro', None, None]\n numbers = [4, -5, -4]\n\n # The residues.\n self.assertEqual(len(sel), 3)\n for i in range(3):\n self.assertEqual(sel[i].name, names[i])\n self.assertEqual(sel[i].num, numbers[i])","def test_policer_handoff_input(self):\n self.policer_handoff_test(Dir.RX)","def test_reset(self):\n ran = []\n def foo():\n ran.append(None)\n\n c = task.Clock()\n lc = TestableLoopingCall(c, foo)\n lc.start(2, now=False)\n c.advance(1)\n lc.reset()\n c.advance(1)\n self.assertEqual(ran, [])\n c.advance(1)\n self.assertEqual(ran, [None])","def test_return_molecule(self):\n\n # Ask for a few molecules.\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\n\n # Test the data of molecule 1.\n self.assertEqual(mol1.name, 'Ap4Aase')\n\n # Test the data of molecule 2.\n self.assertEqual(mol2.name, 'RNA')","def test_single_molecule(self, single_mol_system, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def algorithm_loop(self):","def _readloop(self):\r\n\r\n while self._ll_alive:\r\n with self._rx_lock:\r\n data = self._Random(1)\r\n if len(data) != 0: # check for timeout\r\n self._uart_rx_queue.put(data)","def check_for_residue_existance(self):\n if not self.pose.total_residue():\n print \"No pose Loaded.\"\n return False\n\n if not self.current_chain.get() or not self.current_residue.get():\n print \"Chain or residue not set\"\n return False\n\n current_region = self.current_residue.get().split(\":\")\n if len(current_region)>1:\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\n\n\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\n print \"Region not found in pose\"\n return False\n else:\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\n\n print \"Residue not found in pose\"\n return False\n\n #If everythig is good then:\n return True","def test_perceive_residues_natoms_mainchain_glutamic_acid(self, strict_chirality):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/MainChain_GLU.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def test_chunk_pauli(self, method, device):\n opts_no_chunk = {\"fusion_enable\": False}\n opts_chunk = copy.copy(opts_no_chunk)\n opts_chunk[\"blocking_enable\"] = True\n opts_chunk[\"blocking_qubits\"] = 3\n\n backend = self.backend(method=method, device=device, **opts_chunk)\n backend_no_chunk = self.backend(method=method, device=device, **opts_no_chunk)\n\n shots = 100\n\n qr = QuantumRegister(5)\n cr = ClassicalRegister(5)\n regs = (qr, cr)\n circuit = QuantumCircuit(*regs)\n circuit.h(qr[0])\n circuit.h(qr[1])\n circuit.h(qr[2])\n circuit.h(qr[3])\n circuit.h(qr[4])\n circuit.pauli(\"YXZYX\", qr)\n circuit.measure_all()\n\n result = backend.run(circuit, shots=shots, memory=True).result()\n counts = result.get_counts(circuit)\n result_no_chunk = backend_no_chunk.run(circuit, shots=shots, memory=True).result()\n counts_no_chunk = result_no_chunk.get_counts(circuit)\n\n self.assertEqual(counts_no_chunk, counts)","def wait_for_data(receiver):\n\n while not receiver.available(pipes[1]):\n time.sleep(0.01)","def test_ls_empty():\n with pipeline.fixture(assets=[], versions=0):\n assert_raises(StopIteration, next, pipeline.ls())","def test_pure_prisoners_dilemma(_):\n game = gamegen.sym_2p2s_game(2, 0, 3, 1) # prisoners dilemma\n eqm = [0, 2]\n\n assert (\n regret.pure_strategy_regret(game, eqm) == 0\n ), \"Known equilibrium was not zero regret\"","def revProcess(env):\n api.injectInteger(propdb.PROP_IGNITION_STATE, propdb.IGNITION_STATE_ON)\n while True:\n \n if vehicle_data.rpm < 3000:\n vehicle_data.rpm += 50\n elif vehicle_data.gear < 5:\n vehicle_data.rpm = vehicle_data.speed * 100.0 / (vehicle_data.gear + 1)\n vehicle_data.gear += 1\n \n vehicle_data.speed = vehicle_data.rpm * vehicle_data.gear / 100.0\n\n yield env.timeout(0.025)","def test_non_pauli_error(self):\n circuit = hadamard_circuit(3)\n bits, recipes = circuit()\n shadow = ClassicalShadow(bits, recipes)\n\n H = qml.Hadamard(0) @ qml.Hadamard(2)\n\n msg = \"Observable must be a linear combination of Pauli observables\"\n with pytest.raises(ValueError, match=msg):\n shadow.expval(H, k=10)","def _while_loop(pd, nmax, max_loop, ncore, outfile):\n \n # make sure the random seed is different for every processor\n random_number_seeds = [3456789, 7654321, 2435467, 8273645,\n 1085712, 4154712, 1248291, 8415917,\n 2345161, 5710916, 5718601, 7516234,\n 9235161, 4917519, 1111245, 8167834] \n \n # get the processor ID (1 - Ncore) and convert to single integer\n current = multiprocessing.current_process()\n pid = current._identity\n pid = pid[0]\n \n #\n # choose a different seed for each processor from the list so each processor has\n # a different randum number seed. Then, fiddle with each seed a little so \n # the seeds aren't the same every time the code is run\n seed = np.int(random_number_seeds[pid] * (np.random.rand()*(10.0 - 0.01) + 0.01))\n \n np.random.seed(seed)\n \n #print 'id and seed', pid, seed\n \n n_particles = 0\n loop_counter = 0\n fmin_scale = 1.0E-100 # -16 -> -32 -> -100\n F_max = np.max(pd.DF.f) #; F_min = np.min(pd.DF.f);\n F_min = np.min(pd.DF.f) * fmin_scale\n # F_max = np.max(pd.DF.f[:-1])#; F_max = 1.0E-88\n #print F_min, F_max\n if pd.optimize:\n relative_potential = pd._interpolate_relative_potential\n else:\n relative_potential = pd.DF.relative_potential\n \n \n pos = np.zeros((nmax, 3))\n vel = np.zeros((nmax, 3)) \n \n while (( n_particles < nmax) and (loop_counter < max_loop)):\n \n r = pd._choose_position()\n Psi = relative_potential(r) \n \n v = pd._choose_velocity(r, Psi)\n \n E = Psi - 0.5 * v * v\n \n f_E = pd.DF.interpolate_f(E)\n \n logF = ( np.random.rand()*(np.log10(F_max) - np.log10(F_min)) + np.log10(F_min) )\n \n # if choosing random F in log F, might be good to do the comparison in logspace as well\n #.... i.e log(F) <= log(f_E) \n #\n # 0 FOR F_E MEANS THAT E < E_min of the potential. THis happens when Psi - KE is smaller\n # than the value of the potential at large_r... should this be considered unbound \n # even though it isn't zero? Is this effectively zero? This has been adjusted in the velocity\n # picking routine but needs verification to make sure it works.... but regardless, I doubt\n # that this is the reason why the particles are failing for NFW but working for hernquist....\n #\n if np.abs(np.log10(f_E)) == np.inf:\n keep_particle = False\n _my_print('log value error... throwing out particle')\n else:\n keep_particle = (logF <= np.log10(f_E))\n\n \n if keep_particle: \n index = n_particles \n \n # \n # need to sample in cosine theta NOT theta!!!!! WTF!!!!!\n #\n #\n \n theta = np.arccos( np.random.rand() * (2.0) - 1.0)\n \n # convert position to cartesian using random theta and phi\n phi = np.random.rand() * 2.0 * np.pi\n \n x = np.sin(theta) * np.cos(phi)\n y = np.sin(theta) * np.sin(phi)\n z = np.cos(theta)\n \n pos[index] = r * np.array([x,y,z])\n\n # repeat for velocity using new random numbersw\n theta = np.arccos( np.random.rand() * (2.0) - 1.0)\n phi = np.random.rand() * 2.0 * np.pi\n \n vx = np.sin(theta) * np.cos(phi)\n vy = np.sin(theta) * np.sin(phi)\n vz = np.cos(theta)\n \n vel[index] = v * np.array([vx,vy,vz])\n \"\"\" \n #else: # do strict cartesian ... slower.... less attractive\n # \n # axis_list = [0, 1, 2]\n # random.shuffle(axis_list)\n \n # #axis_index = np.random.randint(3)\n # first_axis = axis_list[0]\n #\n # pos[index, first_axis] = np.random.rand() * (2.0*r) - r\n #del axis_list[axis_index]\n \n #axis_index = np.random.randint(2)\n # second_axis = axis_list[1]\n \n max_r = np.sqrt(r*r - pos[index,first_axis]**2)\n \n pos[index, second_axis] = np.random.rand()*(2.0 * max_r) - max_r\n #del axis_list[axis_index]\n \n max_r = np.sqrt(r*r - pos[index,first_axis]**2 - pos[index,second_axis]**2)\n \n third_axis = axis_list[2]\n pos[index, third_axis] = np.random.rand() * (2.0 * max_r) - max_r\n \n if np.sqrt(pos[index,0]**2 + pos[index,1]**2 + pos[index,2]**2) > r:\n _my_print('R IS TOO LARGE')\n \n ###\n axis_list = [0, 1, 2]\n random.shuffle(axis_list)\n \n #axis_index = np.random.randint(3)\n first_axis = axis_list[0]\n \n vel[index, first_axis] = np.random.rand() * (2.0*v) - v\n #del axis_list[axis_index]\n \n #axis_index = np.random.randint(2)\n second_axis = axis_list[1]\n \n max_v = np.sqrt(v*v - vel[index,first_axis]**2)\n \n vel[index, second_axis] = np.random.rand()*(2.0 * max_v) - max_v\n #del axis_list[axis_index]\n \n max_v = np.sqrt(v*v - vel[index,first_axis]**2 - vel[index,second_axis]**2)\n \n third_axis = axis_list[2]\n vel[index, third_axis] = np.random.rand() * (2.0 * max_v) - max_v \n \n \n \"\"\"\n n_particles = n_particles + 1\n \n if (loop_counter % 5000) == 0:\n _my_print(\"Have %4i particles. On loop %6i\"%(n_particles, loop_counter))\n loop_counter = loop_counter + 1\n \n # now write out to a temporary file\n f = open(outfile + \"_%02i_\"%(pid) + \".temp\", 'w')\n fmt = \"%12.12E %12.12E %12.12E %12.12E %12.12E %12.12E %12.12E\\n\"\n \n \n for i in np.arange(nmax):\n f.write(fmt%(pd.M_part, pos[i,0], pos[i,1], pos[i,2], \n vel[i,0], vel[i,1], vel[i,2]))\n \n \n f.close() \n \n return pos, vel","def test_rebinpds(self):\n command = '{0} -r 2'.format(\n os.path.join(self.datadir, 'monol_testA_E3-50_pds') +\n HEN_FILE_EXTENSION)\n hen.rebin.main(command.split())\n os.path.exists(os.path.join(self.datadir,\n 'monol_testA_E3-50_pds_rebin2' +\n HEN_FILE_EXTENSION))","def test_nothing_perceived_dipeptide(self):\n from openff.toolkit._tests.create_molecules import dipeptide as create_dipeptide\n\n dipeptide = create_dipeptide()\n\n with pytest.raises(KeyError):\n assert dipeptide.atoms[0].metadata[\"residue_name\"] is None\n with pytest.raises(KeyError):\n assert \"ALA\" == dipeptide.atoms[10].metadata[\"residue_name\"]\n with pytest.raises(KeyError):\n assert 1 == dipeptide.atoms[10].metadata[\"residue_number\"]\n with pytest.raises(KeyError):\n assert \" \" == dipeptide.atoms[10].metadata[\"insertion_code\"]\n with pytest.raises(AttributeError):\n dipeptide.residues[0]","def test_74_break(self):\n\t\tinput = \"\"\"procedure main(); var x:integer;\n\t\tbegin while(true)do begin\n\t\twith x:integer; do with x:real; do begin\n\t\t\tif (x>0) then break;\n\t\t\twith x:integer; do if (x=0) then return;\n\t\tend{with} break; end{while} break; end\"\"\"\n\t\texpect = \"Break Not In Loop\"\n\t\tself.assertTrue(TestChecker.test(input,expect,474))","def read(self):\n try:\n cmd = 'SAMP:COUN 1' \n self.handle.write(cmd) #one sample per trigger\n self.handle.write('TRIG:SOUR BUS') #triggered by command\n self.handle.write('TRIG:COUN 1') #one trigger to return to wait for trg\n self.handle.write('INIT:IMM') #DVM to \"wait for trigger\" \n self.handle.write('*TRG')\n startTime = time.time()\n while True: #wait until measuring flag goes to 0\n try:\n measured = self.handle.ask(\"DATA:POIN?\")\n measured = measured.strip() #remove CR \n measured = int(measured) #convert to number\n if measured == 1: #final number of samples achieved\n break;\n except Exception:\n print('Dvm34411:read() polling failed !')\n raise\n \n if time.time() - startTime > self.timeout:\n print('Dvm34411:read() timeout !')\n return False\n \n time.sleep(1) \n reading = self.handle.ask('R? 1;') #definite-Length block format\n except Exception:\n print('Dvm34411.read() failed !')\n raise\n if reading[0] != '#':\n print('Dvm34411.read() DLB format error - # expected !')\n return False\n digits = int(reading[1])\n reading = reading[2 + digits:]\n rdg = float(reading)\n return rdg","def pipe_loop(context, _INPUT, conf, embed=None, **kwargs):\n mode = conf['mode']['value']\n assign_to = conf['assign_to']['value']\n assign_part = conf['assign_part']['value']\n emit_part = conf['emit_part']['value']\n loop_with = conf['with']['value']\n embed_conf = conf['embed']['value']['conf']\n \n #Prepare the submodule to take parameters from the loop instead of from the user\n embed_context = copy.copy(context)\n embed_context.submodule = True\n \n for item in _INPUT: \n if loop_with:\n inp = item[loop_with] #todo: get_value here?\n else:\n inp = item\n \n #Pass any input parameters into the submodule\n embed_context.inputs = {}\n for k in embed_conf:\n embed_context.inputs[k] = unicode(util.get_value(embed_conf[k], item))\n p = embed(embed_context, [inp], embed_conf) #prepare the submodule\n \n results = None\n try:\n for i in p:\n if mode == 'assign' and assign_part == 'first' or mode == 'EMIT' and emit_part == 'all':\n results = i\n break\n else:\n if results:\n results += i #is ok here, i.e. for assign/emit_part=all?\n else:\n results = i\n except HTTPError: #todo any other errors we want to continue looping after?\n if context.verbose:\n print \"Submodule gave HTTPError - continuing the loop\"\n continue\n \n if mode == 'assign':\n util.set_value(item, assign_to, results)\n elif mode == 'EMIT':\n item = results\n else:\n raise Exception(\"Invalid mode %s (expecting assign or EMIT)\" % mode)\n\n yield item","def test_is_in_ring(self):\n molecule = Molecule.from_smiles(\"c1ccccc1\")\n\n for atom in molecule.atoms:\n if atom.atomic_number == 6:\n assert atom.is_in_ring()\n\n for bond in molecule.bonds:\n if 1 in (bond.atom1.atomic_number, bond.atom2.atomic_number):\n continue\n assert bond.is_in_ring()","def test_perceive_residues_natoms_t4(self, strict_chirality):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/T4-protein.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def test_distributeReactor(self):\n original_reactor = self.action.r\n self.action._distributeReactor(self.cs)\n if context.MPI_RANK == 0:\n self.assertEqual(original_reactor, self.action.r)\n else:\n self.assertNotEqual(original_reactor, self.action.r)\n self.assertIsNone(self.action.r.core.lib)","def test_perceive_residues_cyclic_peptide_chirality(self, strict_chirality):\n smiles = (\n \"[H]c1c(c(c(c(c1[H])[H])C([H])([H])[C@]2(C(=O)N([C@](C(=O)N([C@@](C(=O)N3[C@@](C(=O)N2[H])\"\n \"(C(C(C3([H])[H])([H])[H])([H])[H])[H])([H])C([H])([H])[H])[H])([H])C([H])([H])C4=C(N(c5c4c(c(c(c5[H])\"\n \"[H])[H])[H])[H])[H])[H])[H])[H])[H]\"\n )\n offmol = Molecule.from_smiles(smiles)\n # perceive residues\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n if strict_chirality:\n # Make sure it fails if strict_chirality=True\n with pytest.raises(AssertionError):\n assert counter == offmol.n_atoms\n else:\n assert counter == offmol.n_atoms","def test_pulse_counter_loop(self):\n self.l.output(conf_d=0x01, state_d=0x0)\n self.l.count(reset=True)\n t10, t20 = 0.001231, 0.002063\n errmask, t1, t2 = self.l.pulse(t1=t10, t2=t20,\n lines=0x01, num_pulses=100)\n self.assertTrue(abs(t1-t10)/t10 < .1)\n self.assertTrue(abs(t2-t20)/t20 < .1)\n c, t = self.l.count()\n self.assertEqual(c, 100,\n \"counted %g pulses\" % c)"],"string":"[\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_molecule_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for molecule in mol_res_spin.molecule_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def test_spin_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for spin in mol_res_spin.spin_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_molecule_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the molecules.\\n i = 0\\n for molecule in mol_res_spin.molecule_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_residue_loop(self):\\n\\n # Loop over the residues.\\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\\n # Test the selection.\\n self.assertEqual(res.num, 2)\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)\",\n \"def test_return_residue_pipe_fail(self):\\n\\n # Try to get a residue from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def test_molecule_loop_no_selection(self):\\n\\n # Molecule data.\\n name = ['Ap4Aase', 'RNA']\\n\\n # Loop over the molecules.\\n i = 0\\n for mol in mol_res_spin.molecule_loop():\\n # Test the molecule names.\\n self.assertEqual(mol.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_molecule_loop(self):\\n\\n # Loop over the molecules.\\n for mol in mol_res_spin.molecule_loop('#RNA'):\\n # Test the molecule name.\\n self.assertEqual(mol.name, 'RNA')\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_spin_loop_no_selection(self):\\n\\n # Spin data.\\n select = [0, 1, 0, 0, 1, 1, 0, 1]\\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 8)\",\n \"def test_spin_loop(self):\\n\\n # Spin data.\\n select = [1, 0]\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, 'N5')\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 2)\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_return_molecule_pipe_fail(self):\\n\\n # Try to get a molecule from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')\",\n \"def test_return_spin_pipe_fail(self):\\n\\n # Try to get a spin from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')\",\n \"def test_count_spins_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Test for the error.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.count_spins)\",\n \"def test_spin_loop_multiatom(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_return_residue(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_residue(':1')\\n res2 = mol_res_spin.return_residue(selection=':2')\\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1.num, 1)\\n self.assertEqual(res1.name, None)\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2.num, 2)\\n self.assertEqual(res2.name, 'Glu')\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4.num, 4)\\n self.assertEqual(res4.name, 'Pro')\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5.num, -5)\\n self.assertEqual(res5.name, None)\\n self.assertEqual(res5.spin[1].name, 'N5')\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_spin_loop_wildcard(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N*'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_wrong_length(multi_mol_system_irregular, sequence):\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n with pytest.raises(ValueError):\\n processor.run_system(multi_mol_system_irregular)\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_empty_with_filter(multi_mol_system_irregular):\\n sequence = \\\"not empty\\\"\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\", sequence, molecule_selector=lambda mol: False\\n )\\n with pytest.raises(ValueError):\\n processor.run_system(multi_mol_system_irregular)\",\n \"def test_count_no_spins(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Test the number of spins counted.\\n self.assertEqual(mol_res_spin.count_spins(), 0)\",\n \"def test_multi_molecules_cycle_one(self, multi_mol_system_irregular):\\n sequence = \\\"A\\\"\\n expected = [sequence] * (15 * 3)\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_irregular)\\n found = self.sequence_from_system(multi_mol_system_irregular, \\\"test\\\")\\n assert found == expected\",\n \"def test_run_loop_success(self):\\n found = False\\n pyint = Interpreter(limit=15)\\n try:\\n pyint.run(code=BF_CODE_LOOP_TWICE)\\n except SystemExit: \\n found = True\\n self.assertFalse(found)\",\n \"def test_empty_system_empty_sequence():\\n system = vermouth.system.System()\\n sequence = \\\"\\\"\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n try:\\n processor.run_system(system)\\n except ValueError:\\n pytest.fail(\\\"Should not have raised a ValueError.\\\")\",\n \"def test_run_molecule_not_selected(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\", sequence, molecule_selector=lambda mol: False\\n )\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert vermouth.utils.are_all_equal(found)\\n assert found[0] is None\",\n \"def test_RUMI():\\r\\n\\r\\n start = 11051\\r\\n end = 11902\\r\\n read_poems(start, end)\",\n \"def test_single_molecules_cycle_one(self, single_mol_system):\\n sequence = \\\"A\\\"\\n expected = [sequence] * (5 * 3)\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def test_return_single_residue_info(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_single_residue_info('1')\\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\\n res5 = mol_res_spin.return_single_residue_info('-5')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1, (1, None))\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2, (2, 'Glu'))\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4, (4, 'Pro'))\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5, (-5, None))\",\n \"def test_empty_system_error():\\n system = vermouth.system.System()\\n sequence = \\\"not empty\\\"\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n with pytest.raises(ValueError):\\n processor.run_system(system)\",\n \"def test_multi_molecules_cycle(self, multi_mol_system_regular, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n expected = expected * 3\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_regular)\\n found = self.sequence_from_system(multi_mol_system_regular, \\\"test\\\")\\n assert found == expected\",\n \"def test_wrong_length_with_filter(multi_mol_system_irregular, sequence):\\n # We exclude the second molecule. The filter excludes it based on the\\n # number of nodes, which is 15 because it has 5 residues with 3 nodes\\n # each.\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\",\\n sequence,\\n molecule_selector=lambda mol: len(mol.nodes) != (5 * 3),\\n )\\n with pytest.raises(ValueError):\\n processor.run_system(multi_mol_system_irregular)\",\n \"def test_return_single_residue_info_fail(self):\\n\\n # Ask for a few residues.\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')\",\n \"def test_invoke_pipe_not_found():\\n\\n testapp = holocron.Application()\\n\\n with pytest.raises(ValueError) as excinfo:\\n next(testapp.invoke(\\\"test\\\"))\\n\\n assert str(excinfo.value) == \\\"no such pipe: 'test'\\\"\",\n \"def test_perceive_residues_natoms_mainchain_arginine(self, strict_chirality):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/MainChain_ARG.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def check_residue_callback(self):\\n\\n if not self.check_for_residue_existance():\\n return\\n\\n self.listbox_current_designs.delete(0, END)\\n self.current_residueFull = self.current_residue.get().split(\\\":\\\")\\n\\n if len(self.current_residueFull) > 1:\\n self.listbox_restypes.delete(9)\\n self.listbox_restypes.insert(9, \\\"Conserved\\\")\\n else:\\n res = self.current_residueFull[0] +\\\":\\\"+self.current_chain.get()\\n #print res\\n if not self.pose.total_residue():\\n return\\n\\n resType = self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get()))\\n try:\\n resName = self.pose.residue(resType).name()\\n except PyRosettaException:\\n print \\\"Residue does not exist in PDB...\\\"\\n return\\n\\n\\n self.current_residue_name_full.set(resName)\\n three_letter_name = resName.split(\\\"_\\\")[0]; #Fix for Rosetta designated chain endings, His_d\\n self.current_residue_name.set(resName)\\n\\n #Fix for not having data for certain residue types:\\n try:\\n self.design_accessible_sa.set(self.residue_definitions.resinfo[three_letter_name][0])\\n self.design_relative_mutability.set(self.residue_definitions.resinfo[three_letter_name][1])\\n self.design_surface_probability.set(self.residue_definitions.resinfo[three_letter_name][2])\\n except KeyError:\\n print \\\"No Data for restype\\\"\\n self.design_accessible_sa.set(\\\"\\\")\\n self.design_relative_mutability.set(\\\"\\\")\\n self.design_surface_probability.set(\\\"\\\")\\n\\n con = \\\"Conserved:\\\" +three_letter_name\\n self.listbox_restypes.delete(9)\\n self.listbox_restypes.insert(9, con)\\n if self.DesignDic.has_key(res):\\n for residues in self.DesignDic[res]:\\n self.listbox_current_designs.insert(END, residues)\",\n \"def test_circularloop(self):\\n cmd = f\\\"{SRC_LISTER} -i {PWD}/main\\\"\\n with subprocess.Popen(\\n shlex.split(cmd), stdout=subprocess.PIPE, stderr=subprocess.PIPE\\n ) as proc:\\n try:\\n out, err = proc.communicate(timeout=5)\\n assert len(err.strip()) > 0, \\\"Expected a circular reference error\\\"\\n except subprocess.TimeoutExpired as te:\\n print(\\\"Unexpected parser timeout during infinite loop test\\\")\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def test_78_continue(self):\\n\\t\\tinput = \\\"\\\"\\\"procedure main(); var x:integer;\\n\\t\\tbegin while(true)do begin\\n\\t\\twith x:integer; do with x:real; do begin\\n\\t\\t\\tif (x>0) then continue;\\n\\t\\t\\twith x:integer; do if (x=0) then return;\\n\\t\\tend{with} continue; end{while} continue; end\\\"\\\"\\\"\\n\\t\\texpect = \\\"Continue Not In Loop\\\"\\n\\t\\tself.assertTrue(TestChecker.test(input,expect,478))\",\n \"def waitOverlappedDone(self, count, timeout):\\n startTime = time.time()\\n while True: #wait until measuring flag goes to 0\\n try:\\n measured = self.handle.ask(\\\":DATA:POIN?;\\\")\\n measured = measured.strip() #remove CR \\n measured = int(measured) #convert to number\\n if measured == count: #final number of samples achieved\\n break;\\n except Exception:\\n print('Dvm34411.waitOverlappedDone() polling failed !')\\n raise\\n \\n if time.time() - startTime > timeout:\\n print('Dvm34411.waitOverlappedDone() timeout !')\\n return False\\n \\n samples = [] \\n for i in range(0, count):\\n try:\\n reading = self.handle.ask('R? 1;') #definite-Length block format\\n except Exception: \\n print('Dvm34411.Reading results failed !')\\n raise;\\n #DLB: '#' followed by number od decimal digits to follow\\n #the decimal number is length of data in bytes\\n if reading[0] != '#':\\n print('Dvm34411.DLB format error - # expected !')\\n return False\\n digits = int(reading[1])\\n reading = reading[2 + digits:]\\n samples.append(reading.strip())\\n \\n return samples\",\n \"def test_boolean_and_selection(self):\\n\\n # The selection loop:\\n sel = list(mol_res_spin.residue_loop(\\\"#Ap4Aase:4 & :Pro\\\"))\\n\\n # Test:\\n self.assertEqual(len(sel), 1)\\n for res in sel:\\n self.assert_(res.name == \\\"Pro\\\" and res.num == 4)\",\n \"def test_test(self):\\n\\n # The following should do nothing as the pipes exist.\\n pipes.check_pipe()\\n pipes.check_pipe('orig')\\n pipes.check_pipe('empty')\\n\\n # Assert that a RelaxNoPipeError occurs when the pipe doesn't exist.\\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe, 'x')\\n\\n # Reset relax.\\n reset()\\n\\n # Now none of the following pipes exist, hence errors should be thrown.\\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe)\\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe, 'orig')\\n self.assertRaises(RelaxNoPipeError, pipes.check_pipe, 'empty')\",\n \"def test_run_molecule(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def test_setup_explicit_solvation_system():\\n with mmtools.utils.temporary_directory() as tmp_dir:\\n yaml_script = get_template_script(tmp_dir)\\n del yaml_script['experiments']\\n exp_builder = ExperimentBuilder(yaml_script)\\n output_dir = os.path.dirname(\\n exp_builder._db.get_system('hydration-system')[0].position_path)\\n\\n # Test that output file exists and that it has correct components\\n expected_resnames = {'solvent1': set(['TOL', 'WAT']), 'solvent2': set(['TOL'])}\\n for phase in expected_resnames:\\n found_resnames = set()\\n pdb_path = os.path.join(output_dir, phase + '.pdb')\\n prmtop_path = os.path.join(output_dir, phase + '.prmtop')\\n inpcrd_path = os.path.join(output_dir, phase + '.inpcrd')\\n\\n with open(pdb_path, 'r') as f:\\n for line in f:\\n if len(line) > 10 and line[:5] != 'CRYST':\\n found_resnames.add(line[17:20])\\n\\n assert os.path.exists(prmtop_path)\\n assert os.path.exists(inpcrd_path)\\n assert os.path.getsize(prmtop_path) > 0\\n assert os.path.getsize(inpcrd_path) > 0\\n assert found_resnames == expected_resnames[phase]\",\n \"def testPipeFound(self):\\n safeFoundHelper(self)\\n self.assertCurrentState(safe.Seeking)\",\n \"def test_pump_bypass_on_reverse_flow(use_numba):\\n net = pandapipes.create_empty_network(\\\"net\\\", add_stdtypes=True)\\n\\n j1 = pandapipes.create_junction(net, pn_bar=5, tfluid_k=283.15)\\n j2 = pandapipes.create_junction(net, pn_bar=5, tfluid_k=283.15)\\n j3 = pandapipes.create_junction(net, pn_bar=5, tfluid_k=283.15)\\n j4 = pandapipes.create_junction(net, pn_bar=5, tfluid_k=283.15)\\n\\n pandapipes.create_pipe(net, j1, j2, std_type='125_PE_80_SDR_11', k_mm=1., length_km=10)\\n pandapipes.create_pipe(net, j3, j4, std_type='125_PE_80_SDR_11', k_mm=1., length_km=12)\\n pandapipes.create_ext_grid(net, j1, 5, 283.15, type=\\\"p\\\")\\n pandapipes.create_pump(net, j2, j3, std_type='P1')\\n pandapipes.create_source(net, j4, 0.02333)\\n\\n pandapipes.create_fluid_from_lib(net, \\\"hgas\\\", overwrite=True)\\n\\n pandapipes.pipeflow(net, stop_condition=\\\"tol\\\", iter=3, friction_model=\\\"nikuradse\\\",\\n mode=\\\"hydraulics\\\", transient=False, nonlinear_method=\\\"automatic\\\",\\n tol_p=1e-4, tol_v=1e-4, use_numba=use_numba)\\n\\n assert net.res_pump.deltap_bar.isin([0]).all()\\n assert np.isclose(net.res_junction.loc[1, \\\"p_bar\\\"], net.res_junction.loc[2, \\\"p_bar\\\"])\",\n \"def test_halts_if_halt_on_next(self, get_pipe_manager, raise_error):\\n pm = get_pipe_manager(name=\\\"TestPM\\\")\\n pm.halt_on_next = True\\n if raise_error:\\n with pytest.raises(PipelineHalt):\\n pm.timestamp(\\\"testing\\\")\\n else:\\n pm.timestamp(\\\"testing\\\", raise_error=False)\\n assert pm.halted\",\n \"def check_residue(self, chain_id, resid, resname):\\n if resname in PTM_lookup.keys():\\n return\\n else:\\n try:\\n ref_resname = PTM_reverse_lookup[resname]\\n except KeyError:\\n # print \\\"skipping unrecognized residue\\\", resname\\n return\\n ptm_dict = PTM_lookup[ref_resname][resname]\\n return (chain_id, resid, ref_resname, ptm_dict[\\\"goto_atom\\\"], ptm_dict[\\\"name\\\"])\",\n \"def check_pipe_setup(pipe=None, sequence=False, j=False):\\n\\n # The data pipe.\\n if pipe == None:\\n pipe = pipes.cdp_name()\\n\\n # Get the data pipe.\\n dp = pipes.get_pipe(pipe)\\n\\n # Test if the current data pipe exists.\\n check_pipe(pipe)\\n\\n # Test if sequence data exists.\\n if sequence and not exists_mol_res_spin_data(pipe):\\n raise RelaxNoSequenceError(pipe)\\n\\n # Test if J coupling data exists.\\n if j:\\n # Search for interatomic data.\\n data = False\\n for interatom in interatomic_loop():\\n if hasattr(interatom, 'j_coupling'):\\n data = True\\n break\\n\\n # No data.\\n if not data:\\n raise RelaxNoJError()\",\n \"def setUp(self):\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Name the first molecule.\\n cdp.mol[0].name = 'Ap4Aase'\\n\\n # Add a second molecule to the system.\\n cdp.mol.add_item(mol_name='RNA')\\n\\n # Add two more residues to the first molecule (and set the residue number of the first).\\n cdp.mol[0].res[0].num = 1\\n cdp.mol[0].res.add_item(res_num=2, res_name='Glu')\\n cdp.mol[0].res.add_item(res_num=4, res_name='Pro')\\n\\n # Add some spin info to this molecule.\\n cdp.mol[0].res[0].spin[0].name = 'NH'\\n cdp.mol[0].res[0].spin[0].num = 60\\n cdp.mol[0].res[1].spin[0].name = 'NH'\\n cdp.mol[0].res[1].spin[0].num = 63\\n\\n # Add one more residue to the second molecule (and set the residue number of the first).\\n cdp.mol[1].res[0].num = -5\\n cdp.mol[1].res.add_item(res_num=-4)\\n\\n # Add a second set of spins to the second molecule (naming the first set first).\\n cdp.mol[1].res[0].spin[0].name = 'C8'\\n cdp.mol[1].res[1].spin[0].name = 'C8'\\n cdp.mol[1].res[0].spin.add_item(spin_name='N5')\\n cdp.mol[1].res[1].spin.add_item(spin_name='N5')\\n cdp.mol[1].res[1].spin.add_item(spin_name='2H', spin_num=132)\\n\\n # Deselect a number of spins.\\n cdp.mol[0].res[0].spin[0].select = 0\\n cdp.mol[0].res[2].spin[0].select = 0\\n cdp.mol[1].res[0].spin[0].select = 0\\n cdp.mol[1].res[1].spin[1].select = 0\\n\\n # Update the metadata.\\n mol_res_spin.metadata_update()\",\n \"def _loop_raw(raw):\\n raise NotImplemented\",\n \"def test_run_loop_exc(self):\\n with self.assertRaises(ExecutionException):\\n pyint = Interpreter(limit=1)\\n pyint.run(code=BF_CODE_LOOP_TWICE)\",\n \"def test_stop_resume(self):\\n self.create_sample_data_set_dir(\\\"node59p1_step1.dat\\\", TELEM_DIR, \\\"node59p1.dat\\\",\\n copy_metadata=False)\\n driver_config = self._driver_config()['startup_config']\\n sio_mule_config = driver_config['harvester'][DataSourceKey.PHSEN_ABCDEF_SIO_MULE]\\n fullfile = os.path.join(sio_mule_config['directory'], sio_mule_config['pattern'])\\n mod_time = os.path.getmtime(fullfile)\\n\\n # Create and store the new driver state\\n self.memento = {DataSourceKey.PHSEN_ABCDEF_SIO_MULE: {\\n \\\"node59p1.dat\\\": {\\n DriverStateKey.FILE_SIZE: 911,\\n DriverStateKey.FILE_CHECKSUM: '8b7cf73895eded0198b3f3621f962abc',\\n DriverStateKey.FILE_MOD_DATE: mod_time,\\n DriverStateKey.PARSER_STATE: {\\n StateKey.IN_PROCESS_DATA: [],\\n StateKey.UNPROCESSED_DATA:[[0, 172]],\\n StateKey.FILE_SIZE: 911\\n }\\n }\\n }}\\n\\n self.driver = self._get_driver_object(memento=self.memento)\\n\\n # create some data to parse\\n self.clear_async_data()\\n self.create_sample_data_set_dir(\\\"node59p1_step2.dat\\\", TELEM_DIR, \\\"node59p1.dat\\\",\\n copy_metadata=False)\\n\\n self.driver.start_sampling()\\n\\n # verify data is produced\\n self.assert_data(PhsenParserDataParticle, 'test_data_2.txt.result.yml',\\n count=2, timeout=10)\",\n \"def test_ipam_rirs_read(self):\\n pass\",\n \"def residual(pars, data= None):\\n\\n\\t\\t\\tresid = np.array([])\\n\\n\\n\\t\\t\\t# make residual per data set\\n\\n\\t\\t\\tfor N in range(n_annulus):\\n\\n\\t\\t\\t\\tmdl_ev = 0\\n\\t\\t\\t\\tr_space_k = rings_pos[N+1] - rings_pos[N] \\n\\t\\t\\t\\tmask = np.where( (r_n >= rings_pos[N] ) & (r_n < rings_pos[N+1]) )\\n\\t\\t\\t\\tx,y = XY_mesh[0][mask], XY_mesh[1][mask] \\n\\t\\t\\t\\tXY = (x,y)\\n\\n\\n\\n\\n\\t\\t\\t\\tfor kk in range(2):\\n\\t\\t\\t\\t\\tVxy,Vsys = vmodel_dataset(pars, N+kk, XY, r_0 = rings_pos[N], r_space = r_space_k )\\n\\n\\t\\t\\t\\t\\tmdl_ev = mdl_ev + Vxy[kk]\\n\\n\\n\\t\\t\\t\\t\\tif N == 0 and kk == 0:\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tmask1 = np.where( (r_n < rings_pos[0] ) )\\n\\t\\t\\t\\t\\t\\tx1,y1 = XY_mesh[0][mask1], XY_mesh[1][mask1] \\n\\t\\t\\t\\t\\t\\tXY1 = (x1,y1)\\n\\n\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t# inner interpolation\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t#(a) velocity rise linearly from zero\\n\\n\\t\\t\\t\\t\\t\\tr_space_0 = rings_pos[0]\\n\\t\\t\\t\\t\\t\\tVxy,Vsys = vmodel_dataset(pars, 0, XY1, r_0 = 0, r_space = r_space_0)\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tinterp_model[mask1] = Vxy[1] + Vsys\\n\\n\\t\\t\\t\\tinterp_model[mask] = mdl_ev + Vsys\\n\\n\\n\\n\\n\\t\\t\\t\\n\\t\\t\\tsigma = np.sqrt(e_vel_map**2 + e_ISM**2)\\n\\t\\t\\t#interp_model[interp_model == 0] = np.nan\\n\\n\\n\\t\\t\\tconvolved = 0\\n\\n\\t\\t\\tif convolved == True:\\n\\n\\t\\t\\t\\tmy_beam = Beam(2.5*u.arcsec, 2.5*u.arcsec, 0*u.deg)\\n\\t\\t\\t\\tpix_scale = pixel_scale * u.arcsec\\n\\t\\t\\t\\tgauss_kern = my_beam.as_kernel(pix_scale, x_size = nx, y_size = ny)\\n\\n\\n\\t\\t\\t\\textend = np.zeros((3*ny,3*nx))\\n\\t\\t\\t\\textend[ny:2*ny,nx:2*nx] = interp_model\\n\\t\\t\\t\\tconvolve_extend = convolve_fft(extend, gauss_kern, mask = extend == 0 )\\n\\t\\t\\t\\tinterp_model_conv = convolve_extend[ny:2*ny,nx:2*nx]\\n\\t\\t\\t\\tinterp_model_conv[interp_model == 0] = 0\\n\\n\\n\\n\\n\\t\\t\\telse:\\n\\t\\t\\t\\tinterp_model_conv = interp_model\\n\\n\\t\\t\\tinterp_model_conv[interp_model_conv == 0] = np.nan\\n\\t\\t\\tres = vel_map - interp_model_conv\\n\\t\\t\\tResid = res/sigma\\n\\n\\n\\t\\t\\treturn Resid.flatten()\",\n \"def test_08(self, test):\\r\\n globalConfig.test = test\\r\\n\\r\\n forbiddenRoutes = []\\r\\n outputList = getOutputList()\\r\\n inputList = getInputList()\\r\\n if len(inputList) == 0 or len(outputList) == 0:\\r\\n return test.UNCLEAR(\\\"Not tested. No resources found.\\\")\\r\\n\\r\\n for outputInstance in outputList:\\r\\n sourceID = outputInstance.getSourceID()\\r\\n for inputInstance in inputList:\\r\\n inputParent = inputInstance.getParent()\\r\\n if inputParent['type'] == \\\"source\\\" and sourceID == inputParent['id']:\\r\\n route = {\\r\\n \\\"input\\\": inputInstance,\\r\\n \\\"output\\\": outputInstance\\r\\n }\\r\\n forbiddenRoutes.append(route)\\r\\n\\r\\n for route in forbiddenRoutes:\\r\\n outputCaps = route['output'].getCaps()\\r\\n msg = (\\\"It is possible to create a loop using re-entrant matrices \\\"\\r\\n \\\"between Input {} and Output {}\\\".format(route['input'].id, route['output'].id))\\r\\n try:\\r\\n routableInputs = outputCaps['routable_inputs']\\r\\n except KeyError:\\r\\n return test.FAIL(\\\"Could not find 'routable_inputs' in /caps \\\"\\r\\n \\\"for Output {}\\\".format(route['output'].id))\\r\\n if routableInputs is None or route['input'].id in routableInputs:\\r\\n return test.FAIL(msg)\\r\\n return test.PASS()\",\n \"def residual_processor(self):\\n def get_file(field, solver):\\n \\\"\\\"\\\"Helper method to get the file handle for a field.\\n\\n On first invocation, it creates the file with headers. On\\n subsequent invocations it just returns the relevant file handle.\\n \\\"\\\"\\\"\\n if not field in self.res_files:\\n fh = open(join(self.logs_dir, field+\\\".dat\\\"), 'w')\\n fh.write(\\\"# Field: %s; Solver: %s\\\\n\\\"%(field, solver))\\n fh.write(\\\"Time SubIteration InitialResidual FinalResidual NoIterations\\\\n\\\")\\n self.res_files[field] = fh\\n return self.res_files[field]\\n # end get_file\\n\\n try:\\n while True:\\n rexp = (yield)\\n solver = rexp.group(1) # e.g., PCB, GAMG, etc.\\n field = rexp.group(2) # Ux, Uy, p, etc.\\n\\n icorr = self.subiter_map.get(field, 0) + 1\\n self.subiter_map[field] = icorr\\n fh = get_file(field, solver)\\n fh.write(\\n self.time_str + \\\"\\\\t%d\\\\t\\\"%icorr +\\n \\\"\\\\t\\\".join([rexp.group(i) for i in range(3, 6)]) + \\\"\\\\n\\\")\\n except GeneratorExit:\\n for fh in self.res_files.values():\\n if not fh.closed:\\n fh.close()\",\n \"def test_perceive_residues_natoms_mainchain_charged_glutamic_acid(\\n self, strict_chirality\\n ):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/MainChain_GLH.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def fatal_error_processor(self):\\n while True:\\n _ = (yield)\\n self.failed = True\\n self.converged = False\\n self.solve_completed = False\",\n \"def test_wrong_turn_results_in_inf_loop():\\n\\t\\n\\t# chceme vystup v citelny podobe pro PIPE\\n\\tcp = subprocess.run([sys.executable, 'game.py'],\\n\\t\\t\\t\\t\\t\\t# misto encoding, kvuli Python3.5, pouziju univ_new\\n\\t\\t\\t\\t\\t\\tuniversal_newlines=True,\\n\\t\\t\\t\\t\\t\\tstdout=subprocess.PIPE,\\n\\t\\t\\t\\t\\t\\tinput='doggie\\\\nrock\\\\n',\\n\\t\\t\\t\\t\\t\\tcheck=True)\\n\\n\\tassert cp.stdout.count('Choice: rock, scissors, paper: ') == 2 # 2x True value\",\n \"def residual(pars, data= None):\\n\\n\\t\\t\\tresid = np.array([])\\n\\n\\n\\t\\t\\t# make residual per data set\\n\\n\\t\\t\\tfor N in range(n_annulus):\\n\\n\\t\\t\\t\\tmdl_ev = 0\\n\\t\\t\\t\\tr_space_k = rings_pos[N+1] - rings_pos[N] \\n\\t\\t\\t\\tmask = np.where( (r_n >= rings_pos[N] ) & (r_n < rings_pos[N+1]) )\\n\\t\\t\\t\\tx,y = XY_mesh[0][mask], XY_mesh[1][mask] \\n\\t\\t\\t\\tXY = (x,y)\\n\\n\\n\\n\\n\\t\\t\\t\\tfor kk in range(2):\\n\\t\\t\\t\\t\\tVxy,Vsys = vmodel_dataset(pars, N+kk, XY, r_0 = rings_pos[N], r_space = r_space_k)\\n\\n\\t\\t\\t\\t\\tmdl_ev = mdl_ev + Vxy[kk]\\n\\n\\n\\t\\t\\t\\t\\tif N == 0 and kk == 0:\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tmask1 = np.where( (r_n < rings_pos[0] ) )\\n\\t\\t\\t\\t\\t\\tx1,y1 = XY_mesh[0][mask1], XY_mesh[1][mask1] \\n\\t\\t\\t\\t\\t\\tXY1 = (x1,y1)\\n\\n\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t# inner interpolation\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t#(a) velocity rise linearly from zero\\n\\n\\t\\t\\t\\t\\t\\tr_space_0 = rings_pos[0]\\n\\t\\t\\t\\t\\t\\tVxy,Vsys = vmodel_dataset(pars, 0, XY1, r_0 = 0, r_space = r_space_0)\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tinterp_model[mask1] = Vxy[1] + Vsys\\n\\n\\t\\t\\t\\tinterp_model[mask] = mdl_ev + Vsys\\n\\n\\n\\n\\n\\t\\t\\t\\n\\t\\t\\tsigma = np.sqrt(e_vel_map**2 + e_ISM**2)\\n\\n\\n\\n\\t\\t\\tconvolved = 0\\n\\n\\t\\t\\tif convolved == True:\\n\\n\\t\\t\\t\\tmy_beam = Beam(2.5*u.arcsec, 2.5*u.arcsec, 0*u.deg)\\n\\t\\t\\t\\tpix_scale = pixel_scale * u.arcsec\\n\\t\\t\\t\\tgauss_kern = my_beam.as_kernel(pix_scale, x_size = nx, y_size = ny)\\n\\n\\n\\t\\t\\t\\textend = np.zeros((3*ny,3*nx))\\n\\t\\t\\t\\textend[ny:2*ny,nx:2*nx] = interp_model\\n\\t\\t\\t\\tconvolve_extend = convolve_fft(extend, gauss_kern, mask = extend == 0 )\\n\\t\\t\\t\\tinterp_model_conv = convolve_extend[ny:2*ny,nx:2*nx]\\n\\t\\t\\t\\tinterp_model_conv[interp_model == 0] = 0\\n\\n\\n\\t\\t\\telse:\\n\\t\\t\\t\\tinterp_model_conv = interp_model\\n\\n\\n\\t\\t\\tinterp_model_conv[interp_model_conv == 0] = np.nan\\n\\t\\t\\tres = vel_map - interp_model_conv\\n\\t\\t\\tResid = res/sigma\\n\\n\\n\\t\\t\\treturn Resid.flatten()\",\n \"def residual(pars, data= None):\\n\\n\\t\\t\\tresid = np.array([])\\n\\n\\n\\t\\t\\t# make residual per data set\\n\\n\\t\\t\\tfor N in range(n_annulus):\\n\\n\\t\\t\\t\\tmdl_ev = 0\\n\\t\\t\\t\\tr_space_k = rings_pos[N+1] - rings_pos[N] \\n\\t\\t\\t\\tmask = np.where( (r_n >= rings_pos[N] ) & (r_n < rings_pos[N+1]) )\\n\\t\\t\\t\\tx,y = XY_mesh[0][mask], XY_mesh[1][mask] \\n\\t\\t\\t\\tXY = (x,y)\\n\\n\\n\\n\\n\\t\\t\\t\\tfor kk in range(2):\\n\\t\\t\\t\\t\\tVxy,Vsys = vmodel_dataset(pars, N+kk, XY, r_0 = rings_pos[N], r_space = r_space_k)\\n\\n\\t\\t\\t\\t\\tmdl_ev = mdl_ev + Vxy[kk]\\n\\n\\n\\t\\t\\t\\t\\tif N == 0 and kk == 0:\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tmask1 = np.where( (r_n < rings_pos[0] ) )\\n\\t\\t\\t\\t\\t\\tx1,y1 = XY_mesh[0][mask1], XY_mesh[1][mask1] \\n\\t\\t\\t\\t\\t\\tXY1 = (x1,y1)\\n\\n\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t# inner interpolation\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t#(a) velocity rise linearly from zero\\n\\n\\t\\t\\t\\t\\t\\tr_space_0 = rings_pos[0]\\n\\t\\t\\t\\t\\t\\tVxy,Vsys = vmodel_dataset(pars, 0, XY1, r_0 = 0, r_space = r_space_0)\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tinterp_model[mask1] = Vxy[1] + Vsys\\n\\n\\t\\t\\t\\tinterp_model[mask] = mdl_ev + Vsys\\n\\n\\n\\n\\n\\t\\t\\t\\n\\t\\t\\tsigma = np.sqrt(e_vel_map**2 + e_ISM**2)\\n\\n\\n\\n\\t\\t\\tconvolved = 0\\n\\n\\t\\t\\tif convolved == True:\\n\\n\\t\\t\\t\\tmy_beam = Beam(2.5*u.arcsec, 2.5*u.arcsec, 0*u.deg)\\n\\t\\t\\t\\tpix_scale = pixel_scale * u.arcsec\\n\\t\\t\\t\\tgauss_kern = my_beam.as_kernel(pix_scale, x_size = nx, y_size = ny)\\n\\n\\n\\t\\t\\t\\textend = np.zeros((3*ny,3*nx))\\n\\t\\t\\t\\textend[ny:2*ny,nx:2*nx] = interp_model\\n\\t\\t\\t\\tconvolve_extend = convolve_fft(extend, gauss_kern, mask = extend == 0 )\\n\\t\\t\\t\\tinterp_model_conv = convolve_extend[ny:2*ny,nx:2*nx]\\n\\t\\t\\t\\tinterp_model_conv[interp_model == 0] = 0\\n\\n\\n\\t\\t\\telse:\\n\\t\\t\\t\\tinterp_model_conv = interp_model\\n\\n\\n\\t\\t\\tinterp_model_conv[interp_model_conv == 0] = np.nan\\n\\t\\t\\tres = vel_map - interp_model_conv\\n\\t\\t\\tResid = res/sigma\\n\\n\\t\\t\\treturn Resid.flatten()\",\n \"def residual(pars, data= None):\\n\\n\\t\\t\\tresid = np.array([])\\n\\n\\n\\t\\t\\t# make residual per data set\\n\\n\\t\\t\\tfor N in range(n_annulus):\\n\\n\\t\\t\\t\\tmdl_ev = 0\\n\\t\\t\\t\\tr_space_k = rings_pos[N+1] - rings_pos[N] \\n\\t\\t\\t\\tmask = np.where( (r_n >= rings_pos[N] ) & (r_n < rings_pos[N+1]) )\\n\\t\\t\\t\\tx,y = XY_mesh[0][mask], XY_mesh[1][mask] \\n\\t\\t\\t\\tXY = (x,y)\\n\\n\\n\\n\\n\\t\\t\\t\\tfor kk in range(2):\\n\\t\\t\\t\\t\\tVxy,Vsys = vmodel_dataset(pars, N+kk, XY, r_0 = rings_pos[N], r_space = r_space_k)\\n\\n\\t\\t\\t\\t\\tmdl_ev = mdl_ev + Vxy[kk]\\n\\n\\n\\t\\t\\t\\t\\tif N == 0 and kk == 0:\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tmask1 = np.where( (r_n < rings_pos[0] ) )\\n\\t\\t\\t\\t\\t\\tx1,y1 = XY_mesh[0][mask1], XY_mesh[1][mask1] \\n\\t\\t\\t\\t\\t\\tXY1 = (x1,y1)\\n\\n\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t# inner interpolation\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\t#\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t#(a) velocity rise linearly from zero\\n\\n\\t\\t\\t\\t\\t\\tr_space_0 = rings_pos[0]\\n\\t\\t\\t\\t\\t\\tVxy,Vsys = vmodel_dataset(pars, 0, XY1, r_0 = 0, r_space = r_space_0)\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tinterp_model[mask1] = Vxy[1] + Vsys\\n\\n\\t\\t\\t\\tinterp_model[mask] = mdl_ev + Vsys\\n\\n\\n\\n\\n\\t\\t\\t\\n\\t\\t\\tsigma = np.sqrt(e_vel_map**2 + e_ISM**2)\\n\\n\\n\\n\\t\\t\\tconvolved = 0\\n\\n\\t\\t\\tif convolved == True:\\n\\n\\t\\t\\t\\tmy_beam = Beam(2.5*u.arcsec, 2.5*u.arcsec, 0*u.deg)\\n\\t\\t\\t\\tpix_scale = pixel_scale * u.arcsec\\n\\t\\t\\t\\tgauss_kern = my_beam.as_kernel(pix_scale, x_size = nx, y_size = ny)\\n\\n\\n\\t\\t\\t\\textend = np.zeros((3*ny,3*nx))\\n\\t\\t\\t\\textend[ny:2*ny,nx:2*nx] = interp_model\\n\\t\\t\\t\\tconvolve_extend = convolve_fft(extend, gauss_kern, mask = extend == 0 )\\n\\t\\t\\t\\tinterp_model_conv = convolve_extend[ny:2*ny,nx:2*nx]\\n\\t\\t\\t\\tinterp_model_conv[interp_model == 0] = 0\\n\\n\\n\\t\\t\\telse:\\n\\t\\t\\t\\tinterp_model_conv = interp_model\\n\\n\\t\\t\\tinterp_model[interp_model == 0] = np.nan\\n\\t\\t\\tres = vel_map - interp_model_conv\\n\\t\\t\\tResid = res/sigma\\n\\n\\n\\n\\t\\t\\treturn Resid.flatten()\",\n \"def test_invoke_passthrough_items_empty_pipe():\\n\\n testapp = holocron.Application()\\n testapp.add_pipe(\\\"test\\\", [])\\n\\n stream = testapp.invoke(\\n \\\"test\\\",\\n [\\n holocron.Item(name=\\\"yoda\\\", rank=\\\"master\\\"),\\n holocron.Item(name=\\\"skywalker\\\"),\\n ],\\n )\\n\\n assert next(stream) == holocron.Item(name=\\\"yoda\\\", rank=\\\"master\\\")\\n assert next(stream) == holocron.Item(name=\\\"skywalker\\\")\\n\\n with pytest.raises(StopIteration):\\n next(testapp.invoke(\\\"test\\\"))\",\n \"def compile_loop(self, use_context=True):\\n missings = set()\\n errors = {}\\n root_vars = self.external_vars.copy()\\n\\n # Local vars computation.\\n for name, formula in self.local_vars.iteritems():\\n if name not in self._evaluated_vars:\\n try:\\n val = eval_entry(formula, root_vars, missings)\\n self._evaluated_vars[name] = val\\n except Exception as e:\\n errors['root_' + name] = repr(e)\\n\\n root_vars.update(self._evaluated_vars)\\n\\n if self.time_constrained:\\n try:\\n duration = eval_entry(self.sequence_duration, root_vars,\\n missings)\\n root_vars['sequence_end'] = duration\\n except Exception as e:\\n errors['root_seq_duration'] = repr(e)\\n\\n res, pulses = self._compile_items(root_vars, root_vars,\\n missings, errors)\\n\\n if not res:\\n return False, (missings, errors), None\\n\\n if self.time_constrained:\\n err = [p for p in pulses if p.stop > duration]\\n\\n if err:\\n mess = cleandoc('''The stop time of the following pulses {}\\n is larger than the duration of the sequence.''')\\n ind = [p.index for p in err]\\n errors['Root-stop'] = mess.format(ind)\\n return False, (missings, errors), None\\n\\n if not use_context:\\n return True, pulses, None\\n\\n else:\\n kwargs = {}\\n if self.time_constrained:\\n kwargs['sequence_duration'] = duration\\n return self.context.compile_loop(pulses, **kwargs)\",\n \"def test_rsp_invalid(self):\\n\\n def handle(event):\\n ds = Dataset()\\n ds.PatientName = \\\"Test^test\\\"\\n return 0x0000, ds\\n\\n self.ae = ae = AE()\\n ae.acse_timeout = 5\\n ae.dimse_timeout = 0.4\\n ae.network_timeout = 5\\n ae.add_supported_context(ModalityPerformedProcedureStep)\\n scp = ae.start_server(\\n (\\\"localhost\\\", 11112), block=False, evt_handlers=[(evt.EVT_N_SET, handle)]\\n )\\n\\n ae.add_requested_context(ModalityPerformedProcedureStep)\\n assoc = ae.associate(\\\"localhost\\\", 11112)\\n assert assoc.is_established\\n\\n class DummyResponse:\\n is_valid_response = False\\n\\n class DummyDIMSE:\\n msg_queue = queue.Queue()\\n gotten = False\\n\\n def send_msg(*args, **kwargs):\\n return\\n\\n def get_msg(self, *args, **kwargs):\\n if not self.gotten:\\n self.gotten = True\\n return None, DummyResponse()\\n return None, None\\n\\n assoc._reactor_checkpoint.clear()\\n while not assoc._is_paused:\\n time.sleep(0.01)\\n assoc.dimse = DummyDIMSE()\\n mod_list = Dataset()\\n mod_list.PatientName = \\\"Test^test\\\"\\n status, ds = assoc.send_n_set(\\n mod_list, ModalityPerformedProcedureStep, \\\"1.2.840.10008.5.1.1.40.1\\\"\\n )\\n\\n assert status == Dataset()\\n assert ds is None\\n assert assoc.is_aborted\\n\\n scp.shutdown()\",\n \"def next():\\n iraw = 0\\n run = 0\\n seqno = 0\\n with db_connection() as conn:\\n with conn.cursor() as curs:\\n try:\\n curs.execute(\\\"\\\"\\\"SELECT rawdata.id,rawdata.run,rawdata.seqno,\\n slices.block1,slices.block2,\\n jobs.cluster,jobs.process\\n FROM rawdata\\n LEFT JOIN bindings\\n ON bindings.iraw = rawdata.id\\n INNER JOIN slices\\n ON slices.iraw = rawdata.id\\n LEFT JOIN jobs\\n ON slices.ijob = jobs.id\\n AND jobs.exitcode = 0\\n WHERE bindings.id IS NULL\\n ORDER BY rawdata.id,slices.block1\\n LIMIT 2000;\\n \\\"\\\"\\\")\\n slices_missing = 1\\n for row in curs.fetchall():\\n i = int(row[0])\\n if i != iraw:\\n if slices_missing == 0:\\n break\\n else:\\n run = int(row[1])\\n seqno = int(row[2])\\n slices_missing = 0\\n slices = []\\n iraw = i\\n block1 = int(row[3])\\n block2 = int(row[4])\\n if row[5] is not None and row[6] is not None:\\n cluster = int(row[5])\\n process = int(row[6])\\n slices.append((block1,block2,cluster,process))\\n else:\\n print(\\\"slices missing on\\\", row[5], row[6])\\n slices_missing += 1\\n if slices_missing:\\n return 0\\n else:\\n curs.execute(\\\"SELECT TIMEZONE('GMT', NOW());\\\")\\n now = curs.fetchone()[0]\\n curs.execute(\\\"\\\"\\\"INSERT INTO bindings\\n (iraw,starttime)\\n VALUES (%s,%s)\\n RETURNING id;\\n \\\"\\\"\\\", (iraw, now))\\n row = curs.fetchone()\\n if row:\\n ibind = int(row[0])\\n else:\\n return 0\\n except:\\n iraw = 0\\n if iraw == 0:\\n time.sleep(random.randint(1,30))\\n return -9 # collision\\n\\n workdir = str(iraw)\\n os.mkdir(workdir)\\n os.chdir(workdir)\\n badslices = []\\n for sl in slices:\\n sdir = str(sl[0]) + \\\",\\\" + str(sl[1])\\n os.mkdir(sdir)\\n tarfile = \\\"job_{0}_{1}.tar.gz\\\".format(sl[2], sl[3])\\n tarpath = input_area + \\\"/\\\" + tarfile\\n try:\\n subprocess.check_output([\\\"gfal-copy\\\", src_url + tarpath,\\n \\\"file://\\\" + os.getcwd() + \\\"/\\\" + tarfile])\\n except:\\n sys.stderr.write(\\\"Error -999 on rawdata id {0}\\\".format(iraw) +\\n \\\" - job output \\\" + tarfile + \\\" is missing!\\\\n\\\")\\n sys.stderr.flush()\\n badslices.append(sdir)\\n continue\\n try:\\n subprocess.check_output([\\\"tar\\\", \\\"zxf\\\", tarfile, \\\"-C\\\", sdir])\\n except:\\n sys.stderr.write(\\\"Error -999 on rawdata id {0}\\\".format(iraw) +\\n \\\" - job output \\\" + tarfile + \\\" is not readable!\\\\n\\\")\\n sys.stderr.flush()\\n badslices.append(sdir)\\n finally:\\n os.remove(tarfile)\\n if len(badslices) > 0:\\n with db_connection() as conn:\\n with conn.cursor() as curs:\\n curs.execute(\\\"SELECT TIMEZONE('GMT', NOW());\\\")\\n now = curs.fetchone()[0]\\n curs.execute(\\\"\\\"\\\"UPDATE bindings\\n SET endtime=%s, \\n exitcode=%s,\\n details=%s\\n WHERE id = %s;\\n \\\"\\\"\\\", (now, -999, \\\":\\\".join(badslices), ibind))\\n os.chdir(\\\"..\\\")\\n shutil.rmtree(workdir)\\n return 1\\n\\n badslices += merge_evio_skims(run, seqno, slices)\\n badslices += merge_hddm_output(run, seqno, slices)\\n badslices += merge_job_info(run, seqno, slices)\\n badslices += merge_root_histos(run, seqno, slices)\\n exitcode = -len(badslices)\\n with db_connection() as comm:\\n with conn.cursor() as curs:\\n curs.execute(\\\"SELECT TIMEZONE('GMT', NOW());\\\")\\n now = curs.fetchone()[0]\\n curs.execute(\\\"\\\"\\\"UPDATE bindings\\n SET endtime=%s,\\n exitcode=%s,\\n details=%s\\n WHERE id = %s;\\n \\\"\\\"\\\", (now, exitcode, \\\":\\\".join(badslices), ibind))\\n os.chdir(\\\"..\\\")\\n shutil.rmtree(workdir)\\n return 1\",\n \"def test_boolean_complex_selection(self):\\n\\n # The residue selection loop.\\n sel = list(mol_res_spin.residue_loop(\\\"#Ap4Aase:4 & :Pro | #RNA\\\"))\\n\\n # Residue names and numbers.\\n names = ['Pro', None, None]\\n numbers = [4, -5, -4]\\n\\n # The residues.\\n self.assertEqual(len(sel), 3)\\n for i in range(3):\\n self.assertEqual(sel[i].name, names[i])\\n self.assertEqual(sel[i].num, numbers[i])\",\n \"def test_policer_handoff_input(self):\\n self.policer_handoff_test(Dir.RX)\",\n \"def test_reset(self):\\n ran = []\\n def foo():\\n ran.append(None)\\n\\n c = task.Clock()\\n lc = TestableLoopingCall(c, foo)\\n lc.start(2, now=False)\\n c.advance(1)\\n lc.reset()\\n c.advance(1)\\n self.assertEqual(ran, [])\\n c.advance(1)\\n self.assertEqual(ran, [None])\",\n \"def test_return_molecule(self):\\n\\n # Ask for a few molecules.\\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\\n\\n # Test the data of molecule 1.\\n self.assertEqual(mol1.name, 'Ap4Aase')\\n\\n # Test the data of molecule 2.\\n self.assertEqual(mol2.name, 'RNA')\",\n \"def test_single_molecule(self, single_mol_system, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def algorithm_loop(self):\",\n \"def _readloop(self):\\r\\n\\r\\n while self._ll_alive:\\r\\n with self._rx_lock:\\r\\n data = self._Random(1)\\r\\n if len(data) != 0: # check for timeout\\r\\n self._uart_rx_queue.put(data)\",\n \"def check_for_residue_existance(self):\\n if not self.pose.total_residue():\\n print \\\"No pose Loaded.\\\"\\n return False\\n\\n if not self.current_chain.get() or not self.current_residue.get():\\n print \\\"Chain or residue not set\\\"\\n return False\\n\\n current_region = self.current_residue.get().split(\\\":\\\")\\n if len(current_region)>1:\\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\\n\\n\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\\n print \\\"Region not found in pose\\\"\\n return False\\n else:\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\\n\\n print \\\"Residue not found in pose\\\"\\n return False\\n\\n #If everythig is good then:\\n return True\",\n \"def test_perceive_residues_natoms_mainchain_glutamic_acid(self, strict_chirality):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/MainChain_GLU.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def test_chunk_pauli(self, method, device):\\n opts_no_chunk = {\\\"fusion_enable\\\": False}\\n opts_chunk = copy.copy(opts_no_chunk)\\n opts_chunk[\\\"blocking_enable\\\"] = True\\n opts_chunk[\\\"blocking_qubits\\\"] = 3\\n\\n backend = self.backend(method=method, device=device, **opts_chunk)\\n backend_no_chunk = self.backend(method=method, device=device, **opts_no_chunk)\\n\\n shots = 100\\n\\n qr = QuantumRegister(5)\\n cr = ClassicalRegister(5)\\n regs = (qr, cr)\\n circuit = QuantumCircuit(*regs)\\n circuit.h(qr[0])\\n circuit.h(qr[1])\\n circuit.h(qr[2])\\n circuit.h(qr[3])\\n circuit.h(qr[4])\\n circuit.pauli(\\\"YXZYX\\\", qr)\\n circuit.measure_all()\\n\\n result = backend.run(circuit, shots=shots, memory=True).result()\\n counts = result.get_counts(circuit)\\n result_no_chunk = backend_no_chunk.run(circuit, shots=shots, memory=True).result()\\n counts_no_chunk = result_no_chunk.get_counts(circuit)\\n\\n self.assertEqual(counts_no_chunk, counts)\",\n \"def wait_for_data(receiver):\\n\\n while not receiver.available(pipes[1]):\\n time.sleep(0.01)\",\n \"def test_ls_empty():\\n with pipeline.fixture(assets=[], versions=0):\\n assert_raises(StopIteration, next, pipeline.ls())\",\n \"def test_pure_prisoners_dilemma(_):\\n game = gamegen.sym_2p2s_game(2, 0, 3, 1) # prisoners dilemma\\n eqm = [0, 2]\\n\\n assert (\\n regret.pure_strategy_regret(game, eqm) == 0\\n ), \\\"Known equilibrium was not zero regret\\\"\",\n \"def revProcess(env):\\n api.injectInteger(propdb.PROP_IGNITION_STATE, propdb.IGNITION_STATE_ON)\\n while True:\\n \\n if vehicle_data.rpm < 3000:\\n vehicle_data.rpm += 50\\n elif vehicle_data.gear < 5:\\n vehicle_data.rpm = vehicle_data.speed * 100.0 / (vehicle_data.gear + 1)\\n vehicle_data.gear += 1\\n \\n vehicle_data.speed = vehicle_data.rpm * vehicle_data.gear / 100.0\\n\\n yield env.timeout(0.025)\",\n \"def test_non_pauli_error(self):\\n circuit = hadamard_circuit(3)\\n bits, recipes = circuit()\\n shadow = ClassicalShadow(bits, recipes)\\n\\n H = qml.Hadamard(0) @ qml.Hadamard(2)\\n\\n msg = \\\"Observable must be a linear combination of Pauli observables\\\"\\n with pytest.raises(ValueError, match=msg):\\n shadow.expval(H, k=10)\",\n \"def _while_loop(pd, nmax, max_loop, ncore, outfile):\\n \\n # make sure the random seed is different for every processor\\n random_number_seeds = [3456789, 7654321, 2435467, 8273645,\\n 1085712, 4154712, 1248291, 8415917,\\n 2345161, 5710916, 5718601, 7516234,\\n 9235161, 4917519, 1111245, 8167834] \\n \\n # get the processor ID (1 - Ncore) and convert to single integer\\n current = multiprocessing.current_process()\\n pid = current._identity\\n pid = pid[0]\\n \\n #\\n # choose a different seed for each processor from the list so each processor has\\n # a different randum number seed. Then, fiddle with each seed a little so \\n # the seeds aren't the same every time the code is run\\n seed = np.int(random_number_seeds[pid] * (np.random.rand()*(10.0 - 0.01) + 0.01))\\n \\n np.random.seed(seed)\\n \\n #print 'id and seed', pid, seed\\n \\n n_particles = 0\\n loop_counter = 0\\n fmin_scale = 1.0E-100 # -16 -> -32 -> -100\\n F_max = np.max(pd.DF.f) #; F_min = np.min(pd.DF.f);\\n F_min = np.min(pd.DF.f) * fmin_scale\\n # F_max = np.max(pd.DF.f[:-1])#; F_max = 1.0E-88\\n #print F_min, F_max\\n if pd.optimize:\\n relative_potential = pd._interpolate_relative_potential\\n else:\\n relative_potential = pd.DF.relative_potential\\n \\n \\n pos = np.zeros((nmax, 3))\\n vel = np.zeros((nmax, 3)) \\n \\n while (( n_particles < nmax) and (loop_counter < max_loop)):\\n \\n r = pd._choose_position()\\n Psi = relative_potential(r) \\n \\n v = pd._choose_velocity(r, Psi)\\n \\n E = Psi - 0.5 * v * v\\n \\n f_E = pd.DF.interpolate_f(E)\\n \\n logF = ( np.random.rand()*(np.log10(F_max) - np.log10(F_min)) + np.log10(F_min) )\\n \\n # if choosing random F in log F, might be good to do the comparison in logspace as well\\n #.... i.e log(F) <= log(f_E) \\n #\\n # 0 FOR F_E MEANS THAT E < E_min of the potential. THis happens when Psi - KE is smaller\\n # than the value of the potential at large_r... should this be considered unbound \\n # even though it isn't zero? Is this effectively zero? This has been adjusted in the velocity\\n # picking routine but needs verification to make sure it works.... but regardless, I doubt\\n # that this is the reason why the particles are failing for NFW but working for hernquist....\\n #\\n if np.abs(np.log10(f_E)) == np.inf:\\n keep_particle = False\\n _my_print('log value error... throwing out particle')\\n else:\\n keep_particle = (logF <= np.log10(f_E))\\n\\n \\n if keep_particle: \\n index = n_particles \\n \\n # \\n # need to sample in cosine theta NOT theta!!!!! WTF!!!!!\\n #\\n #\\n \\n theta = np.arccos( np.random.rand() * (2.0) - 1.0)\\n \\n # convert position to cartesian using random theta and phi\\n phi = np.random.rand() * 2.0 * np.pi\\n \\n x = np.sin(theta) * np.cos(phi)\\n y = np.sin(theta) * np.sin(phi)\\n z = np.cos(theta)\\n \\n pos[index] = r * np.array([x,y,z])\\n\\n # repeat for velocity using new random numbersw\\n theta = np.arccos( np.random.rand() * (2.0) - 1.0)\\n phi = np.random.rand() * 2.0 * np.pi\\n \\n vx = np.sin(theta) * np.cos(phi)\\n vy = np.sin(theta) * np.sin(phi)\\n vz = np.cos(theta)\\n \\n vel[index] = v * np.array([vx,vy,vz])\\n \\\"\\\"\\\" \\n #else: # do strict cartesian ... slower.... less attractive\\n # \\n # axis_list = [0, 1, 2]\\n # random.shuffle(axis_list)\\n \\n # #axis_index = np.random.randint(3)\\n # first_axis = axis_list[0]\\n #\\n # pos[index, first_axis] = np.random.rand() * (2.0*r) - r\\n #del axis_list[axis_index]\\n \\n #axis_index = np.random.randint(2)\\n # second_axis = axis_list[1]\\n \\n max_r = np.sqrt(r*r - pos[index,first_axis]**2)\\n \\n pos[index, second_axis] = np.random.rand()*(2.0 * max_r) - max_r\\n #del axis_list[axis_index]\\n \\n max_r = np.sqrt(r*r - pos[index,first_axis]**2 - pos[index,second_axis]**2)\\n \\n third_axis = axis_list[2]\\n pos[index, third_axis] = np.random.rand() * (2.0 * max_r) - max_r\\n \\n if np.sqrt(pos[index,0]**2 + pos[index,1]**2 + pos[index,2]**2) > r:\\n _my_print('R IS TOO LARGE')\\n \\n ###\\n axis_list = [0, 1, 2]\\n random.shuffle(axis_list)\\n \\n #axis_index = np.random.randint(3)\\n first_axis = axis_list[0]\\n \\n vel[index, first_axis] = np.random.rand() * (2.0*v) - v\\n #del axis_list[axis_index]\\n \\n #axis_index = np.random.randint(2)\\n second_axis = axis_list[1]\\n \\n max_v = np.sqrt(v*v - vel[index,first_axis]**2)\\n \\n vel[index, second_axis] = np.random.rand()*(2.0 * max_v) - max_v\\n #del axis_list[axis_index]\\n \\n max_v = np.sqrt(v*v - vel[index,first_axis]**2 - vel[index,second_axis]**2)\\n \\n third_axis = axis_list[2]\\n vel[index, third_axis] = np.random.rand() * (2.0 * max_v) - max_v \\n \\n \\n \\\"\\\"\\\"\\n n_particles = n_particles + 1\\n \\n if (loop_counter % 5000) == 0:\\n _my_print(\\\"Have %4i particles. On loop %6i\\\"%(n_particles, loop_counter))\\n loop_counter = loop_counter + 1\\n \\n # now write out to a temporary file\\n f = open(outfile + \\\"_%02i_\\\"%(pid) + \\\".temp\\\", 'w')\\n fmt = \\\"%12.12E %12.12E %12.12E %12.12E %12.12E %12.12E %12.12E\\\\n\\\"\\n \\n \\n for i in np.arange(nmax):\\n f.write(fmt%(pd.M_part, pos[i,0], pos[i,1], pos[i,2], \\n vel[i,0], vel[i,1], vel[i,2]))\\n \\n \\n f.close() \\n \\n return pos, vel\",\n \"def test_rebinpds(self):\\n command = '{0} -r 2'.format(\\n os.path.join(self.datadir, 'monol_testA_E3-50_pds') +\\n HEN_FILE_EXTENSION)\\n hen.rebin.main(command.split())\\n os.path.exists(os.path.join(self.datadir,\\n 'monol_testA_E3-50_pds_rebin2' +\\n HEN_FILE_EXTENSION))\",\n \"def test_nothing_perceived_dipeptide(self):\\n from openff.toolkit._tests.create_molecules import dipeptide as create_dipeptide\\n\\n dipeptide = create_dipeptide()\\n\\n with pytest.raises(KeyError):\\n assert dipeptide.atoms[0].metadata[\\\"residue_name\\\"] is None\\n with pytest.raises(KeyError):\\n assert \\\"ALA\\\" == dipeptide.atoms[10].metadata[\\\"residue_name\\\"]\\n with pytest.raises(KeyError):\\n assert 1 == dipeptide.atoms[10].metadata[\\\"residue_number\\\"]\\n with pytest.raises(KeyError):\\n assert \\\" \\\" == dipeptide.atoms[10].metadata[\\\"insertion_code\\\"]\\n with pytest.raises(AttributeError):\\n dipeptide.residues[0]\",\n \"def test_74_break(self):\\n\\t\\tinput = \\\"\\\"\\\"procedure main(); var x:integer;\\n\\t\\tbegin while(true)do begin\\n\\t\\twith x:integer; do with x:real; do begin\\n\\t\\t\\tif (x>0) then break;\\n\\t\\t\\twith x:integer; do if (x=0) then return;\\n\\t\\tend{with} break; end{while} break; end\\\"\\\"\\\"\\n\\t\\texpect = \\\"Break Not In Loop\\\"\\n\\t\\tself.assertTrue(TestChecker.test(input,expect,474))\",\n \"def read(self):\\n try:\\n cmd = 'SAMP:COUN 1' \\n self.handle.write(cmd) #one sample per trigger\\n self.handle.write('TRIG:SOUR BUS') #triggered by command\\n self.handle.write('TRIG:COUN 1') #one trigger to return to wait for trg\\n self.handle.write('INIT:IMM') #DVM to \\\"wait for trigger\\\" \\n self.handle.write('*TRG')\\n startTime = time.time()\\n while True: #wait until measuring flag goes to 0\\n try:\\n measured = self.handle.ask(\\\"DATA:POIN?\\\")\\n measured = measured.strip() #remove CR \\n measured = int(measured) #convert to number\\n if measured == 1: #final number of samples achieved\\n break;\\n except Exception:\\n print('Dvm34411:read() polling failed !')\\n raise\\n \\n if time.time() - startTime > self.timeout:\\n print('Dvm34411:read() timeout !')\\n return False\\n \\n time.sleep(1) \\n reading = self.handle.ask('R? 1;') #definite-Length block format\\n except Exception:\\n print('Dvm34411.read() failed !')\\n raise\\n if reading[0] != '#':\\n print('Dvm34411.read() DLB format error - # expected !')\\n return False\\n digits = int(reading[1])\\n reading = reading[2 + digits:]\\n rdg = float(reading)\\n return rdg\",\n \"def pipe_loop(context, _INPUT, conf, embed=None, **kwargs):\\n mode = conf['mode']['value']\\n assign_to = conf['assign_to']['value']\\n assign_part = conf['assign_part']['value']\\n emit_part = conf['emit_part']['value']\\n loop_with = conf['with']['value']\\n embed_conf = conf['embed']['value']['conf']\\n \\n #Prepare the submodule to take parameters from the loop instead of from the user\\n embed_context = copy.copy(context)\\n embed_context.submodule = True\\n \\n for item in _INPUT: \\n if loop_with:\\n inp = item[loop_with] #todo: get_value here?\\n else:\\n inp = item\\n \\n #Pass any input parameters into the submodule\\n embed_context.inputs = {}\\n for k in embed_conf:\\n embed_context.inputs[k] = unicode(util.get_value(embed_conf[k], item))\\n p = embed(embed_context, [inp], embed_conf) #prepare the submodule\\n \\n results = None\\n try:\\n for i in p:\\n if mode == 'assign' and assign_part == 'first' or mode == 'EMIT' and emit_part == 'all':\\n results = i\\n break\\n else:\\n if results:\\n results += i #is ok here, i.e. for assign/emit_part=all?\\n else:\\n results = i\\n except HTTPError: #todo any other errors we want to continue looping after?\\n if context.verbose:\\n print \\\"Submodule gave HTTPError - continuing the loop\\\"\\n continue\\n \\n if mode == 'assign':\\n util.set_value(item, assign_to, results)\\n elif mode == 'EMIT':\\n item = results\\n else:\\n raise Exception(\\\"Invalid mode %s (expecting assign or EMIT)\\\" % mode)\\n\\n yield item\",\n \"def test_is_in_ring(self):\\n molecule = Molecule.from_smiles(\\\"c1ccccc1\\\")\\n\\n for atom in molecule.atoms:\\n if atom.atomic_number == 6:\\n assert atom.is_in_ring()\\n\\n for bond in molecule.bonds:\\n if 1 in (bond.atom1.atomic_number, bond.atom2.atomic_number):\\n continue\\n assert bond.is_in_ring()\",\n \"def test_perceive_residues_natoms_t4(self, strict_chirality):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/T4-protein.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def test_distributeReactor(self):\\n original_reactor = self.action.r\\n self.action._distributeReactor(self.cs)\\n if context.MPI_RANK == 0:\\n self.assertEqual(original_reactor, self.action.r)\\n else:\\n self.assertNotEqual(original_reactor, self.action.r)\\n self.assertIsNone(self.action.r.core.lib)\",\n \"def test_perceive_residues_cyclic_peptide_chirality(self, strict_chirality):\\n smiles = (\\n \\\"[H]c1c(c(c(c(c1[H])[H])C([H])([H])[C@]2(C(=O)N([C@](C(=O)N([C@@](C(=O)N3[C@@](C(=O)N2[H])\\\"\\n \\\"(C(C(C3([H])[H])([H])[H])([H])[H])[H])([H])C([H])([H])[H])[H])([H])C([H])([H])C4=C(N(c5c4c(c(c(c5[H])\\\"\\n \\\"[H])[H])[H])[H])[H])[H])[H])[H])[H]\\\"\\n )\\n offmol = Molecule.from_smiles(smiles)\\n # perceive residues\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n if strict_chirality:\\n # Make sure it fails if strict_chirality=True\\n with pytest.raises(AssertionError):\\n assert counter == offmol.n_atoms\\n else:\\n assert counter == offmol.n_atoms\",\n \"def test_pulse_counter_loop(self):\\n self.l.output(conf_d=0x01, state_d=0x0)\\n self.l.count(reset=True)\\n t10, t20 = 0.001231, 0.002063\\n errmask, t1, t2 = self.l.pulse(t1=t10, t2=t20,\\n lines=0x01, num_pulses=100)\\n self.assertTrue(abs(t1-t10)/t10 < .1)\\n self.assertTrue(abs(t2-t20)/t20 < .1)\\n c, t = self.l.count()\\n self.assertEqual(c, 100,\\n \\\"counted %g pulses\\\" % c)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.85945946","0.77838326","0.7751666","0.76332873","0.7629808","0.7481475","0.6956494","0.69382966","0.68887913","0.65152484","0.6382403","0.63752276","0.6283524","0.6206884","0.62047124","0.61061484","0.6081791","0.6047085","0.59946924","0.5982436","0.5883731","0.5819783","0.57810205","0.56473935","0.55041945","0.5470499","0.546334","0.5459113","0.5319738","0.53138393","0.5289875","0.5192066","0.51624835","0.5131608","0.51271546","0.51191574","0.5115809","0.50559765","0.50505704","0.5041564","0.49913374","0.4972682","0.4951229","0.49410865","0.4934736","0.49311888","0.4917329","0.489112","0.4883294","0.4876569","0.48401448","0.48365992","0.4823597","0.48206982","0.48107624","0.4809277","0.48039705","0.47965539","0.47941694","0.4776951","0.47726226","0.47705284","0.47582877","0.47576508","0.47561628","0.47496766","0.4732447","0.4728533","0.4728533","0.4728533","0.4725772","0.47254133","0.4717214","0.47164047","0.4709128","0.47081423","0.47026727","0.46920726","0.46842557","0.46713567","0.46695155","0.4666046","0.46659672","0.4653283","0.46506977","0.46505272","0.46462616","0.4641241","0.46095425","0.46021688","0.4600683","0.4596645","0.45953146","0.45892885","0.45859733","0.45799145","0.45779344","0.45736706","0.45653737","0.45606548"],"string":"[\n \"0.85945946\",\n \"0.77838326\",\n \"0.7751666\",\n \"0.76332873\",\n \"0.7629808\",\n \"0.7481475\",\n \"0.6956494\",\n \"0.69382966\",\n \"0.68887913\",\n \"0.65152484\",\n \"0.6382403\",\n \"0.63752276\",\n \"0.6283524\",\n \"0.6206884\",\n \"0.62047124\",\n \"0.61061484\",\n \"0.6081791\",\n \"0.6047085\",\n \"0.59946924\",\n \"0.5982436\",\n \"0.5883731\",\n \"0.5819783\",\n \"0.57810205\",\n \"0.56473935\",\n \"0.55041945\",\n \"0.5470499\",\n \"0.546334\",\n \"0.5459113\",\n \"0.5319738\",\n \"0.53138393\",\n \"0.5289875\",\n \"0.5192066\",\n \"0.51624835\",\n \"0.5131608\",\n \"0.51271546\",\n \"0.51191574\",\n \"0.5115809\",\n \"0.50559765\",\n \"0.50505704\",\n \"0.5041564\",\n \"0.49913374\",\n \"0.4972682\",\n \"0.4951229\",\n \"0.49410865\",\n \"0.4934736\",\n \"0.49311888\",\n \"0.4917329\",\n \"0.489112\",\n \"0.4883294\",\n \"0.4876569\",\n \"0.48401448\",\n \"0.48365992\",\n \"0.4823597\",\n \"0.48206982\",\n \"0.48107624\",\n \"0.4809277\",\n \"0.48039705\",\n \"0.47965539\",\n \"0.47941694\",\n \"0.4776951\",\n \"0.47726226\",\n \"0.47705284\",\n \"0.47582877\",\n \"0.47576508\",\n \"0.47561628\",\n \"0.47496766\",\n \"0.4732447\",\n \"0.4728533\",\n \"0.4728533\",\n \"0.4728533\",\n \"0.4725772\",\n \"0.47254133\",\n \"0.4717214\",\n \"0.47164047\",\n \"0.4709128\",\n \"0.47081423\",\n \"0.47026727\",\n \"0.46920726\",\n \"0.46842557\",\n \"0.46713567\",\n \"0.46695155\",\n \"0.4666046\",\n \"0.46659672\",\n \"0.4653283\",\n \"0.46506977\",\n \"0.46505272\",\n \"0.46462616\",\n \"0.4641241\",\n \"0.46095425\",\n \"0.46021688\",\n \"0.4600683\",\n \"0.4596645\",\n \"0.45953146\",\n \"0.45892885\",\n \"0.45859733\",\n \"0.45799145\",\n \"0.45779344\",\n \"0.45736706\",\n \"0.45653737\",\n \"0.45606548\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.86027044"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81496,"cells":{"query":{"kind":"string","value":"Test the proper operation of the residue loop when no selection is present. The function tested is pipe_control.mol_res_spin.residue_loop()."},"document":{"kind":"string","value":"def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_residue_loop(self):\n\n # Loop over the residues.\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\n # Test the selection.\n self.assertEqual(res.num, 2)\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)","def test_residue_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for residue in mol_res_spin.residue_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_spin_loop_no_selection(self):\n\n # Spin data.\n select = [0, 1, 0, 0, 1, 1, 0, 1]\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 8)","def test_molecule_loop_no_selection(self):\n\n # Molecule data.\n name = ['Ap4Aase', 'RNA']\n\n # Loop over the molecules.\n i = 0\n for mol in mol_res_spin.molecule_loop():\n # Test the molecule names.\n self.assertEqual(mol.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_spin_loop(self):\n\n # Spin data.\n select = [1, 0]\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, 'N5')\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 2)","def test_molecule_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for molecule in mol_res_spin.molecule_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_boolean_and_selection(self):\n\n # The selection loop:\n sel = list(mol_res_spin.residue_loop(\"#Ap4Aase:4 & :Pro\"))\n\n # Test:\n self.assertEqual(len(sel), 1)\n for res in sel:\n self.assert_(res.name == \"Pro\" and res.num == 4)","def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_spin_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for spin in mol_res_spin.spin_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_return_residue(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_residue(':1')\n res2 = mol_res_spin.return_residue(selection=':2')\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\n\n # Test the data of residue 1.\n self.assertEqual(res1.num, 1)\n self.assertEqual(res1.name, None)\n\n # Test the data of residue 2.\n self.assertEqual(res2.num, 2)\n self.assertEqual(res2.name, 'Glu')\n\n # Test the data of residue 4.\n self.assertEqual(res4.num, 4)\n self.assertEqual(res4.name, 'Pro')\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5.num, -5)\n self.assertEqual(res5.name, None)\n self.assertEqual(res5.spin[1].name, 'N5')","def test_boolean_complex_selection(self):\n\n # The residue selection loop.\n sel = list(mol_res_spin.residue_loop(\"#Ap4Aase:4 & :Pro | #RNA\"))\n\n # Residue names and numbers.\n names = ['Pro', None, None]\n numbers = [4, -5, -4]\n\n # The residues.\n self.assertEqual(len(sel), 3)\n for i in range(3):\n self.assertEqual(sel[i].name, names[i])\n self.assertEqual(sel[i].num, numbers[i])","def test_spin_loop_multiatom(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_run_molecule_not_selected(self, single_mol_system):\n sequence = \"ABCDE\"\n processor = dssp.AnnotateResidues(\n \"test\", sequence, molecule_selector=lambda mol: False\n )\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert vermouth.utils.are_all_equal(found)\n assert found[0] is None","def test_return_residue_pipe_fail(self):\n\n # Try to get a residue from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')","def test_molecule_loop(self):\n\n # Loop over the molecules.\n for mol in mol_res_spin.molecule_loop('#RNA'):\n # Test the molecule name.\n self.assertEqual(mol.name, 'RNA')\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)","def test_spin_loop_wildcard(self):\n\n # Spin data.\n select = [0, 1, 1, 0]\n name = ['NH', 'NH', 'N5', 'N5']\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop('@N*'):\n # Test the selection.\n self.assertEqual(spin.select, select[i])\n\n # Test the spin names.\n self.assertEqual(spin.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 4)","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def ROOMSELECTION_LOOP():\n pass","def check_residue_callback(self):\n\n if not self.check_for_residue_existance():\n return\n\n self.listbox_current_designs.delete(0, END)\n self.current_residueFull = self.current_residue.get().split(\":\")\n\n if len(self.current_residueFull) > 1:\n self.listbox_restypes.delete(9)\n self.listbox_restypes.insert(9, \"Conserved\")\n else:\n res = self.current_residueFull[0] +\":\"+self.current_chain.get()\n #print res\n if not self.pose.total_residue():\n return\n\n resType = self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get()))\n try:\n resName = self.pose.residue(resType).name()\n except PyRosettaException:\n print \"Residue does not exist in PDB...\"\n return\n\n\n self.current_residue_name_full.set(resName)\n three_letter_name = resName.split(\"_\")[0]; #Fix for Rosetta designated chain endings, His_d\n self.current_residue_name.set(resName)\n\n #Fix for not having data for certain residue types:\n try:\n self.design_accessible_sa.set(self.residue_definitions.resinfo[three_letter_name][0])\n self.design_relative_mutability.set(self.residue_definitions.resinfo[three_letter_name][1])\n self.design_surface_probability.set(self.residue_definitions.resinfo[three_letter_name][2])\n except KeyError:\n print \"No Data for restype\"\n self.design_accessible_sa.set(\"\")\n self.design_relative_mutability.set(\"\")\n self.design_surface_probability.set(\"\")\n\n con = \"Conserved:\" +three_letter_name\n self.listbox_restypes.delete(9)\n self.listbox_restypes.insert(9, con)\n if self.DesignDic.has_key(res):\n for residues in self.DesignDic[res]:\n self.listbox_current_designs.insert(END, residues)","def fixme_test_boolean_parenthesis_selection(self):\n\n # The selection loop:\n sel = list(mol_res_spin.residue_loop(\"(#Ap4Aase & :Pro) | (#RNA & :-4)\"))\n\n # Test:\n self.assertEqual(len(sel), 2)\n for res in sel:\n self.assert_(res.num in [-4, 4])","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_multi_molecules_cycle_one(self, multi_mol_system_irregular):\n sequence = \"A\"\n expected = [sequence] * (15 * 3)\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_irregular)\n found = self.sequence_from_system(multi_mol_system_irregular, \"test\")\n assert found == expected","def nextRes(self):\n\n self.current_residueFull = self.current_residue.get().split(\":\")\n if len(self.current_residueFull) < 2:\n res = int(self.current_residue.get())+1\n self.current_residue.set(res)\n self.check_residue_callback()\n else:\n print \"Please Change selection to get info...\"","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_return_single_residue_info(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_single_residue_info('1')\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\n res5 = mol_res_spin.return_single_residue_info('-5')\n\n # Test the data of residue 1.\n self.assertEqual(res1, (1, None))\n\n # Test the data of residue 2.\n self.assertEqual(res2, (2, 'Glu'))\n\n # Test the data of residue 4.\n self.assertEqual(res4, (4, 'Pro'))\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5, (-5, None))","def test_empty_with_filter(multi_mol_system_irregular):\n sequence = \"not empty\"\n processor = dssp.AnnotateResidues(\n \"test\", sequence, molecule_selector=lambda mol: False\n )\n with pytest.raises(ValueError):\n processor.run_system(multi_mol_system_irregular)","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_wrong_length(multi_mol_system_irregular, sequence):\n processor = dssp.AnnotateResidues(\"test\", sequence)\n with pytest.raises(ValueError):\n processor.run_system(multi_mol_system_irregular)","def test_run_loop_success(self):\n found = False\n pyint = Interpreter(limit=15)\n try:\n pyint.run(code=BF_CODE_LOOP_TWICE)\n except SystemExit: \n found = True\n self.assertFalse(found)","def test_return_single_residue_info_fail(self):\n\n # Ask for a few residues.\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')","def test_multi_molecules_cycle(self, multi_mol_system_regular, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n expected = expected * 3\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_regular)\n found = self.sequence_from_system(multi_mol_system_regular, \"test\")\n assert found == expected","def test_single_molecules_cycle_one(self, single_mol_system):\n sequence = \"A\"\n expected = [sequence] * (5 * 3)\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def test_selection():\n pdb_inp = iotbx.pdb.input(source_info=None, lines=pdb_answer_0)\n ncs_obj_phil = ncs.input(\n hierarchy=pdb_inp.construct_hierarchy())\n nrg = ncs_obj_phil.get_ncs_restraints_group_list()\n\n m1 = list(nrg[0].master_iselection)\n c1 = list(nrg[0].copies[0].iselection)\n c2 = list(nrg[0].copies[1].iselection)\n\n assert len(m1) == len(c1) # renumbering\n assert m1 == [0, 1, 2, 3, 4, 5, 6] # 0, 1, X, 3, X, 5, X | 0, 1, 3\n assert c1 == [7, 8, 9, 10, 11, 12, 13] # 7, 8, 9, X, X, 12, X | 4, 5, 7\n assert c2 == [14, 15, 16, 17, 18, 19, 20] # 14, 15, X, 17, X, 19, X | 8, 9, 11\n\n selection1 = flex.size_t([0,1,5,3,100,101])\n selection2 = flex.size_t([0,1,5,3,7,8,9,12,100,101])\n selection3 = flex.size_t([0,1,5,3,7,8,9,12,14,15,19,17,100,101])\n # gone iseqs for selection3: 2,4,6,10,11,13,16,18,20-99\n\n new_nrg = nrg.select(flex.bool(102, selection1))\n # only atoms in master are selected\n mt = list(new_nrg[0].master_iselection)\n c1t = list(new_nrg[0].copies[0].iselection)\n\n assert mt == []\n assert c1t == []\n\n # atoms selected in both master and copies\n new_nrg = nrg.select(flex.bool(102, selection2))\n # only atoms in master are selected\n mt = list(new_nrg[0].master_iselection)\n c1t = list(new_nrg[0].copies[0].iselection)\n\n assert mt == []\n assert c1t == []\n\n new_nrg = nrg.select(flex.bool(102, selection3))\n # only atoms in master are selected\n mt = list(new_nrg[0].master_iselection)\n c1t = list(new_nrg[0].copies[0].iselection)\n c2t = list(new_nrg[0].copies[1].iselection)\n\n assert mt == [0, 1, 3], list(mt)\n assert c1t == [4, 5, 7], list(c1t)\n assert c2t == [8, 9, 11], list(c2t)","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def check_residue(self, chain_id, resid, resname):\n if resname in PTM_lookup.keys():\n return\n else:\n try:\n ref_resname = PTM_reverse_lookup[resname]\n except KeyError:\n # print \"skipping unrecognized residue\", resname\n return\n ptm_dict = PTM_lookup[ref_resname][resname]\n return (chain_id, resid, ref_resname, ptm_dict[\"goto_atom\"], ptm_dict[\"name\"])","def test_empty_system_empty_sequence():\n system = vermouth.system.System()\n sequence = \"\"\n processor = dssp.AnnotateResidues(\"test\", sequence)\n try:\n processor.run_system(system)\n except ValueError:\n pytest.fail(\"Should not have raised a ValueError.\")","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def assignResonanceResidue(resonance, residue):\n\n\n #print 'assignResonanceResidue', makeResonanceGuiName(resonance), residue.seqId\n if residue:\n # we could be setting the residue to None\n if not setAssignmentMolSystem(residue, resonance=resonance):\n return\n \n resonanceSet = resonance.resonanceSet\n if resonanceSet:\n assignNames = set()\n \n for atomSet in resonanceSet.atomSets:\n assignNames.add(atomSet.name)\n \n else:\n assignNames = set(resonance.assignNames)\n \n assignedResidue = getResonanceResidue(resonance)\n \n if assignNames and (assignedResidue is not residue):\n resonance.setAssignNames(assignNames)\n \n if residue:\n atomSets = []\n isotopeCode = resonance.isotopeCode\n if ('HA' in assignNames) and (residue.ccpCode == 'Gly'):\n assignNames.add('HA2')\n assignNames.add('HA3')\n \n for atom in residue.atoms:\n element = atom.chemAtom.elementSymbol\n \n if isotopeCode[-len(element):] != element:\n continue\n \n atomSet = atom.atomSet\n if atomSet:\n if atomSet.name in assignNames:\n if atomSet not in atomSets:\n atomSets.append(atomSet)\n \n if resonanceSet:\n resonanceSet.delete()\n \n if atomSets:\n # might not always find atom sets\n # e.g. if changing residue types\n assignAtomsToRes(atomSets,resonance,None)\n else:\n if resonanceSet:\n resonanceSet.delete()\n #updateResonanceAnnotation(resonance)\n\n if not resonance.resonanceGroup:\n nmrProject = resonance.nmrProject\n spinSystem = None\n molResidue = residue.molResidue\n ccpCode = molResidue.ccpCode\n molType = molResidue.molType\n spinSystems = nmrProject.findAllResonanceGroups(ccpCode=ccpCode,\n molType=molType)\n \n for extantSpinSystem in spinSystems:\n if extantSpinSystem.residue is residue:\n spinSystem = extantSpinSystem\n break\n \n if not spinSystem:\n spinSystem = nmrProject.newResonanceGroup()\n assignSpinSystemResidue(spinSystem,residue)\n \n if resonance not in spinSystem.resonances:\n spinSystem.addResonance(resonance)\n updateResonanceAnnotation(resonance)\n \n else:\n updateResonanceAnnotation(resonance)","def test_RUMI():\r\n\r\n start = 11051\r\n end = 11902\r\n read_poems(start, end)","def test_return_molecule_pipe_fail(self):\n\n # Try to get a molecule from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')","def test_run_molecule(self, single_mol_system):\n sequence = \"ABCDE\"\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def check_for_residue_existance(self):\n if not self.pose.total_residue():\n print \"No pose Loaded.\"\n return False\n\n if not self.current_chain.get() or not self.current_residue.get():\n print \"Chain or residue not set\"\n return False\n\n current_region = self.current_residue.get().split(\":\")\n if len(current_region)>1:\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\n\n\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\n print \"Region not found in pose\"\n return False\n else:\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\n\n print \"Residue not found in pose\"\n return False\n\n #If everythig is good then:\n return True","def test_wrong_length_with_filter(multi_mol_system_irregular, sequence):\n # We exclude the second molecule. The filter excludes it based on the\n # number of nodes, which is 15 because it has 5 residues with 3 nodes\n # each.\n processor = dssp.AnnotateResidues(\n \"test\",\n sequence,\n molecule_selector=lambda mol: len(mol.nodes) != (5 * 3),\n )\n with pytest.raises(ValueError):\n processor.run_system(multi_mol_system_irregular)","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def test_perceive_residues_natoms_mainchain_charged_glutamic_acid(\n self, strict_chirality\n ):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/MainChain_GLH.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def test_empty_system_error():\n system = vermouth.system.System()\n sequence = \"not empty\"\n processor = dssp.AnnotateResidues(\"test\", sequence)\n with pytest.raises(ValueError):\n processor.run_system(system)","def test_setup_explicit_solvation_system():\n with mmtools.utils.temporary_directory() as tmp_dir:\n yaml_script = get_template_script(tmp_dir)\n del yaml_script['experiments']\n exp_builder = ExperimentBuilder(yaml_script)\n output_dir = os.path.dirname(\n exp_builder._db.get_system('hydration-system')[0].position_path)\n\n # Test that output file exists and that it has correct components\n expected_resnames = {'solvent1': set(['TOL', 'WAT']), 'solvent2': set(['TOL'])}\n for phase in expected_resnames:\n found_resnames = set()\n pdb_path = os.path.join(output_dir, phase + '.pdb')\n prmtop_path = os.path.join(output_dir, phase + '.prmtop')\n inpcrd_path = os.path.join(output_dir, phase + '.inpcrd')\n\n with open(pdb_path, 'r') as f:\n for line in f:\n if len(line) > 10 and line[:5] != 'CRYST':\n found_resnames.add(line[17:20])\n\n assert os.path.exists(prmtop_path)\n assert os.path.exists(inpcrd_path)\n assert os.path.getsize(prmtop_path) > 0\n assert os.path.getsize(inpcrd_path) > 0\n assert found_resnames == expected_resnames[phase]","def algorithm_loop(self):","def is_standard_residue(self):\n return False","def test_play_again_no(self):\n # Prepare test\n choice = random.choice(i18n.IN_NO_LIST)\n self.console.out_farewell = MagicMock()\n self.console.input = MagicMock(side_effect=[choice, StopIteration])\n\n # Run test\n self.console.ask_play_again()\n\n # Evaluate test\n calls = [call(FORMAT_NEWLINE_END(i18n.IN_MSG_REPLAY))]\n self.console.input.assert_has_calls(calls)\n self.console.out_farewell.assert_called_once()","def isResidueAssigned(residue):\n\n for atom in residue.atoms:\n if atom.atomSet:\n if atom.atomSet.resonanceSets:\n return True\n \n return False","def test_perceive_residues_natoms_mainchain_arginine(self, strict_chirality):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/MainChain_ARG.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def test_single_molecule(self, single_mol_system, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def test_run_loop_exc(self):\n with self.assertRaises(ExecutionException):\n pyint = Interpreter(limit=1)\n pyint.run(code=BF_CODE_LOOP_TWICE)","def test_return_molecule(self):\n\n # Ask for a few molecules.\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\n\n # Test the data of molecule 1.\n self.assertEqual(mol1.name, 'Ap4Aase')\n\n # Test the data of molecule 2.\n self.assertEqual(mol2.name, 'RNA')","def test_perceive_residues_natoms_mainchain_glutamic_acid(self, strict_chirality):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/MainChain_GLU.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def test_78_continue(self):\n\t\tinput = \"\"\"procedure main(); var x:integer;\n\t\tbegin while(true)do begin\n\t\twith x:integer; do with x:real; do begin\n\t\t\tif (x>0) then continue;\n\t\t\twith x:integer; do if (x=0) then return;\n\t\tend{with} continue; end{while} continue; end\"\"\"\n\t\texpect = \"Continue Not In Loop\"\n\t\tself.assertTrue(TestChecker.test(input,expect,478))","def test_rescore_unmask(self):\r\n module = CapaFactory.create(xml=self.common_shuffle_xml)\r\n get_request_dict = {CapaFactory.input_key(): 'mask_0'}\r\n module.check_problem(get_request_dict)\r\n # On rescore, state/student_answers should use unmasked names\r\n with patch.object(module.runtime, 'track_function') as mock_track_function:\r\n module.rescore_problem()\r\n mock_call = mock_track_function.mock_calls[0]\r\n event_info = mock_call[1][1]\r\n self.assertEquals(mock_call[1][0], 'problem_rescore')\r\n self.assertEquals(event_info['state']['student_answers'][CapaFactory.answer_key()], 'choice_2')\r\n self.assertIsNotNone(event_info['permutation'][CapaFactory.answer_key()])","def is_standard_residue(self):\n return True","def is_standard_residue(self):\n return True","def test_match_right_none():\r\n runmatch(lcode_right_none)","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def residue(self, resnum, chain_id, icode=' ', alt=' ', model_num = 0):\n res = self.struct[model_num][chain_id][(alt, resnum, icode)]\n res.chain_id = chain_id\n return res","def PLAYERSELECTION_LOOP():\n pass","def test_return_spin_pipe_fail(self):\n\n # Try to get a spin from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')","def initResonance(resonance, doMerge=True):\n from ccpnmr.analysis.core.MoleculeBasic import DEFAULT_ISOTOPES\n \n if resonance.isDeleted:\n return\n \n #print 'initResonance', makeResonanceGuiName(resonance)\n resonanceSet = resonance.resonanceSet\n \n if resonance.name == 'r%d' % resonance.serial:\n resonance.setName(None)\n \n if resonanceSet:\n atomSets = tuple(resonanceSet.atomSets)\n atom = atomSets[0].findFirstAtom()\n element = atom.chemAtom.elementSymbol\n if resonance.isotopeCode[-len(element):] != element:\n msg = 'Resonance %d isotope-assignment mismatch: Resetting isotope' \n print msg % resonance.serial\n \n resonance.isotopeCode = DEFAULT_ISOTOPES.get(element, 'unknown')\n getBoundResonances(resonance, recalculate=True, contribs=None) \n \n spinSystem = findSpinSystem(resonance)\n if spinSystem:\n if resonance.resonanceGroup: # same as the spin system\n residue = atom.residue\n \n if spinSystem.residue is not residue:\n #assignSpinSystemResidue(spinSystem,residue)\n \n if doMerge:\n ccpCode = residue.molResidue.ccpCode\n spinSystems = list(resonance.nmrProject.findAllResonanceGroups(residue=residue))\n N = len(spinSystems)\n msg = 'There are %d separate %d%s spin systems. Merge together?'\n if (N > 1) and showOkCancel('Confirm', msg % (N,residue.seqCode,ccpCode)):\n assignSpinSystemResidue(spinSystem,residue) \n \n for spinSystem1 in spinSystems[1:]:\n mergeSpinSystems(spinSystem1,spinSystems[0])\n \n else:\n assignSpinSystemResidue(spinSystem,residue) \n \n else:\n assignSpinSystemResidue(spinSystem,residue) \n \n else:\n addSpinSystemResonance(spinSystem, resonance)\n\n assignResonanceType(resonance, atomSets)\n \n else:\n updateResonanceAnnotation(resonance)\n\n if not resonance.shifts:\n if resonance.peakDimContribs:\n for contrib in resonance.peakDimContribs:\n peakDim = contrib.peakDim\n experiment = peakDim.peak.peakList.dataSource.experiment\n \n if experiment.shiftList is None:\n shiftList = resonance.nmrProject.findFirstMeasurementList(className='ShiftList')\n if shiftList is None:\n shiftList = resonance.nmrProject.newShiftList(unit='ppm')\n experiment.setShiftList( shiftList )\n \n updateResonShift(resonance,peakDim)","def check_termination(self) :\n\t\trc_all = self.rc1[-1]+self.rc2[-1]\n\t\tif rc_all == 0 and self.ssep[-1] < self.tol \\\n\t\t\t and self.ssed[-1] < self.tol : \n\t\t\tself.converged = True\n\t\t\tself.continueLoop = False \n\t\n\t\tif self.loopiter >= self.maxiter : \n\t\t\tself.maxiter_exceeded = True\n\t\t\tself.converged = False\n\t\t\tself.continueLoop = False\n\t\n\t# Check any obvious SSE inconsistencies\n\t\tif self.ssep[-1] > self.sseMax or self.ssed[-1] > self.sseMax : \n\t\t\tself.continueLoop = False","def test_case_01_right_scalene(self):\n self.__assert_equals_test_case(self.yield_right_scalene_triangles(), 'Right Scalene Triangle')","def _select_arm(self):\n pass","def test_rescoring_option_problem(self):\r\n # get descriptor:\r\n problem_url_name = 'H1P1'\r\n self.define_option_problem(problem_url_name)\r\n location = InstructorTaskModuleTestCase.problem_location(problem_url_name)\r\n descriptor = self.module_store.get_item(location)\r\n\r\n # first store answers for each of the separate users:\r\n self.submit_student_answer('u1', problem_url_name, [OPTION_1, OPTION_1])\r\n self.submit_student_answer('u2', problem_url_name, [OPTION_1, OPTION_2])\r\n self.submit_student_answer('u3', problem_url_name, [OPTION_2, OPTION_1])\r\n self.submit_student_answer('u4', problem_url_name, [OPTION_2, OPTION_2])\r\n\r\n self.check_state('u1', descriptor, 2, 2, 1)\r\n self.check_state('u2', descriptor, 1, 2, 1)\r\n self.check_state('u3', descriptor, 1, 2, 1)\r\n self.check_state('u4', descriptor, 0, 2, 1)\r\n\r\n # update the data in the problem definition\r\n self.redefine_option_problem(problem_url_name)\r\n # confirm that simply rendering the problem again does not result in a change\r\n # in the grade:\r\n self.render_problem('u1', problem_url_name)\r\n self.check_state('u1', descriptor, 2, 2, 1)\r\n\r\n # rescore the problem for only one student -- only that student's grade should change:\r\n self.submit_rescore_one_student_answer('instructor', problem_url_name, User.objects.get(username='u1'))\r\n self.check_state('u1', descriptor, 0, 2, 1)\r\n self.check_state('u2', descriptor, 1, 2, 1)\r\n self.check_state('u3', descriptor, 1, 2, 1)\r\n self.check_state('u4', descriptor, 0, 2, 1)\r\n\r\n # rescore the problem for all students\r\n self.submit_rescore_all_student_answers('instructor', problem_url_name)\r\n self.check_state('u1', descriptor, 0, 2, 1)\r\n self.check_state('u2', descriptor, 1, 2, 1)\r\n self.check_state('u3', descriptor, 1, 2, 1)\r\n self.check_state('u4', descriptor, 2, 2, 1)","def test_pure_prisoners_dilemma(_):\n game = gamegen.sym_2p2s_game(2, 0, 3, 1) # prisoners dilemma\n eqm = [0, 2]\n\n assert (\n regret.pure_strategy_regret(game, eqm) == 0\n ), \"Known equilibrium was not zero regret\"","def select_perturbation_residues(molecule):\n # Validte the length of the molecule\n validate_molecule_length(molecule)\n # Set the maximum allowed perturbation numbers\n maxNum = 3\n # Select a random number between 1 and maxNum\n ranNum = random.randint(1, maxNum)\n # Define the perturbed list to hold the perturbed residue name\n perturbed = []\n count = 0\n while count < ranNum:\n # Random select a residue number in the molecule \n index = random.randint(1, len(molecule))\n perturbed.append([molecule.name, index, molecule[index].name])\n count += 1\n\n return perturbed","def test_special_RR(self):\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, -0.1).to_matrix(), \"RR\", {})\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, 0.2).to_matrix(), \"RR\", {\"r\": 2})\n self.check_oneq_special_cases(U3Gate(-np.pi, 0.2, 0.0).to_matrix(), \"RR\", {\"r\": 1})\n self.check_oneq_special_cases(U3Gate(np.pi, 0.0, 0.2).to_matrix(), \"RR\", {\"r\": 1})\n self.check_oneq_special_cases(U3Gate(0.1, 0.2, 0.3).to_matrix(), \"RR\", {\"r\": 2})","def restrict_non_nbrs_from_repacking(pose, res, task, pack_radius):\n\n center = pose.residue( res ).xyz( pose.residue( res ).nbr_atom() )\n print( \"Res: pack radius: \"+repr(pack_radius) )\n for i in range(1, pose.total_residue() + 1):\n # only pack the mutating residue and any within the pack_radius\n if i == res: continue\n\n nbr = pose.residue( i ).xyz( pose.residue( i ).nbr_atom() )\n dist = nbr.distance(center)\n if dist > pack_radius:\n task.nonconst_residue_task(i).prevent_repacking()\n else:\n task.nonconst_residue_task(i).restrict_to_repacking()\n\n #print task\n return task","def test_match_left_none():\r\n runmatch(lcode_left_none)","def test_count_spins_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Test for the error.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.count_spins)","def selectResN(self):\n\n\t\tif len(self.resn) == 0:\n\t\t\treturn\n\n\t\ttmplist = []\n\t\tfor atom in self.atomlist:\n\t\t\tfound = False\n\t\t\tfor resn in self.resn:\n\t\t\t\tif atom.parentResidue.name == resn:\n\t\t\t\t\tfound = True\n\t\t\t\t\tbreak\n\n\t\t\tif found and not self.invresn:\n\t\t\t\ttmplist.append(atom)\n\t\t\tif not found and self.invresn:\n\t\t\t\ttmplist.append(atom)\n\n\t\tself.atomlist = tmplist","def test_wrong_turn_results_in_inf_loop():\n\t\n\t# chceme vystup v citelny podobe pro PIPE\n\tcp = subprocess.run([sys.executable, 'game.py'],\n\t\t\t\t\t\t# misto encoding, kvuli Python3.5, pouziju univ_new\n\t\t\t\t\t\tuniversal_newlines=True,\n\t\t\t\t\t\tstdout=subprocess.PIPE,\n\t\t\t\t\t\tinput='doggie\\nrock\\n',\n\t\t\t\t\t\tcheck=True)\n\n\tassert cp.stdout.count('Choice: rock, scissors, paper: ') == 2 # 2x True value","def test_remain():\r\n global pickno\r\n #Change pick number to the total amount of balls\r\n # Ex. If we have 3 balls remaining the user cannot pick 4\r\n if total <= 4:\r\n pickno = total","def test_one_arm(self):\n bandit = self.bandit_class(self.one_arm_test_case)\n self._test_one_arm(bandit)","def test_match_or_none2():\r\n runmatch(lcode)","def test_pol_id_range(self):\n pol = '0~1'\n ref_idx = []\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\n self.assertEqual(self.res,None,\n msg='Any error occurred during calibration')\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)","def test_recomb(self):\n sol1, sol2 = [0,0,0,0],[1,1,1,1]\n hot_regions = [0,0,0,1] ##NOTE: sum(hot_regions) shouls always be 1\n rec_events = 1\n sol = list(d.recombine(sol1,sol2,rec_events,hot_regions))\n print(f\"recomb sol: {sol}\")\n self.assertTrue( (sol == [0,0,0,1]) or (sol == [1,1,1,0]) )","def selectResI(self):\n\n\t\tif len(self.resi) == 0:\t\n\t\t\treturn\n\n\t\ttmplist = []\n\t\tfor atom in self.atomlist:\n\t\t\tfound = False\n\t\t\tfor resi in self.resi:\n\t\t\t\tif int(atom.parentResidue.file_id) == resi:\n\t\t\t\t\tfound = True\n\t\t\t\t\tbreak\n\n\t\t\tif found and not self.invresi:\n\t\t\t\ttmplist.append(atom)\n\t\t\tif not found and self.invresi:\n\t\t\t\ttmplist.append(atom)\n\n\t\tself.atomlist = tmplist","def test_three_arms_one_unsampled_arm(self):\n self._test_three_arms_one_unsampled_arm()","def test_match_or_none():\r\n runmatch(lcode)","def test_select_pdb_conformation(self):\n with mmtools.utils.temporary_directory() as tmp_dir:\n yaml_content = \"\"\"\n ---\n options:\n output_dir: {}\n setup_dir: .\n molecules:\n selected:\n filepath: {}\n leap: {{parameters: oldff/leaprc.ff14SB}}\n select: 1\n \"\"\".format(tmp_dir, self.pdb_path)\n yaml_content = textwrap.dedent(yaml_content)\n exp_builder = ExperimentBuilder(yaml_content)\n\n # The molecule now is neither set up nor processed\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\n assert is_setup is False\n assert is_processed is False\n\n # The setup of the molecule must isolate the frame in a single-frame PDB\n exp_builder._db._setup_molecules('selected')\n selected_pdb_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\n 'selected', 'selected.pdb')\n assert os.path.exists(os.path.join(selected_pdb_path))\n assert os.path.getsize(os.path.join(selected_pdb_path)) > 0\n\n # The positions must be the ones of the second frame\n selected_pdb = PDBFile(selected_pdb_path)\n selected_pos = selected_pdb.getPositions(asNumpy=True)\n second_pos = PDBFile(self.pdb_path).getPositions(asNumpy=True, frame=1)\n assert selected_pdb.getNumFrames() == 1\n assert (selected_pos == second_pos).all()\n\n # The description of the molecule is now updated\n assert os.path.normpath(exp_builder._db.molecules['selected']['filepath']) == selected_pdb_path\n\n # The molecule now both set up and processed\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\n assert is_setup is True\n assert is_processed is True\n\n # A new instance of ExperimentBuilder is able to resume with correct molecule\n exp_builder = ExperimentBuilder(yaml_content)\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\n assert is_setup is True\n assert is_processed is True","def test_no_specification_error():\n try:\n bad_arm = survey.get_spiral_slice()\n except SyntaxError:\n assert True\n else:\n assert False","def test_call_default_params_reversed_seq(self):\r\n\r\n app = Usearch610DeNovoOtuPicker(\r\n params={'save_intermediate_files': False,\r\n 'output_dir': self.output_dir,\r\n 'remove_usearch_logs': True\r\n })\r\n\r\n obs_clusters = app(self.tmp_seq_filepath_97perc_id_rc)\r\n\r\n # RC seq should fall into its own cluster\r\n expected_clusters = [set(['usearch_ecoli_seq',\r\n 'usearch_ecoli_seq_1bp_change']),\r\n set(['usearch_ecoli_seq_2bp_change_rc'])]\r\n\r\n self.assertEqual(len(obs_clusters), 2)\r\n for result in obs_clusters:\r\n self.assertTrue(set(obs_clusters[result]) in expected_clusters)","def check_for_barrierless_reaction(self):\n # Check for barrierless reaction leading to new graphs\n if self.rc_opt_system_name not in self.systems: # Skip if already done\n print(\"Running Reactive Complex Optimization\")\n print(\"Settings:\")\n print(self.settings[self.rc_opt_system_name], \"\\n\")\n self.systems, success = self.observed_readuct_call(\n 'run_opt_task', self.systems, [self.rc_key], **self.settings[self.rc_opt_system_name]\n )\n self.throw_if_not_successful(\n success,\n self.systems,\n [self.rc_opt_system_name],\n [],\n \"Reactive complex optimization failed.\\n\",\n )\n _, rc_opt_graph, _, _, rc_opt_decision_lists = \\\n self.get_graph_charges_multiplicities(self.rc_opt_system_name, sum(self.start_charges))\n\n if not masm.JsonSerialization.equal_molecules(self.start_graph, rc_opt_graph):\n return rc_opt_graph, rc_opt_decision_lists\n return None, None","def test_perceive_residues_natoms_t4(self, strict_chirality):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/T4-protein.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def test_is_in_ring(self):\n molecule = Molecule.from_smiles(\"c1ccccc1\")\n\n for atom in molecule.atoms:\n if atom.atomic_number == 6:\n assert atom.is_in_ring()\n\n for bond in molecule.bonds:\n if 1 in (bond.atom1.atomic_number, bond.atom2.atomic_number):\n continue\n assert bond.is_in_ring()","def test_specific_qubit_pauli_error_gate_100percent(self):\n qr = QuantumRegister(2, 'qr')\n cr = ClassicalRegister(2, 'cr')\n circuit = QuantumCircuit(qr, cr)\n circuit.iden(qr)\n circuit.barrier(qr)\n circuit.measure(qr, cr)\n backend = QasmSimulator()\n shots = 100\n # test noise model\n error = pauli_error([('X', 1)])\n noise_model = NoiseModel()\n noise_model.add_quantum_error(error, 'id', [1])\n # Execute\n target = {'0x2': shots}\n circuit = transpile(circuit, basis_gates=noise_model.basis_gates)\n qobj = assemble([circuit], backend, shots=shots)\n result = backend.run(qobj, noise_model=noise_model).result()\n self.is_completed(result)\n self.compare_counts(result, [circuit], [target], delta=0)","def mutate_residue(pose, mutant_position, mutant_aa,\n pack_radius = 0.0, pack_scorefxn = '' ):\n #### a MutateResidue Mover exists similar to this except it does not pack\n #### the area around the mutant residue (no pack_radius feature)\n #mutator = MutateResidue(mutant_position, mutant_aa)\n #mutator.apply(test_pose)\n\n if pose.is_fullatom() == False:\n IOError( 'mutate_residue only works with fullatom poses' )\n\n\n # create a standard scorefxn by default\n if not pack_scorefxn:\n pack_scorefxn = rosetta.core.scoring.get_score_function()\n\n task = pyrosetta.standard_packer_task(pose)\n\n # the Vector1 of booleans (a specific object) is needed for specifying the\n # mutation, this demonstrates another more direct method of setting\n # PackerTask options for design\n aa_bool = rosetta.utility.vector1_bool()\n # PyRosetta uses several ways of tracking amino acids (ResidueTypes)\n # the numbers 1-20 correspond individually to the 20 proteogenic amino acids\n # aa_from_oneletter returns the integer representation of an amino acid\n # from its one letter code\n # convert mutant_aa to its integer representation\n mutant_aa = rosetta.core.chemical.aa_from_oneletter_code(mutant_aa)\n\n # mutation is performed by using a PackerTask with only the mutant\n # amino acid available during design\n # to do this, construct a Vector1 of booleans indicating which amino acid\n # (by its numerical designation, see above) to allow\n for i in range(1, 21):\n # in Python, logical expression are evaluated with priority, thus the\n # line below appends to aa_bool the truth (True or False) of the\n # statement i == mutant_aa\n aa_bool.append( i == int(mutant_aa) )\n\n # modify the mutating residue's assignment in the PackerTask using the\n # Vector1 of booleans across the proteogenic amino acids\n task.nonconst_residue_task(mutant_position\n ).restrict_absent_canonical_aas(aa_bool)\n\n # prevent residues from packing by setting the per-residue \"options\" of\n # the PackerTask\n restrict_non_nbrs_from_repacking(pose, mutant_position, task, pack_radius)\n\n # apply the mutation and pack nearby residues\n #print task\n packer = rosetta.protocols.simple_moves.PackRotamersMover(pack_scorefxn, task)\n packer.apply(pose)","def test_ok_mm_primer(self):\r\n primers = ['AAAA', 'GGGG']\r\n self.assertEqual(ok_mm_primer('AAAA', primers, 0), True)\r\n self.assertEqual(ok_mm_primer('AAAA', primers, 3), True)\r\n self.assertEqual(ok_mm_primer('CCCC', primers, 0), False)\r\n self.assertEqual(ok_mm_primer('CCCA', primers, 3), True)\r\n self.assertEqual(ok_mm_primer('CCCA', primers, 2), False)\r\n self.assertEqual(ok_mm_primer('CCGG', primers, 2), True)\r\n self.assertEqual(ok_mm_primer('CCGA', primers, 2), False)","def test_parameterize_mol_missing_stereo_rdkit(self, force_field):\n toolkit_registry = ToolkitRegistry(\n toolkit_precedence=[RDKitToolkitWrapper, AmberToolsToolkitWrapper]\n )\n\n molecule = Molecule.from_smiles(\"CC1CCC(=O)O1\", allow_undefined_stereo=True)\n topology = Topology.from_molecules([molecule])\n\n force_field.create_openmm_system(\n topology,\n toolkit_registry=toolkit_registry,\n )","def _loop_raw(raw):\n raise NotImplemented"],"string":"[\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_residue_loop(self):\\n\\n # Loop over the residues.\\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\\n # Test the selection.\\n self.assertEqual(res.num, 2)\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)\",\n \"def test_residue_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for residue in mol_res_spin.residue_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_spin_loop_no_selection(self):\\n\\n # Spin data.\\n select = [0, 1, 0, 0, 1, 1, 0, 1]\\n name = ['NH', 'NH', None, 'C8', 'N5', 'C8', 'N5', '2H']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 8)\",\n \"def test_molecule_loop_no_selection(self):\\n\\n # Molecule data.\\n name = ['Ap4Aase', 'RNA']\\n\\n # Loop over the molecules.\\n i = 0\\n for mol in mol_res_spin.molecule_loop():\\n # Test the molecule names.\\n self.assertEqual(mol.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_spin_loop(self):\\n\\n # Spin data.\\n select = [1, 0]\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, 'N5')\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 2)\",\n \"def test_molecule_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for molecule in mol_res_spin.molecule_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_boolean_and_selection(self):\\n\\n # The selection loop:\\n sel = list(mol_res_spin.residue_loop(\\\"#Ap4Aase:4 & :Pro\\\"))\\n\\n # Test:\\n self.assertEqual(len(sel), 1)\\n for res in sel:\\n self.assert_(res.name == \\\"Pro\\\" and res.num == 4)\",\n \"def test_molecule_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the molecules.\\n i = 0\\n for molecule in mol_res_spin.molecule_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_spin_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for spin in mol_res_spin.spin_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_return_residue(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_residue(':1')\\n res2 = mol_res_spin.return_residue(selection=':2')\\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1.num, 1)\\n self.assertEqual(res1.name, None)\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2.num, 2)\\n self.assertEqual(res2.name, 'Glu')\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4.num, 4)\\n self.assertEqual(res4.name, 'Pro')\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5.num, -5)\\n self.assertEqual(res5.name, None)\\n self.assertEqual(res5.spin[1].name, 'N5')\",\n \"def test_boolean_complex_selection(self):\\n\\n # The residue selection loop.\\n sel = list(mol_res_spin.residue_loop(\\\"#Ap4Aase:4 & :Pro | #RNA\\\"))\\n\\n # Residue names and numbers.\\n names = ['Pro', None, None]\\n numbers = [4, -5, -4]\\n\\n # The residues.\\n self.assertEqual(len(sel), 3)\\n for i in range(3):\\n self.assertEqual(sel[i].name, names[i])\\n self.assertEqual(sel[i].num, numbers[i])\",\n \"def test_spin_loop_multiatom(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@NH|@N5'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_run_molecule_not_selected(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\", sequence, molecule_selector=lambda mol: False\\n )\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert vermouth.utils.are_all_equal(found)\\n assert found[0] is None\",\n \"def test_return_residue_pipe_fail(self):\\n\\n # Try to get a residue from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')\",\n \"def test_molecule_loop(self):\\n\\n # Loop over the molecules.\\n for mol in mol_res_spin.molecule_loop('#RNA'):\\n # Test the molecule name.\\n self.assertEqual(mol.name, 'RNA')\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)\",\n \"def test_spin_loop_wildcard(self):\\n\\n # Spin data.\\n select = [0, 1, 1, 0]\\n name = ['NH', 'NH', 'N5', 'N5']\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop('@N*'):\\n # Test the selection.\\n self.assertEqual(spin.select, select[i])\\n\\n # Test the spin names.\\n self.assertEqual(spin.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 4)\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def ROOMSELECTION_LOOP():\\n pass\",\n \"def check_residue_callback(self):\\n\\n if not self.check_for_residue_existance():\\n return\\n\\n self.listbox_current_designs.delete(0, END)\\n self.current_residueFull = self.current_residue.get().split(\\\":\\\")\\n\\n if len(self.current_residueFull) > 1:\\n self.listbox_restypes.delete(9)\\n self.listbox_restypes.insert(9, \\\"Conserved\\\")\\n else:\\n res = self.current_residueFull[0] +\\\":\\\"+self.current_chain.get()\\n #print res\\n if not self.pose.total_residue():\\n return\\n\\n resType = self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get()))\\n try:\\n resName = self.pose.residue(resType).name()\\n except PyRosettaException:\\n print \\\"Residue does not exist in PDB...\\\"\\n return\\n\\n\\n self.current_residue_name_full.set(resName)\\n three_letter_name = resName.split(\\\"_\\\")[0]; #Fix for Rosetta designated chain endings, His_d\\n self.current_residue_name.set(resName)\\n\\n #Fix for not having data for certain residue types:\\n try:\\n self.design_accessible_sa.set(self.residue_definitions.resinfo[three_letter_name][0])\\n self.design_relative_mutability.set(self.residue_definitions.resinfo[three_letter_name][1])\\n self.design_surface_probability.set(self.residue_definitions.resinfo[three_letter_name][2])\\n except KeyError:\\n print \\\"No Data for restype\\\"\\n self.design_accessible_sa.set(\\\"\\\")\\n self.design_relative_mutability.set(\\\"\\\")\\n self.design_surface_probability.set(\\\"\\\")\\n\\n con = \\\"Conserved:\\\" +three_letter_name\\n self.listbox_restypes.delete(9)\\n self.listbox_restypes.insert(9, con)\\n if self.DesignDic.has_key(res):\\n for residues in self.DesignDic[res]:\\n self.listbox_current_designs.insert(END, residues)\",\n \"def fixme_test_boolean_parenthesis_selection(self):\\n\\n # The selection loop:\\n sel = list(mol_res_spin.residue_loop(\\\"(#Ap4Aase & :Pro) | (#RNA & :-4)\\\"))\\n\\n # Test:\\n self.assertEqual(len(sel), 2)\\n for res in sel:\\n self.assert_(res.num in [-4, 4])\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_multi_molecules_cycle_one(self, multi_mol_system_irregular):\\n sequence = \\\"A\\\"\\n expected = [sequence] * (15 * 3)\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_irregular)\\n found = self.sequence_from_system(multi_mol_system_irregular, \\\"test\\\")\\n assert found == expected\",\n \"def nextRes(self):\\n\\n self.current_residueFull = self.current_residue.get().split(\\\":\\\")\\n if len(self.current_residueFull) < 2:\\n res = int(self.current_residue.get())+1\\n self.current_residue.set(res)\\n self.check_residue_callback()\\n else:\\n print \\\"Please Change selection to get info...\\\"\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_return_single_residue_info(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_single_residue_info('1')\\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\\n res5 = mol_res_spin.return_single_residue_info('-5')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1, (1, None))\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2, (2, 'Glu'))\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4, (4, 'Pro'))\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5, (-5, None))\",\n \"def test_empty_with_filter(multi_mol_system_irregular):\\n sequence = \\\"not empty\\\"\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\", sequence, molecule_selector=lambda mol: False\\n )\\n with pytest.raises(ValueError):\\n processor.run_system(multi_mol_system_irregular)\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_wrong_length(multi_mol_system_irregular, sequence):\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n with pytest.raises(ValueError):\\n processor.run_system(multi_mol_system_irregular)\",\n \"def test_run_loop_success(self):\\n found = False\\n pyint = Interpreter(limit=15)\\n try:\\n pyint.run(code=BF_CODE_LOOP_TWICE)\\n except SystemExit: \\n found = True\\n self.assertFalse(found)\",\n \"def test_return_single_residue_info_fail(self):\\n\\n # Ask for a few residues.\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')\",\n \"def test_multi_molecules_cycle(self, multi_mol_system_regular, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n expected = expected * 3\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_regular)\\n found = self.sequence_from_system(multi_mol_system_regular, \\\"test\\\")\\n assert found == expected\",\n \"def test_single_molecules_cycle_one(self, single_mol_system):\\n sequence = \\\"A\\\"\\n expected = [sequence] * (5 * 3)\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def test_selection():\\n pdb_inp = iotbx.pdb.input(source_info=None, lines=pdb_answer_0)\\n ncs_obj_phil = ncs.input(\\n hierarchy=pdb_inp.construct_hierarchy())\\n nrg = ncs_obj_phil.get_ncs_restraints_group_list()\\n\\n m1 = list(nrg[0].master_iselection)\\n c1 = list(nrg[0].copies[0].iselection)\\n c2 = list(nrg[0].copies[1].iselection)\\n\\n assert len(m1) == len(c1) # renumbering\\n assert m1 == [0, 1, 2, 3, 4, 5, 6] # 0, 1, X, 3, X, 5, X | 0, 1, 3\\n assert c1 == [7, 8, 9, 10, 11, 12, 13] # 7, 8, 9, X, X, 12, X | 4, 5, 7\\n assert c2 == [14, 15, 16, 17, 18, 19, 20] # 14, 15, X, 17, X, 19, X | 8, 9, 11\\n\\n selection1 = flex.size_t([0,1,5,3,100,101])\\n selection2 = flex.size_t([0,1,5,3,7,8,9,12,100,101])\\n selection3 = flex.size_t([0,1,5,3,7,8,9,12,14,15,19,17,100,101])\\n # gone iseqs for selection3: 2,4,6,10,11,13,16,18,20-99\\n\\n new_nrg = nrg.select(flex.bool(102, selection1))\\n # only atoms in master are selected\\n mt = list(new_nrg[0].master_iselection)\\n c1t = list(new_nrg[0].copies[0].iselection)\\n\\n assert mt == []\\n assert c1t == []\\n\\n # atoms selected in both master and copies\\n new_nrg = nrg.select(flex.bool(102, selection2))\\n # only atoms in master are selected\\n mt = list(new_nrg[0].master_iselection)\\n c1t = list(new_nrg[0].copies[0].iselection)\\n\\n assert mt == []\\n assert c1t == []\\n\\n new_nrg = nrg.select(flex.bool(102, selection3))\\n # only atoms in master are selected\\n mt = list(new_nrg[0].master_iselection)\\n c1t = list(new_nrg[0].copies[0].iselection)\\n c2t = list(new_nrg[0].copies[1].iselection)\\n\\n assert mt == [0, 1, 3], list(mt)\\n assert c1t == [4, 5, 7], list(c1t)\\n assert c2t == [8, 9, 11], list(c2t)\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def check_residue(self, chain_id, resid, resname):\\n if resname in PTM_lookup.keys():\\n return\\n else:\\n try:\\n ref_resname = PTM_reverse_lookup[resname]\\n except KeyError:\\n # print \\\"skipping unrecognized residue\\\", resname\\n return\\n ptm_dict = PTM_lookup[ref_resname][resname]\\n return (chain_id, resid, ref_resname, ptm_dict[\\\"goto_atom\\\"], ptm_dict[\\\"name\\\"])\",\n \"def test_empty_system_empty_sequence():\\n system = vermouth.system.System()\\n sequence = \\\"\\\"\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n try:\\n processor.run_system(system)\\n except ValueError:\\n pytest.fail(\\\"Should not have raised a ValueError.\\\")\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def assignResonanceResidue(resonance, residue):\\n\\n\\n #print 'assignResonanceResidue', makeResonanceGuiName(resonance), residue.seqId\\n if residue:\\n # we could be setting the residue to None\\n if not setAssignmentMolSystem(residue, resonance=resonance):\\n return\\n \\n resonanceSet = resonance.resonanceSet\\n if resonanceSet:\\n assignNames = set()\\n \\n for atomSet in resonanceSet.atomSets:\\n assignNames.add(atomSet.name)\\n \\n else:\\n assignNames = set(resonance.assignNames)\\n \\n assignedResidue = getResonanceResidue(resonance)\\n \\n if assignNames and (assignedResidue is not residue):\\n resonance.setAssignNames(assignNames)\\n \\n if residue:\\n atomSets = []\\n isotopeCode = resonance.isotopeCode\\n if ('HA' in assignNames) and (residue.ccpCode == 'Gly'):\\n assignNames.add('HA2')\\n assignNames.add('HA3')\\n \\n for atom in residue.atoms:\\n element = atom.chemAtom.elementSymbol\\n \\n if isotopeCode[-len(element):] != element:\\n continue\\n \\n atomSet = atom.atomSet\\n if atomSet:\\n if atomSet.name in assignNames:\\n if atomSet not in atomSets:\\n atomSets.append(atomSet)\\n \\n if resonanceSet:\\n resonanceSet.delete()\\n \\n if atomSets:\\n # might not always find atom sets\\n # e.g. if changing residue types\\n assignAtomsToRes(atomSets,resonance,None)\\n else:\\n if resonanceSet:\\n resonanceSet.delete()\\n #updateResonanceAnnotation(resonance)\\n\\n if not resonance.resonanceGroup:\\n nmrProject = resonance.nmrProject\\n spinSystem = None\\n molResidue = residue.molResidue\\n ccpCode = molResidue.ccpCode\\n molType = molResidue.molType\\n spinSystems = nmrProject.findAllResonanceGroups(ccpCode=ccpCode,\\n molType=molType)\\n \\n for extantSpinSystem in spinSystems:\\n if extantSpinSystem.residue is residue:\\n spinSystem = extantSpinSystem\\n break\\n \\n if not spinSystem:\\n spinSystem = nmrProject.newResonanceGroup()\\n assignSpinSystemResidue(spinSystem,residue)\\n \\n if resonance not in spinSystem.resonances:\\n spinSystem.addResonance(resonance)\\n updateResonanceAnnotation(resonance)\\n \\n else:\\n updateResonanceAnnotation(resonance)\",\n \"def test_RUMI():\\r\\n\\r\\n start = 11051\\r\\n end = 11902\\r\\n read_poems(start, end)\",\n \"def test_return_molecule_pipe_fail(self):\\n\\n # Try to get a molecule from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')\",\n \"def test_run_molecule(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def check_for_residue_existance(self):\\n if not self.pose.total_residue():\\n print \\\"No pose Loaded.\\\"\\n return False\\n\\n if not self.current_chain.get() or not self.current_residue.get():\\n print \\\"Chain or residue not set\\\"\\n return False\\n\\n current_region = self.current_residue.get().split(\\\":\\\")\\n if len(current_region)>1:\\n ResStart = int(current_region[0]); ResEnd = int(self.current_region[1])\\n\\n\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResStart)==0 or self.pose.pdb_info().pdb2pose(self.current_chain.get(), ResEnd)==0:\\n print \\\"Region not found in pose\\\"\\n return False\\n else:\\n if self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get())) ==0:\\n\\n print \\\"Residue not found in pose\\\"\\n return False\\n\\n #If everythig is good then:\\n return True\",\n \"def test_wrong_length_with_filter(multi_mol_system_irregular, sequence):\\n # We exclude the second molecule. The filter excludes it based on the\\n # number of nodes, which is 15 because it has 5 residues with 3 nodes\\n # each.\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\",\\n sequence,\\n molecule_selector=lambda mol: len(mol.nodes) != (5 * 3),\\n )\\n with pytest.raises(ValueError):\\n processor.run_system(multi_mol_system_irregular)\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def test_perceive_residues_natoms_mainchain_charged_glutamic_acid(\\n self, strict_chirality\\n ):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/MainChain_GLH.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def test_empty_system_error():\\n system = vermouth.system.System()\\n sequence = \\\"not empty\\\"\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n with pytest.raises(ValueError):\\n processor.run_system(system)\",\n \"def test_setup_explicit_solvation_system():\\n with mmtools.utils.temporary_directory() as tmp_dir:\\n yaml_script = get_template_script(tmp_dir)\\n del yaml_script['experiments']\\n exp_builder = ExperimentBuilder(yaml_script)\\n output_dir = os.path.dirname(\\n exp_builder._db.get_system('hydration-system')[0].position_path)\\n\\n # Test that output file exists and that it has correct components\\n expected_resnames = {'solvent1': set(['TOL', 'WAT']), 'solvent2': set(['TOL'])}\\n for phase in expected_resnames:\\n found_resnames = set()\\n pdb_path = os.path.join(output_dir, phase + '.pdb')\\n prmtop_path = os.path.join(output_dir, phase + '.prmtop')\\n inpcrd_path = os.path.join(output_dir, phase + '.inpcrd')\\n\\n with open(pdb_path, 'r') as f:\\n for line in f:\\n if len(line) > 10 and line[:5] != 'CRYST':\\n found_resnames.add(line[17:20])\\n\\n assert os.path.exists(prmtop_path)\\n assert os.path.exists(inpcrd_path)\\n assert os.path.getsize(prmtop_path) > 0\\n assert os.path.getsize(inpcrd_path) > 0\\n assert found_resnames == expected_resnames[phase]\",\n \"def algorithm_loop(self):\",\n \"def is_standard_residue(self):\\n return False\",\n \"def test_play_again_no(self):\\n # Prepare test\\n choice = random.choice(i18n.IN_NO_LIST)\\n self.console.out_farewell = MagicMock()\\n self.console.input = MagicMock(side_effect=[choice, StopIteration])\\n\\n # Run test\\n self.console.ask_play_again()\\n\\n # Evaluate test\\n calls = [call(FORMAT_NEWLINE_END(i18n.IN_MSG_REPLAY))]\\n self.console.input.assert_has_calls(calls)\\n self.console.out_farewell.assert_called_once()\",\n \"def isResidueAssigned(residue):\\n\\n for atom in residue.atoms:\\n if atom.atomSet:\\n if atom.atomSet.resonanceSets:\\n return True\\n \\n return False\",\n \"def test_perceive_residues_natoms_mainchain_arginine(self, strict_chirality):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/MainChain_ARG.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def test_single_molecule(self, single_mol_system, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def test_run_loop_exc(self):\\n with self.assertRaises(ExecutionException):\\n pyint = Interpreter(limit=1)\\n pyint.run(code=BF_CODE_LOOP_TWICE)\",\n \"def test_return_molecule(self):\\n\\n # Ask for a few molecules.\\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\\n\\n # Test the data of molecule 1.\\n self.assertEqual(mol1.name, 'Ap4Aase')\\n\\n # Test the data of molecule 2.\\n self.assertEqual(mol2.name, 'RNA')\",\n \"def test_perceive_residues_natoms_mainchain_glutamic_acid(self, strict_chirality):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/MainChain_GLU.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def test_78_continue(self):\\n\\t\\tinput = \\\"\\\"\\\"procedure main(); var x:integer;\\n\\t\\tbegin while(true)do begin\\n\\t\\twith x:integer; do with x:real; do begin\\n\\t\\t\\tif (x>0) then continue;\\n\\t\\t\\twith x:integer; do if (x=0) then return;\\n\\t\\tend{with} continue; end{while} continue; end\\\"\\\"\\\"\\n\\t\\texpect = \\\"Continue Not In Loop\\\"\\n\\t\\tself.assertTrue(TestChecker.test(input,expect,478))\",\n \"def test_rescore_unmask(self):\\r\\n module = CapaFactory.create(xml=self.common_shuffle_xml)\\r\\n get_request_dict = {CapaFactory.input_key(): 'mask_0'}\\r\\n module.check_problem(get_request_dict)\\r\\n # On rescore, state/student_answers should use unmasked names\\r\\n with patch.object(module.runtime, 'track_function') as mock_track_function:\\r\\n module.rescore_problem()\\r\\n mock_call = mock_track_function.mock_calls[0]\\r\\n event_info = mock_call[1][1]\\r\\n self.assertEquals(mock_call[1][0], 'problem_rescore')\\r\\n self.assertEquals(event_info['state']['student_answers'][CapaFactory.answer_key()], 'choice_2')\\r\\n self.assertIsNotNone(event_info['permutation'][CapaFactory.answer_key()])\",\n \"def is_standard_residue(self):\\n return True\",\n \"def is_standard_residue(self):\\n return True\",\n \"def test_match_right_none():\\r\\n runmatch(lcode_right_none)\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def residue(self, resnum, chain_id, icode=' ', alt=' ', model_num = 0):\\n res = self.struct[model_num][chain_id][(alt, resnum, icode)]\\n res.chain_id = chain_id\\n return res\",\n \"def PLAYERSELECTION_LOOP():\\n pass\",\n \"def test_return_spin_pipe_fail(self):\\n\\n # Try to get a spin from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')\",\n \"def initResonance(resonance, doMerge=True):\\n from ccpnmr.analysis.core.MoleculeBasic import DEFAULT_ISOTOPES\\n \\n if resonance.isDeleted:\\n return\\n \\n #print 'initResonance', makeResonanceGuiName(resonance)\\n resonanceSet = resonance.resonanceSet\\n \\n if resonance.name == 'r%d' % resonance.serial:\\n resonance.setName(None)\\n \\n if resonanceSet:\\n atomSets = tuple(resonanceSet.atomSets)\\n atom = atomSets[0].findFirstAtom()\\n element = atom.chemAtom.elementSymbol\\n if resonance.isotopeCode[-len(element):] != element:\\n msg = 'Resonance %d isotope-assignment mismatch: Resetting isotope' \\n print msg % resonance.serial\\n \\n resonance.isotopeCode = DEFAULT_ISOTOPES.get(element, 'unknown')\\n getBoundResonances(resonance, recalculate=True, contribs=None) \\n \\n spinSystem = findSpinSystem(resonance)\\n if spinSystem:\\n if resonance.resonanceGroup: # same as the spin system\\n residue = atom.residue\\n \\n if spinSystem.residue is not residue:\\n #assignSpinSystemResidue(spinSystem,residue)\\n \\n if doMerge:\\n ccpCode = residue.molResidue.ccpCode\\n spinSystems = list(resonance.nmrProject.findAllResonanceGroups(residue=residue))\\n N = len(spinSystems)\\n msg = 'There are %d separate %d%s spin systems. Merge together?'\\n if (N > 1) and showOkCancel('Confirm', msg % (N,residue.seqCode,ccpCode)):\\n assignSpinSystemResidue(spinSystem,residue) \\n \\n for spinSystem1 in spinSystems[1:]:\\n mergeSpinSystems(spinSystem1,spinSystems[0])\\n \\n else:\\n assignSpinSystemResidue(spinSystem,residue) \\n \\n else:\\n assignSpinSystemResidue(spinSystem,residue) \\n \\n else:\\n addSpinSystemResonance(spinSystem, resonance)\\n\\n assignResonanceType(resonance, atomSets)\\n \\n else:\\n updateResonanceAnnotation(resonance)\\n\\n if not resonance.shifts:\\n if resonance.peakDimContribs:\\n for contrib in resonance.peakDimContribs:\\n peakDim = contrib.peakDim\\n experiment = peakDim.peak.peakList.dataSource.experiment\\n \\n if experiment.shiftList is None:\\n shiftList = resonance.nmrProject.findFirstMeasurementList(className='ShiftList')\\n if shiftList is None:\\n shiftList = resonance.nmrProject.newShiftList(unit='ppm')\\n experiment.setShiftList( shiftList )\\n \\n updateResonShift(resonance,peakDim)\",\n \"def check_termination(self) :\\n\\t\\trc_all = self.rc1[-1]+self.rc2[-1]\\n\\t\\tif rc_all == 0 and self.ssep[-1] < self.tol \\\\\\n\\t\\t\\t and self.ssed[-1] < self.tol : \\n\\t\\t\\tself.converged = True\\n\\t\\t\\tself.continueLoop = False \\n\\t\\n\\t\\tif self.loopiter >= self.maxiter : \\n\\t\\t\\tself.maxiter_exceeded = True\\n\\t\\t\\tself.converged = False\\n\\t\\t\\tself.continueLoop = False\\n\\t\\n\\t# Check any obvious SSE inconsistencies\\n\\t\\tif self.ssep[-1] > self.sseMax or self.ssed[-1] > self.sseMax : \\n\\t\\t\\tself.continueLoop = False\",\n \"def test_case_01_right_scalene(self):\\n self.__assert_equals_test_case(self.yield_right_scalene_triangles(), 'Right Scalene Triangle')\",\n \"def _select_arm(self):\\n pass\",\n \"def test_rescoring_option_problem(self):\\r\\n # get descriptor:\\r\\n problem_url_name = 'H1P1'\\r\\n self.define_option_problem(problem_url_name)\\r\\n location = InstructorTaskModuleTestCase.problem_location(problem_url_name)\\r\\n descriptor = self.module_store.get_item(location)\\r\\n\\r\\n # first store answers for each of the separate users:\\r\\n self.submit_student_answer('u1', problem_url_name, [OPTION_1, OPTION_1])\\r\\n self.submit_student_answer('u2', problem_url_name, [OPTION_1, OPTION_2])\\r\\n self.submit_student_answer('u3', problem_url_name, [OPTION_2, OPTION_1])\\r\\n self.submit_student_answer('u4', problem_url_name, [OPTION_2, OPTION_2])\\r\\n\\r\\n self.check_state('u1', descriptor, 2, 2, 1)\\r\\n self.check_state('u2', descriptor, 1, 2, 1)\\r\\n self.check_state('u3', descriptor, 1, 2, 1)\\r\\n self.check_state('u4', descriptor, 0, 2, 1)\\r\\n\\r\\n # update the data in the problem definition\\r\\n self.redefine_option_problem(problem_url_name)\\r\\n # confirm that simply rendering the problem again does not result in a change\\r\\n # in the grade:\\r\\n self.render_problem('u1', problem_url_name)\\r\\n self.check_state('u1', descriptor, 2, 2, 1)\\r\\n\\r\\n # rescore the problem for only one student -- only that student's grade should change:\\r\\n self.submit_rescore_one_student_answer('instructor', problem_url_name, User.objects.get(username='u1'))\\r\\n self.check_state('u1', descriptor, 0, 2, 1)\\r\\n self.check_state('u2', descriptor, 1, 2, 1)\\r\\n self.check_state('u3', descriptor, 1, 2, 1)\\r\\n self.check_state('u4', descriptor, 0, 2, 1)\\r\\n\\r\\n # rescore the problem for all students\\r\\n self.submit_rescore_all_student_answers('instructor', problem_url_name)\\r\\n self.check_state('u1', descriptor, 0, 2, 1)\\r\\n self.check_state('u2', descriptor, 1, 2, 1)\\r\\n self.check_state('u3', descriptor, 1, 2, 1)\\r\\n self.check_state('u4', descriptor, 2, 2, 1)\",\n \"def test_pure_prisoners_dilemma(_):\\n game = gamegen.sym_2p2s_game(2, 0, 3, 1) # prisoners dilemma\\n eqm = [0, 2]\\n\\n assert (\\n regret.pure_strategy_regret(game, eqm) == 0\\n ), \\\"Known equilibrium was not zero regret\\\"\",\n \"def select_perturbation_residues(molecule):\\n # Validte the length of the molecule\\n validate_molecule_length(molecule)\\n # Set the maximum allowed perturbation numbers\\n maxNum = 3\\n # Select a random number between 1 and maxNum\\n ranNum = random.randint(1, maxNum)\\n # Define the perturbed list to hold the perturbed residue name\\n perturbed = []\\n count = 0\\n while count < ranNum:\\n # Random select a residue number in the molecule \\n index = random.randint(1, len(molecule))\\n perturbed.append([molecule.name, index, molecule[index].name])\\n count += 1\\n\\n return perturbed\",\n \"def test_special_RR(self):\\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, -0.1).to_matrix(), \\\"RR\\\", {})\\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, 0.2).to_matrix(), \\\"RR\\\", {\\\"r\\\": 2})\\n self.check_oneq_special_cases(U3Gate(-np.pi, 0.2, 0.0).to_matrix(), \\\"RR\\\", {\\\"r\\\": 1})\\n self.check_oneq_special_cases(U3Gate(np.pi, 0.0, 0.2).to_matrix(), \\\"RR\\\", {\\\"r\\\": 1})\\n self.check_oneq_special_cases(U3Gate(0.1, 0.2, 0.3).to_matrix(), \\\"RR\\\", {\\\"r\\\": 2})\",\n \"def restrict_non_nbrs_from_repacking(pose, res, task, pack_radius):\\n\\n center = pose.residue( res ).xyz( pose.residue( res ).nbr_atom() )\\n print( \\\"Res: pack radius: \\\"+repr(pack_radius) )\\n for i in range(1, pose.total_residue() + 1):\\n # only pack the mutating residue and any within the pack_radius\\n if i == res: continue\\n\\n nbr = pose.residue( i ).xyz( pose.residue( i ).nbr_atom() )\\n dist = nbr.distance(center)\\n if dist > pack_radius:\\n task.nonconst_residue_task(i).prevent_repacking()\\n else:\\n task.nonconst_residue_task(i).restrict_to_repacking()\\n\\n #print task\\n return task\",\n \"def test_match_left_none():\\r\\n runmatch(lcode_left_none)\",\n \"def test_count_spins_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Test for the error.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.count_spins)\",\n \"def selectResN(self):\\n\\n\\t\\tif len(self.resn) == 0:\\n\\t\\t\\treturn\\n\\n\\t\\ttmplist = []\\n\\t\\tfor atom in self.atomlist:\\n\\t\\t\\tfound = False\\n\\t\\t\\tfor resn in self.resn:\\n\\t\\t\\t\\tif atom.parentResidue.name == resn:\\n\\t\\t\\t\\t\\tfound = True\\n\\t\\t\\t\\t\\tbreak\\n\\n\\t\\t\\tif found and not self.invresn:\\n\\t\\t\\t\\ttmplist.append(atom)\\n\\t\\t\\tif not found and self.invresn:\\n\\t\\t\\t\\ttmplist.append(atom)\\n\\n\\t\\tself.atomlist = tmplist\",\n \"def test_wrong_turn_results_in_inf_loop():\\n\\t\\n\\t# chceme vystup v citelny podobe pro PIPE\\n\\tcp = subprocess.run([sys.executable, 'game.py'],\\n\\t\\t\\t\\t\\t\\t# misto encoding, kvuli Python3.5, pouziju univ_new\\n\\t\\t\\t\\t\\t\\tuniversal_newlines=True,\\n\\t\\t\\t\\t\\t\\tstdout=subprocess.PIPE,\\n\\t\\t\\t\\t\\t\\tinput='doggie\\\\nrock\\\\n',\\n\\t\\t\\t\\t\\t\\tcheck=True)\\n\\n\\tassert cp.stdout.count('Choice: rock, scissors, paper: ') == 2 # 2x True value\",\n \"def test_remain():\\r\\n global pickno\\r\\n #Change pick number to the total amount of balls\\r\\n # Ex. If we have 3 balls remaining the user cannot pick 4\\r\\n if total <= 4:\\r\\n pickno = total\",\n \"def test_one_arm(self):\\n bandit = self.bandit_class(self.one_arm_test_case)\\n self._test_one_arm(bandit)\",\n \"def test_match_or_none2():\\r\\n runmatch(lcode)\",\n \"def test_pol_id_range(self):\\n pol = '0~1'\\n ref_idx = []\\n self.res=self.run_task(infile=self.rawfile,pol=pol,calmode=self.calmode,outfile=self.outname,outform='ASAP')\\n self.assertEqual(self.res,None,\\n msg='Any error occurred during calibration')\\n self._compare_with_analytic(self.outname, self.line, self.baseline, ref_idx)\",\n \"def test_recomb(self):\\n sol1, sol2 = [0,0,0,0],[1,1,1,1]\\n hot_regions = [0,0,0,1] ##NOTE: sum(hot_regions) shouls always be 1\\n rec_events = 1\\n sol = list(d.recombine(sol1,sol2,rec_events,hot_regions))\\n print(f\\\"recomb sol: {sol}\\\")\\n self.assertTrue( (sol == [0,0,0,1]) or (sol == [1,1,1,0]) )\",\n \"def selectResI(self):\\n\\n\\t\\tif len(self.resi) == 0:\\t\\n\\t\\t\\treturn\\n\\n\\t\\ttmplist = []\\n\\t\\tfor atom in self.atomlist:\\n\\t\\t\\tfound = False\\n\\t\\t\\tfor resi in self.resi:\\n\\t\\t\\t\\tif int(atom.parentResidue.file_id) == resi:\\n\\t\\t\\t\\t\\tfound = True\\n\\t\\t\\t\\t\\tbreak\\n\\n\\t\\t\\tif found and not self.invresi:\\n\\t\\t\\t\\ttmplist.append(atom)\\n\\t\\t\\tif not found and self.invresi:\\n\\t\\t\\t\\ttmplist.append(atom)\\n\\n\\t\\tself.atomlist = tmplist\",\n \"def test_three_arms_one_unsampled_arm(self):\\n self._test_three_arms_one_unsampled_arm()\",\n \"def test_match_or_none():\\r\\n runmatch(lcode)\",\n \"def test_select_pdb_conformation(self):\\n with mmtools.utils.temporary_directory() as tmp_dir:\\n yaml_content = \\\"\\\"\\\"\\n ---\\n options:\\n output_dir: {}\\n setup_dir: .\\n molecules:\\n selected:\\n filepath: {}\\n leap: {{parameters: oldff/leaprc.ff14SB}}\\n select: 1\\n \\\"\\\"\\\".format(tmp_dir, self.pdb_path)\\n yaml_content = textwrap.dedent(yaml_content)\\n exp_builder = ExperimentBuilder(yaml_content)\\n\\n # The molecule now is neither set up nor processed\\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\\n assert is_setup is False\\n assert is_processed is False\\n\\n # The setup of the molecule must isolate the frame in a single-frame PDB\\n exp_builder._db._setup_molecules('selected')\\n selected_pdb_path = os.path.join(tmp_dir, pipeline.SetupDatabase.MOLECULES_DIR,\\n 'selected', 'selected.pdb')\\n assert os.path.exists(os.path.join(selected_pdb_path))\\n assert os.path.getsize(os.path.join(selected_pdb_path)) > 0\\n\\n # The positions must be the ones of the second frame\\n selected_pdb = PDBFile(selected_pdb_path)\\n selected_pos = selected_pdb.getPositions(asNumpy=True)\\n second_pos = PDBFile(self.pdb_path).getPositions(asNumpy=True, frame=1)\\n assert selected_pdb.getNumFrames() == 1\\n assert (selected_pos == second_pos).all()\\n\\n # The description of the molecule is now updated\\n assert os.path.normpath(exp_builder._db.molecules['selected']['filepath']) == selected_pdb_path\\n\\n # The molecule now both set up and processed\\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\\n assert is_setup is True\\n assert is_processed is True\\n\\n # A new instance of ExperimentBuilder is able to resume with correct molecule\\n exp_builder = ExperimentBuilder(yaml_content)\\n is_setup, is_processed = exp_builder._db.is_molecule_setup('selected')\\n assert is_setup is True\\n assert is_processed is True\",\n \"def test_no_specification_error():\\n try:\\n bad_arm = survey.get_spiral_slice()\\n except SyntaxError:\\n assert True\\n else:\\n assert False\",\n \"def test_call_default_params_reversed_seq(self):\\r\\n\\r\\n app = Usearch610DeNovoOtuPicker(\\r\\n params={'save_intermediate_files': False,\\r\\n 'output_dir': self.output_dir,\\r\\n 'remove_usearch_logs': True\\r\\n })\\r\\n\\r\\n obs_clusters = app(self.tmp_seq_filepath_97perc_id_rc)\\r\\n\\r\\n # RC seq should fall into its own cluster\\r\\n expected_clusters = [set(['usearch_ecoli_seq',\\r\\n 'usearch_ecoli_seq_1bp_change']),\\r\\n set(['usearch_ecoli_seq_2bp_change_rc'])]\\r\\n\\r\\n self.assertEqual(len(obs_clusters), 2)\\r\\n for result in obs_clusters:\\r\\n self.assertTrue(set(obs_clusters[result]) in expected_clusters)\",\n \"def check_for_barrierless_reaction(self):\\n # Check for barrierless reaction leading to new graphs\\n if self.rc_opt_system_name not in self.systems: # Skip if already done\\n print(\\\"Running Reactive Complex Optimization\\\")\\n print(\\\"Settings:\\\")\\n print(self.settings[self.rc_opt_system_name], \\\"\\\\n\\\")\\n self.systems, success = self.observed_readuct_call(\\n 'run_opt_task', self.systems, [self.rc_key], **self.settings[self.rc_opt_system_name]\\n )\\n self.throw_if_not_successful(\\n success,\\n self.systems,\\n [self.rc_opt_system_name],\\n [],\\n \\\"Reactive complex optimization failed.\\\\n\\\",\\n )\\n _, rc_opt_graph, _, _, rc_opt_decision_lists = \\\\\\n self.get_graph_charges_multiplicities(self.rc_opt_system_name, sum(self.start_charges))\\n\\n if not masm.JsonSerialization.equal_molecules(self.start_graph, rc_opt_graph):\\n return rc_opt_graph, rc_opt_decision_lists\\n return None, None\",\n \"def test_perceive_residues_natoms_t4(self, strict_chirality):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/T4-protein.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def test_is_in_ring(self):\\n molecule = Molecule.from_smiles(\\\"c1ccccc1\\\")\\n\\n for atom in molecule.atoms:\\n if atom.atomic_number == 6:\\n assert atom.is_in_ring()\\n\\n for bond in molecule.bonds:\\n if 1 in (bond.atom1.atomic_number, bond.atom2.atomic_number):\\n continue\\n assert bond.is_in_ring()\",\n \"def test_specific_qubit_pauli_error_gate_100percent(self):\\n qr = QuantumRegister(2, 'qr')\\n cr = ClassicalRegister(2, 'cr')\\n circuit = QuantumCircuit(qr, cr)\\n circuit.iden(qr)\\n circuit.barrier(qr)\\n circuit.measure(qr, cr)\\n backend = QasmSimulator()\\n shots = 100\\n # test noise model\\n error = pauli_error([('X', 1)])\\n noise_model = NoiseModel()\\n noise_model.add_quantum_error(error, 'id', [1])\\n # Execute\\n target = {'0x2': shots}\\n circuit = transpile(circuit, basis_gates=noise_model.basis_gates)\\n qobj = assemble([circuit], backend, shots=shots)\\n result = backend.run(qobj, noise_model=noise_model).result()\\n self.is_completed(result)\\n self.compare_counts(result, [circuit], [target], delta=0)\",\n \"def mutate_residue(pose, mutant_position, mutant_aa,\\n pack_radius = 0.0, pack_scorefxn = '' ):\\n #### a MutateResidue Mover exists similar to this except it does not pack\\n #### the area around the mutant residue (no pack_radius feature)\\n #mutator = MutateResidue(mutant_position, mutant_aa)\\n #mutator.apply(test_pose)\\n\\n if pose.is_fullatom() == False:\\n IOError( 'mutate_residue only works with fullatom poses' )\\n\\n\\n # create a standard scorefxn by default\\n if not pack_scorefxn:\\n pack_scorefxn = rosetta.core.scoring.get_score_function()\\n\\n task = pyrosetta.standard_packer_task(pose)\\n\\n # the Vector1 of booleans (a specific object) is needed for specifying the\\n # mutation, this demonstrates another more direct method of setting\\n # PackerTask options for design\\n aa_bool = rosetta.utility.vector1_bool()\\n # PyRosetta uses several ways of tracking amino acids (ResidueTypes)\\n # the numbers 1-20 correspond individually to the 20 proteogenic amino acids\\n # aa_from_oneletter returns the integer representation of an amino acid\\n # from its one letter code\\n # convert mutant_aa to its integer representation\\n mutant_aa = rosetta.core.chemical.aa_from_oneletter_code(mutant_aa)\\n\\n # mutation is performed by using a PackerTask with only the mutant\\n # amino acid available during design\\n # to do this, construct a Vector1 of booleans indicating which amino acid\\n # (by its numerical designation, see above) to allow\\n for i in range(1, 21):\\n # in Python, logical expression are evaluated with priority, thus the\\n # line below appends to aa_bool the truth (True or False) of the\\n # statement i == mutant_aa\\n aa_bool.append( i == int(mutant_aa) )\\n\\n # modify the mutating residue's assignment in the PackerTask using the\\n # Vector1 of booleans across the proteogenic amino acids\\n task.nonconst_residue_task(mutant_position\\n ).restrict_absent_canonical_aas(aa_bool)\\n\\n # prevent residues from packing by setting the per-residue \\\"options\\\" of\\n # the PackerTask\\n restrict_non_nbrs_from_repacking(pose, mutant_position, task, pack_radius)\\n\\n # apply the mutation and pack nearby residues\\n #print task\\n packer = rosetta.protocols.simple_moves.PackRotamersMover(pack_scorefxn, task)\\n packer.apply(pose)\",\n \"def test_ok_mm_primer(self):\\r\\n primers = ['AAAA', 'GGGG']\\r\\n self.assertEqual(ok_mm_primer('AAAA', primers, 0), True)\\r\\n self.assertEqual(ok_mm_primer('AAAA', primers, 3), True)\\r\\n self.assertEqual(ok_mm_primer('CCCC', primers, 0), False)\\r\\n self.assertEqual(ok_mm_primer('CCCA', primers, 3), True)\\r\\n self.assertEqual(ok_mm_primer('CCCA', primers, 2), False)\\r\\n self.assertEqual(ok_mm_primer('CCGG', primers, 2), True)\\r\\n self.assertEqual(ok_mm_primer('CCGA', primers, 2), False)\",\n \"def test_parameterize_mol_missing_stereo_rdkit(self, force_field):\\n toolkit_registry = ToolkitRegistry(\\n toolkit_precedence=[RDKitToolkitWrapper, AmberToolsToolkitWrapper]\\n )\\n\\n molecule = Molecule.from_smiles(\\\"CC1CCC(=O)O1\\\", allow_undefined_stereo=True)\\n topology = Topology.from_molecules([molecule])\\n\\n force_field.create_openmm_system(\\n topology,\\n toolkit_registry=toolkit_registry,\\n )\",\n \"def _loop_raw(raw):\\n raise NotImplemented\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.8018613","0.7852093","0.77218246","0.70574504","0.68793595","0.67554224","0.66418993","0.65647024","0.64698106","0.6459469","0.6435851","0.63787186","0.62164485","0.6151769","0.61505395","0.61433077","0.60872215","0.60452425","0.5893791","0.5879402","0.5816877","0.5748314","0.57241976","0.5518187","0.5453054","0.54468817","0.54436886","0.5415543","0.54130983","0.53951675","0.53886235","0.53503746","0.53234977","0.53062725","0.52978724","0.52400845","0.5232283","0.52124226","0.5110902","0.507787","0.5060523","0.50497514","0.5034254","0.50307536","0.5018271","0.5004526","0.49671337","0.4954381","0.4944591","0.49398127","0.4924353","0.4919342","0.4916166","0.48952717","0.48846805","0.48831335","0.48799494","0.48711544","0.4855505","0.48335114","0.48167804","0.47885442","0.47885442","0.47816795","0.47597817","0.47567594","0.47442466","0.47359347","0.469388","0.46902898","0.46813643","0.467412","0.4673299","0.4671667","0.4662525","0.4659108","0.46536848","0.46452016","0.4631938","0.46267998","0.46262944","0.46214086","0.461878","0.45977977","0.45936555","0.4589389","0.45859185","0.45834365","0.45826203","0.45773646","0.4577183","0.45689163","0.45655763","0.45624548","0.4560336","0.4558492","0.45572573","0.4557054","0.4547731","0.4547155"],"string":"[\n \"0.8018613\",\n \"0.7852093\",\n \"0.77218246\",\n \"0.70574504\",\n \"0.68793595\",\n \"0.67554224\",\n \"0.66418993\",\n \"0.65647024\",\n \"0.64698106\",\n \"0.6459469\",\n \"0.6435851\",\n \"0.63787186\",\n \"0.62164485\",\n \"0.6151769\",\n \"0.61505395\",\n \"0.61433077\",\n \"0.60872215\",\n \"0.60452425\",\n \"0.5893791\",\n \"0.5879402\",\n \"0.5816877\",\n \"0.5748314\",\n \"0.57241976\",\n \"0.5518187\",\n \"0.5453054\",\n \"0.54468817\",\n \"0.54436886\",\n \"0.5415543\",\n \"0.54130983\",\n \"0.53951675\",\n \"0.53886235\",\n \"0.53503746\",\n \"0.53234977\",\n \"0.53062725\",\n \"0.52978724\",\n \"0.52400845\",\n \"0.5232283\",\n \"0.52124226\",\n \"0.5110902\",\n \"0.507787\",\n \"0.5060523\",\n \"0.50497514\",\n \"0.5034254\",\n \"0.50307536\",\n \"0.5018271\",\n \"0.5004526\",\n \"0.49671337\",\n \"0.4954381\",\n \"0.4944591\",\n \"0.49398127\",\n \"0.4924353\",\n \"0.4919342\",\n \"0.4916166\",\n \"0.48952717\",\n \"0.48846805\",\n \"0.48831335\",\n \"0.48799494\",\n \"0.48711544\",\n \"0.4855505\",\n \"0.48335114\",\n \"0.48167804\",\n \"0.47885442\",\n \"0.47885442\",\n \"0.47816795\",\n \"0.47597817\",\n \"0.47567594\",\n \"0.47442466\",\n \"0.47359347\",\n \"0.469388\",\n \"0.46902898\",\n \"0.46813643\",\n \"0.467412\",\n \"0.4673299\",\n \"0.4671667\",\n \"0.4662525\",\n \"0.4659108\",\n \"0.46536848\",\n \"0.46452016\",\n \"0.4631938\",\n \"0.46267998\",\n \"0.46262944\",\n \"0.46214086\",\n \"0.461878\",\n \"0.45977977\",\n \"0.45936555\",\n \"0.4589389\",\n \"0.45859185\",\n \"0.45834365\",\n \"0.45826203\",\n \"0.45773646\",\n \"0.4577183\",\n \"0.45689163\",\n \"0.45655763\",\n \"0.45624548\",\n \"0.4560336\",\n \"0.4558492\",\n \"0.45572573\",\n \"0.4557054\",\n \"0.4547731\",\n \"0.4547155\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.83963245"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81497,"cells":{"query":{"kind":"string","value":"Test the function for returning the desired molecule data container. The function tested is pipe_control.mol_res_spin.return_molecule()."},"document":{"kind":"string","value":"def test_return_molecule(self):\n\n # Ask for a few molecules.\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\n\n # Test the data of molecule 1.\n self.assertEqual(mol1.name, 'Ap4Aase')\n\n # Test the data of molecule 2.\n self.assertEqual(mol2.name, 'RNA')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_return_molecule_pipe_fail(self):\n\n # Try to get a molecule from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_molecule_loop(self):\n\n # Loop over the molecules.\n for mol in mol_res_spin.molecule_loop('#RNA'):\n # Test the molecule name.\n self.assertEqual(mol.name, 'RNA')\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)","def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_return_residue(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_residue(':1')\n res2 = mol_res_spin.return_residue(selection=':2')\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\n\n # Test the data of residue 1.\n self.assertEqual(res1.num, 1)\n self.assertEqual(res1.name, None)\n\n # Test the data of residue 2.\n self.assertEqual(res2.num, 2)\n self.assertEqual(res2.name, 'Glu')\n\n # Test the data of residue 4.\n self.assertEqual(res4.num, 4)\n self.assertEqual(res4.name, 'Pro')\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5.num, -5)\n self.assertEqual(res5.name, None)\n self.assertEqual(res5.spin[1].name, 'N5')","def test_molecule_loop_no_selection(self):\n\n # Molecule data.\n name = ['Ap4Aase', 'RNA']\n\n # Loop over the molecules.\n i = 0\n for mol in mol_res_spin.molecule_loop():\n # Test the molecule names.\n self.assertEqual(mol.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def test_run_molecule(self, single_mol_system):\n sequence = \"ABCDE\"\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def test_return_single_residue_info(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_single_residue_info('1')\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\n res5 = mol_res_spin.return_single_residue_info('-5')\n\n # Test the data of residue 1.\n self.assertEqual(res1, (1, None))\n\n # Test the data of residue 2.\n self.assertEqual(res2, (2, 'Glu'))\n\n # Test the data of residue 4.\n self.assertEqual(res4, (4, 'Pro'))\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5, (-5, None))","def test_set_molecule(self):\n mol = Molecule.from_smiles(\"CCO\")\n atom = Atom(6, 0, False)\n atom.molecule = mol","def molecule(self):\n return self._molecule","def make_molecule(self):\n\n self.data.molecules = self.data.Smiles.apply(Chem.MolFromSmiles)\n\n return self.data.molecules","def test_get_container(self):\n pass","def setUp(self):\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Name the first molecule.\n cdp.mol[0].name = 'Ap4Aase'\n\n # Add a second molecule to the system.\n cdp.mol.add_item(mol_name='RNA')\n\n # Add two more residues to the first molecule (and set the residue number of the first).\n cdp.mol[0].res[0].num = 1\n cdp.mol[0].res.add_item(res_num=2, res_name='Glu')\n cdp.mol[0].res.add_item(res_num=4, res_name='Pro')\n\n # Add some spin info to this molecule.\n cdp.mol[0].res[0].spin[0].name = 'NH'\n cdp.mol[0].res[0].spin[0].num = 60\n cdp.mol[0].res[1].spin[0].name = 'NH'\n cdp.mol[0].res[1].spin[0].num = 63\n\n # Add one more residue to the second molecule (and set the residue number of the first).\n cdp.mol[1].res[0].num = -5\n cdp.mol[1].res.add_item(res_num=-4)\n\n # Add a second set of spins to the second molecule (naming the first set first).\n cdp.mol[1].res[0].spin[0].name = 'C8'\n cdp.mol[1].res[1].spin[0].name = 'C8'\n cdp.mol[1].res[0].spin.add_item(spin_name='N5')\n cdp.mol[1].res[1].spin.add_item(spin_name='N5')\n cdp.mol[1].res[1].spin.add_item(spin_name='2H', spin_num=132)\n\n # Deselect a number of spins.\n cdp.mol[0].res[0].spin[0].select = 0\n cdp.mol[0].res[2].spin[0].select = 0\n cdp.mol[1].res[0].spin[0].select = 0\n cdp.mol[1].res[1].spin[1].select = 0\n\n # Update the metadata.\n mol_res_spin.metadata_update()","def test_single_molecule(self, single_mol_system, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def test_container_get_set(self): \n circdich1 = self.circdich1\n \n cntnr = CircDichSpectrumContainer()\n cntnr.set_axis(circdich1.axis)\n cntnr.set_spectrum(circdich1, tag='tester')\n spec = cntnr.get_spectrum(tag='tester')\n \n numpy.testing.assert_array_equal(circdich1.data, spec.data)","def init_molecule():\n \n pos1 = np.array([[0.2],[0.2]])\n pos2 = np.array([[0.8],[0.8]])\n mol = Molecule(pos1, pos2, 10, 20, 1, 0.5)\n \n return mol","def get_molecules(root):\n mols = get_records_with_tag(root,'molecule')\n if not mols: mols = [root] # Assume tree consists of a molecule at the root\n return mols","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def _get_components(\n design_unit: oechem.OEDesignUnit\n ) -> Tuple[oechem.OEGraphMol(), oechem.OEGraphMol(), oechem.OEGraphMol()]:\n from openeye import oechem\n\n protein, solvent, ligand = oechem.OEGraphMol(), oechem.OEGraphMol(), oechem.OEGraphMol()\n\n logging.debug(\"Extracting molecular components ...\")\n design_unit.GetProtein(protein)\n design_unit.GetSolvent(solvent)\n design_unit.GetLigand(ligand)\n\n # delete protein atoms with no name (found in prepared protein of 4ll0)\n for atom in protein.GetAtoms():\n if not atom.GetName().strip():\n logging.debug(\"Deleting unknown atom ...\")\n protein.DeleteAtom(atom)\n\n # perceive residues to remove artifacts of other design units in the sequence of the protein\n # preserve certain properties to assure correct behavior of the pipeline,\n # e.g. deletion of chains in OEKLIFSKinaseApoFeaturizer._process_kinase_domain method\n preserved_info = (\n oechem.OEPreserveResInfo_ResidueNumber\n | oechem.OEPreserveResInfo_ResidueName\n | oechem.OEPreserveResInfo_AtomName\n | oechem.OEPreserveResInfo_ChainID\n | oechem.OEPreserveResInfo_HetAtom\n | oechem.OEPreserveResInfo_InsertCode\n | oechem.OEPreserveResInfo_AlternateLocation\n )\n oechem.OEPerceiveResidues(protein, preserved_info)\n oechem.OEPerceiveResidues(solvent, preserved_info)\n oechem.OEPerceiveResidues(ligand)\n\n logging.debug(\n \"Number of component atoms: \" +\n f\"Protein - {protein.NumAtoms()}, \" +\n f\"Solvent - {solvent.NumAtoms()}, \" +\n f\"Ligand - {ligand.NumAtoms()}.\"\n )\n return protein, solvent, ligand","def test_to_from_rdkit(self, molecule):\n # import pickle\n from openforcefield.utils.toolkits import UndefinedStereochemistryError\n\n undefined_stereo = molecule.name in rdkit_drugbank_undefined_stereo_mols\n\n toolkit_wrapper = RDKitToolkitWrapper()\n\n rdmol = molecule.to_rdkit()\n molecule_smiles = molecule.to_smiles(toolkit_registry=toolkit_wrapper)\n\n # First test making a molecule using the Molecule(oemol) method\n\n # If this is a known failure, check that it raises UndefinedStereochemistryError\n # and proceed with the test ignoring it.\n test_mol = None\n if undefined_stereo:\n with pytest.raises(UndefinedStereochemistryError):\n Molecule(rdmol)\n test_mol = Molecule(rdmol, allow_undefined_stereo=True)\n else:\n test_mol = Molecule(rdmol)\n\n test_mol_smiles = test_mol.to_smiles(toolkit_registry=toolkit_wrapper)\n assert molecule_smiles == test_mol_smiles\n\n # Check that the two topologies are isomorphic.\n assert_molecule_is_equal(\n molecule, test_mol, \"Molecule.to_rdkit()/Molecule(rdmol) round trip failed\"\n )\n\n # Second, test making a molecule using the Molecule.from_openeye(oemol) method\n\n # If this is a known failure, check that it raises UndefinedStereochemistryError\n # and proceed with the test.\n if undefined_stereo:\n with pytest.raises(UndefinedStereochemistryError):\n Molecule.from_rdkit(rdmol)\n test_mol = Molecule.from_rdkit(rdmol, allow_undefined_stereo=True)\n else:\n test_mol = Molecule.from_rdkit(rdmol)\n\n test_mol_smiles = test_mol.to_smiles(toolkit_registry=toolkit_wrapper)\n assert molecule_smiles == test_mol_smiles\n\n # Check that the two topologies are isomorphic.\n assert_molecule_is_equal(\n molecule, test_mol, \"Molecule.to_rdkit()/from_rdkit() round trip failed\"\n )","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_return_single_residue_info_fail(self):\n\n # Ask for a few residues.\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')","def test_molecule_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for molecule in mol_res_spin.molecule_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_get_thermo_data(self):\n output_directory = os.path.join(self.mop4.settings.fileStore, '..', '..')\n self.mop4.set_default_output_directory(output_directory)\n self.gauss3.set_default_output_directory(output_directory)\n self.molpro1.set_default_output_directory(output_directory)\n\n mol = Molecule().from_smiles('C1=CC=C2C=CC=CC2=C1')\n\n with self.assertRaises(Exception):\n self.mop4.get_thermo_data(mol)\n self.gauss3.get_thermo_data(mol)\n self.molpro1.get_thermo_data(mol)","def test_to_from_rdkit(self, molecule):\n # import pickle\n from openff.toolkit.utils.toolkits import UndefinedStereochemistryError\n\n undefined_stereo = molecule.name in rdkit_drugbank_undefined_stereo_mols\n\n toolkit_wrapper = RDKitToolkitWrapper()\n\n rdmol = molecule.to_rdkit()\n molecule_smiles = molecule.to_smiles(toolkit_registry=toolkit_wrapper)\n\n # First test making a molecule using the Molecule(oemol) method\n\n # If this is a known failure, check that it raises UndefinedStereochemistryError\n # and proceed with the test ignoring it.\n test_mol = None\n if undefined_stereo:\n with pytest.raises(UndefinedStereochemistryError):\n Molecule(rdmol)\n test_mol = Molecule(rdmol, allow_undefined_stereo=True)\n else:\n test_mol = Molecule(rdmol)\n\n test_mol_smiles = test_mol.to_smiles(toolkit_registry=toolkit_wrapper)\n assert molecule_smiles == test_mol_smiles\n\n # Check that the two topologies are isomorphic.\n assert_molecule_is_equal(\n molecule, test_mol, \"Molecule.to_rdkit()/Molecule(rdmol) round trip failed\"\n )\n\n # Second, test making a molecule using the Molecule.from_openeye(oemol) method\n\n # If this is a known failure, check that it raises UndefinedStereochemistryError\n # and proceed with the test.\n if undefined_stereo:\n with pytest.raises(UndefinedStereochemistryError):\n Molecule.from_rdkit(rdmol)\n test_mol = Molecule.from_rdkit(rdmol, allow_undefined_stereo=True)\n else:\n test_mol = Molecule.from_rdkit(rdmol)\n\n test_mol_smiles = test_mol.to_smiles(toolkit_registry=toolkit_wrapper)\n assert molecule_smiles == test_mol_smiles\n\n # Check that the two topologies are isomorphic.\n assert_molecule_is_equal(\n molecule, test_mol, \"Molecule.to_rdkit()/from_rdkit() round trip failed\"\n )","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def storeMolecule():\n pass","def __init__(self,\n molinit=None,\n dtype=None,\n\n geom=None,\n elea=None,\n elez=None,\n elem=None,\n mass=None,\n real=None,\n elbl=None,\n\n name=None,\n units='Angstrom',\n input_units_to_au=None,\n fix_com=None,\n fix_orientation=None,\n fix_symmetry=None,\n\n fragment_separators=None,\n fragment_charges=None,\n fragment_multiplicities=None,\n\n molecular_charge=None,\n molecular_multiplicity=None,\n\n enable_qm=True,\n enable_efp=True,\n missing_enabled_return_qm='none',\n missing_enabled_return_efp='none',\n\n missing_enabled_return='error',\n tooclose=0.1,\n zero_ghost_fragments=False,\n nonphysical=False,\n mtol=1.e-3,\n verbose=1):\n super(Molecule, self).__init__()\n\n if molinit is not None or geom is not None:\n if isinstance(molinit, dict):\n molrec = molinit\n\n elif isinstance(molinit, basestring):\n compound_molrec = molparse.from_string(\n molstr=molinit,\n dtype=dtype,\n name=name,\n fix_com=fix_com,\n fix_orientation=fix_orientation,\n fix_symmetry=fix_symmetry,\n return_processed=False,\n enable_qm=enable_qm,\n enable_efp=enable_efp,\n missing_enabled_return_qm=missing_enabled_return_qm,\n missing_enabled_return_efp=missing_enabled_return_efp,\n verbose=verbose)\n molrec = compound_molrec['qm']\n\n elif molinit is None and geom is not None:\n molrec = molparse.from_arrays(\n geom=geom,\n elea=elea,\n elez=elez,\n elem=elem,\n mass=mass,\n real=real,\n elbl=elbl,\n name=name,\n units=units,\n input_units_to_au=input_units_to_au,\n fix_com=fix_com,\n fix_orientation=fix_orientation,\n fix_symmetry=fix_symmetry,\n fragment_separators=fragment_separators,\n fragment_charges=fragment_charges,\n fragment_multiplicities=fragment_multiplicities,\n molecular_charge=molecular_charge,\n molecular_multiplicity=molecular_multiplicity,\n domain='qm',\n missing_enabled_return=missing_enabled_return,\n tooclose=tooclose,\n zero_ghost_fragments=zero_ghost_fragments,\n nonphysical=nonphysical,\n mtol=mtol,\n verbose=verbose)\n\n # ok, got the molrec dictionary; now build the thing\n self._internal_from_dict(molrec, verbose=verbose)\n\n # The comment line\n self.tagline = \"\"","def __call__(self, mol):\n return self.choose(mol)","def __init__(self,\n num_masks=1,\n num_fake=0,\n epsilon_greedy=0.0,\n num_classes = 2,\n num_samples = 1000,\n max_length = 30,\n ambiguity=False,\n num_bondtypes=1):\n\n self.num_masks = num_masks\n self.num_fake = num_fake\n self.epsilon_greedy = epsilon_greedy\n self.num_classes = num_classes\n self.num_samples = num_samples\n\n self.molecule_generator = MoleculeGenerator(num_classes=num_classes, \n max_length=max_length, \n ambiguity=ambiguity,\n num_bondtypes=num_bondtypes)\n\n self.corruption = CorruptionTransform(num_masks=num_masks, num_fake=num_fake, epsilon=epsilon_greedy)\n\n\n self.data = []\n\n\n for i in range(self.num_samples):\n molecule = self.molecule_generator.generate_molecule()\n molecule = chem.AddHs(molecule)\n\n\n Adj = chem.rdmolops.GetAdjacencyMatrix(molecule)\n atoms = np.asarray([periodic_table[atom.GetAtomicNum()] for atom in molecule.GetAtoms()])\n smiles = chem.MolToSmiles(molecule)\n self.data += [MoleculeSample(atoms, Adj, {}, smiles)]","def test_validation_wrong_molecules():\n paths = examples_paths()\n paths['wrongformat'] = utils.get_data_filename(os.path.join('tests', 'data', 'README.md'))\n molecules = [\n {'antechamber': {'charge_method': 'bcc'}},\n {'filepath': paths['wrongformat']},\n {'name': 'p-xylene', 'antechamber': {'charge_method': 'bcc'}, 'unknown': 4},\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'}},\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'invalid'},\n 'antechamber': {'charge_method': None}},\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'},\n 'antechamber': {'charge_method': 'bcc'}},\n {'filepath': 'nonexistentfile.pdb', 'leap': {'parameters': 'leaprc.ff14SB'}},\n {'filepath': paths['toluene'], 'smiles': 'Cc1ccccc1'},\n {'filepath': paths['toluene'], 'strip_protons': True},\n {'filepath': paths['abl'], 'leap': {'parameters': 'oldff/leaprc.ff14SB'}, 'epik': {'select': 0}},\n {'name': 'toluene', 'epik': 0},\n {'name': 'toluene', 'epik': {'tautomerize': 6}},\n {'name': 'toluene', 'epik': {'extract_range': 1}},\n {'name': 'toluene', 'smiles': 'Cc1ccccc1'},\n {'name': 3},\n {'smiles': 'Cc1ccccc1', 'select': 1},\n {'name': 'Cc1ccccc1', 'select': 1},\n {'filepath': paths['abl'], 'leap': {'parameters': 'oldff/leaprc.ff14SB'}, 'select': 'notanoption'},\n {'filepath': paths['abl'], 'regions': 5},\n {'filepath': paths['abl'], 'regions': {'a_region': [-56, 5.23]}},\n {'filepath': paths['toluene'], 'leap': {'parameters': 'leaprc.gaff'}, 'strip_protons': True},\n ]\n for molecule in molecules:\n yield assert_raises, YamlParseError, ExperimentBuilder._validate_molecules, {'mol': molecule}","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def test_get_thermo_data_mopac(self):\n output_directory = os.path.join(self.mop1.settings.fileStore, '..', '..')\n self.mop1.set_default_output_directory(output_directory)\n self.mop2.set_default_output_directory(output_directory)\n self.mop3.set_default_output_directory(output_directory)\n\n mol = Molecule().from_smiles('C1=CC=C2C=CC=CC2=C1')\n\n for directory in (self.mop1.settings.fileStore, self.mop1.settings.scratchDirectory):\n shutil.rmtree(directory, ignore_errors=True)\n\n for directory in (self.mop2.settings.fileStore, self.mop2.settings.scratchDirectory):\n shutil.rmtree(directory, ignore_errors=True)\n\n for directory in (self.mop3.settings.fileStore, self.mop3.settings.scratchDirectory):\n shutil.rmtree(directory, ignore_errors=True)\n\n thermo1 = self.mop1.get_thermo_data(mol)\n thermo2 = self.mop2.get_thermo_data(mol)\n thermo3 = self.mop3.get_thermo_data(mol)\n\n self.assertTrue(thermo1.comment.startswith('QM MopacMolPM3'))\n self.assertTrue(thermo2.comment.startswith('QM MopacMolPM6'))\n self.assertTrue(thermo3.comment.startswith('QM MopacMolPM7'))\n\n self.assertAlmostEqual(thermo1.H298.value_si, 169708.0608, 1) # to 1 decimal place\n self.assertAlmostEqual(thermo1.S298.value_si, 334.5007584, 1) # to 1 decimal place\n self.assertAlmostEqual(thermo2.H298.value_si, 167704.4270, 1) # to 1 decimal place\n self.assertAlmostEqual(thermo2.S298.value_si, 338.0999241, 1) # to 1 decimal place\n self.assertAlmostEqual(thermo3.H298.value_si, 166168.8571, 1) # to 1 decimal place\n self.assertAlmostEqual(thermo3.S298.value_si, 336.3330406, 1) # to 1 decimal place","def molecule_data(self) -> Union[QMolecule, WatsonHamiltonian]:\n return self._molecule_data","def test_generate_random_container_list():\n random_container = main.generate_random_container(10, 100, False)\n assert len(random_container) == 10","def test_chemistries():\n chems = [\n utils.Chemistry(\n potion_map=stones_and_potions.all_fixed_potion_map(),\n stone_map=stones_and_potions.all_fixed_stone_map(),\n graph=graphs.create_graph_from_constraint(\n graphs.no_bottleneck_constraints()[0]),\n rotation=np.eye(3)),\n utils.Chemistry(\n potion_map=stones_and_potions.PotionMap([1, 0, 2], [1, 1, -1]),\n stone_map=stones_and_potions.StoneMap(np.array([-1, 1, -1])),\n graph=graphs.create_graph_from_constraint(\n graphs.bottleneck1_constraints()[0]),\n rotation=stones_and_potions.possible_rotations()[-1])]\n for r in stones_and_potions.possible_rotations():\n for sm in stones_and_potions.possible_stone_maps():\n chems.append(utils.Chemistry(\n potion_map=stones_and_potions.all_fixed_potion_map(),\n stone_map=sm,\n graph=graphs.create_graph_from_constraint(\n graphs.no_bottleneck_constraints()[0]),\n rotation=r))\n return chems","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def _result_wrapper(self, result, _pymatgen) -> List[ase.atoms.Atoms]:\n if _pymatgen:\n _, fname = tempfile.mkstemp(text=True)\n with open(fname, \"w\") as f:\n f.write(result.to(\"poscar\"))\n return ase.io.read(fname, index=':', format=\"vasp\")\n else:\n import json\n result = json.load(result)\n if result[\"valid_response\"]:\n _, fname = tempfile.mkstemp(text=True)\n with open(fname, \"w\") as f:\n f.write(result[\"response\"][0][\"cif\"])\n return ase.io.read(fname, index=':', format=\"cif\")\n elif not result[\"api_key_valid\"]:\n raise ValueError(f\"Invalid API_KEY: {self.API_KEY}. Check your API_KEY at https://www.materialsproject.org/open!\")","def test_molecules_from_xyz(self):\n s_mol, b_mol = converter.molecules_from_xyz(self.xyz6['dict'])\n\n # check that the atom order is the same\n self.assertTrue(s_mol.atoms[0].is_sulfur())\n self.assertTrue(b_mol.atoms[0].is_sulfur())\n self.assertTrue(s_mol.atoms[1].is_oxygen())\n self.assertTrue(b_mol.atoms[1].is_oxygen())\n self.assertTrue(s_mol.atoms[2].is_oxygen())\n self.assertTrue(b_mol.atoms[2].is_oxygen())\n self.assertTrue(s_mol.atoms[3].is_nitrogen())\n self.assertTrue(b_mol.atoms[3].is_nitrogen())\n self.assertTrue(s_mol.atoms[4].is_carbon())\n self.assertTrue(b_mol.atoms[4].is_carbon())\n self.assertTrue(s_mol.atoms[5].is_hydrogen())\n self.assertTrue(b_mol.atoms[5].is_hydrogen())\n self.assertTrue(s_mol.atoms[6].is_hydrogen())\n self.assertTrue(b_mol.atoms[6].is_hydrogen())\n self.assertTrue(s_mol.atoms[7].is_hydrogen())\n self.assertTrue(b_mol.atoms[7].is_hydrogen())\n self.assertTrue(s_mol.atoms[8].is_hydrogen())\n self.assertTrue(b_mol.atoms[8].is_hydrogen())\n self.assertTrue(s_mol.atoms[9].is_hydrogen())\n self.assertTrue(b_mol.atoms[9].is_hydrogen())\n\n s_mol, b_mol = converter.molecules_from_xyz(self.xyz7['dict'])\n self.assertTrue(s_mol.atoms[0].is_oxygen())\n self.assertTrue(b_mol.atoms[0].is_oxygen())\n self.assertTrue(s_mol.atoms[2].is_carbon())\n self.assertTrue(b_mol.atoms[2].is_carbon())\n\n expected_bonded_adjlist = \"\"\"multiplicity 2\n1 O u0 p2 c0 {6,S} {10,S}\n2 O u0 p2 c0 {3,S} {28,S}\n3 C u0 p0 c0 {2,S} {8,S} {14,S} {15,S}\n4 C u0 p0 c0 {7,S} {16,S} {17,S} {18,S}\n5 C u0 p0 c0 {7,S} {19,S} {20,S} {21,S}\n6 C u0 p0 c0 {1,S} {22,S} {23,S} {24,S}\n7 C u1 p0 c0 {4,S} {5,S} {9,S}\n8 C u0 p0 c0 {3,S} {10,D} {11,S}\n9 C u0 p0 c0 {7,S} {11,D} {12,S}\n10 C u0 p0 c0 {1,S} {8,D} {13,S}\n11 C u0 p0 c0 {8,S} {9,D} {25,S}\n12 C u0 p0 c0 {9,S} {13,D} {26,S}\n13 C u0 p0 c0 {10,S} {12,D} {27,S}\n14 H u0 p0 c0 {3,S}\n15 H u0 p0 c0 {3,S}\n16 H u0 p0 c0 {4,S}\n17 H u0 p0 c0 {4,S}\n18 H u0 p0 c0 {4,S}\n19 H u0 p0 c0 {5,S}\n20 H u0 p0 c0 {5,S}\n21 H u0 p0 c0 {5,S}\n22 H u0 p0 c0 {6,S}\n23 H u0 p0 c0 {6,S}\n24 H u0 p0 c0 {6,S}\n25 H u0 p0 c0 {11,S}\n26 H u0 p0 c0 {12,S}\n27 H u0 p0 c0 {13,S}\n28 H u0 p0 c0 {2,S}\n\"\"\"\n expected_mol = Molecule().from_adjacency_list(expected_bonded_adjlist)\n self.assertEqual(b_mol.to_adjacency_list(), expected_bonded_adjlist)\n # the is_isomorphic test must come after the adjlist test since it changes the atom order\n self.assertTrue(b_mol.is_isomorphic(expected_mol))\n\n s_mol, b_mol = converter.molecules_from_xyz(self.xyz10['dict'], multiplicity=1, charge=0)\n self.assertIsNotNone(s_mol)\n self.assertIsNotNone(b_mol)\n for atom1, atom2 in zip(s_mol.atoms, b_mol.atoms):\n self.assertEqual(atom1.symbol, atom2.symbol)\n for atom1, symbol in zip(s_mol.atoms, self.xyz10['dict']['symbols']):\n self.assertEqual(atom1.symbol, symbol)\n\n s_mol, b_mol = converter.molecules_from_xyz(self.xyz_dict_13, multiplicity=1, charge=0)\n for atom1, atom2 in zip(s_mol.atoms, b_mol.atoms):\n self.assertEqual(atom1.symbol, atom2.symbol)\n for atom1, symbol in zip(s_mol.atoms, self.xyz_dict_13['symbols']):\n self.assertEqual(atom1.symbol, symbol)\n self.assertEqual(s_mol.multiplicity, 1)\n self.assertEqual(b_mol.multiplicity, 1)\n self.assertFalse(any(atom.radical_electrons for atom in b_mol.atoms))","def test_rackspace_uploader_get_container(self, mock1):\r\n with patch('pybossa.uploader.rackspace.pyrax.cloudfiles') as mycf:\r\n cdn_enabled_mock = PropertyMock(return_value=False)\r\n type(fake_container).cdn_enabled = cdn_enabled_mock\r\n mycf.get_container.side_effect = NoSuchContainer\r\n\r\n calls = [call.get_container('user_3'),\r\n call.create_container('user_3'),\r\n call.make_container_public('user_3')\r\n ]\r\n u = RackspaceUploader()\r\n u.init_app(self.flask_app)\r\n assert u.get_container('user_3')\r\n mycf.assert_has_calls(calls, any_order=True)","def __init__(self, struct_filename, name='molecules', cutoff=None, num_sampled_shards=None, max_num_atoms=None):\n \n print('Loading',name,'set')\n self.name = name\n \n sharded_ds = shard.Sharded.load(struct_filename)\n num_shards = sharded_ds.get_num_shards()\n \n self.num_atoms = []\n self.symbols = []\n self.charges = []\n self.positions = []\n self.index = []\n self.data = []\n self.data_keys = ['label'] # only one property here\n \n # Define indices and subsample if necessary \n shard_indices = np.arange(num_shards)\n if num_sampled_shards is not None and num_sampled_shards < num_shards:\n shard_indices = np.random.choice(shard_indices, size=num_sampled_shards, replace=False, p=None)\n \n for shard_idx in shard_indices:\n \n struct_df = sharded_ds.read_shard(shard_idx)\n labels_df = sharded_ds.read_shard(shard_idx, 'labels')\n ensembles = labels_df['ensemble']\n\n for i, code in enumerate(ensembles):\n\n new_struct = struct_df[struct_df.ensemble==code]\n new_labels = labels_df['label'][i]\n\n muta_chain = labels_df['chain'][i]\n muta_resid = labels_df['residue'][i]\n\n # select the local environment of the mutated residue\n sel_struct = select_environment(new_struct,muta_chain,muta_resid,cutoff)\n print(code, len(new_struct),len(sel_struct))\n\n # move on with the next structure if this one is too large\n if max_num_atoms is not None and len(sel_struct) > max_num_atoms:\n continue\n\n subunits = sel_struct.subunit.unique()\n for j, sub in enumerate(subunits):\n\n sub_df = sel_struct[sel_struct.subunit == sub]\n sub_df = sub_df.reset_index(drop=True)\n\n # get element symbols\n new_symbols = [ elem.title() for elem in sub_df.element ]\n\n # get atomic numbers\n new_atnums = np.array([ pte.GetAtomicNumber(e.title()) for e in sub_df.element ])\n # extract coordinates\n conf_coord = dt.get_coordinates_from_df(sub_df)\n \n # append everything\n self.symbols.append(new_symbols)\n self.charges.append(new_atnums)\n self.positions.append(conf_coord)\n self.num_atoms.append(len(new_atnums))\n\n self.data.append(new_labels) # There will be twice as many structures as labels (order matters!!!)\n \n return","def test_shared_wires(self):\n wires = range(2)\n estimation_wires = range(1, 3)\n\n with pytest.raises(ValueError, match=\"No wires can be shared between the wires\"):\n quantum_monte_carlo(\n lambda: None, wires=wires, target_wire=0, estimation_wires=estimation_wires\n )","def test_get_mass(self):\n self.assertEqual(get_element_mass(1), (1.00782503224, 1)) # test input by integer\n self.assertEqual(get_element_mass('Si'), (27.97692653465, 14)) # test string input and most common isotope\n self.assertEqual(get_element_mass('C', 13), (13.00335483507, 6)) # test specific isotope\n self.assertEqual(get_element_mass('Bk'), (247.0703073, 97)) # test a two-element array (no isotope data)","def test_return_residue_pipe_fail(self):\n\n # Try to get a residue from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')","def test_read_mol_input():\n # good input\n read_mol_input(os.path.join(TEST_DIR, \"example_mol_input_file.txt\"))\n # good input with extra spaces\n read_mol_input(os.path.join(TEST_DIR, \"example2_mol_input_file.txt\"))\n # no such file error\n assert_raises(FileNotFoundError, read_mol_input, 'no-such-file')\n # qcm appears twice\n assert_raises(ValueError, read_mol_input, os.path.join(TEST_DIR, \"bad1_mol_input_file.txt\"))\n # missing struct type\n assert_raises(ValueError, read_mol_input, os.path.join(TEST_DIR, \"bad2_mol_input_file.txt\"))","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_single_molecules_cycle_one(self, single_mol_system):\n sequence = \"A\"\n expected = [sequence] * (5 * 3)\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def _pyscf_molecule_object(basis, labels, coords):\n mol = pyscf.gto.Mole(atom=zip(labels, coords),\n unit=\"bohr\",\n basis=basis)\n mol.build()\n return mol","def test_call_wrapped_function(self):\r\n\r\n # adapted from test_app.test_cd_hit.test_cdhit_clusters_from_seqs\r\n\r\n exp = {'0': 'R27DLI_4812',\r\n '1': 'U1PLI_7889',\r\n '2': 'W3Cecum_4858',\r\n '3': 'R27DLI_3243',\r\n }\r\n app = GenericRepSetPicker(params={'Algorithm': 'most_abundant',\r\n 'ChoiceF': make_most_abundant, 'ChoiceFRequiresSeqs': True})\r\n obs = app(self.tmp_seq_filepath, self.tmp_otu_filepath)\r\n self.assertEqual(obs, exp)","def test_molecule_venv(host):\n\n assert \"molecule\" in host.pip_package.get_packages(\n pip_path=\"/opt/virtualenv/molecule/bin/pip\"\n )\n molecule_command = host.run(molecule_test_command)\n\n assert molecule_command.rc == 0\n assert \"2.22\" in molecule_command.stdout","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_set_molecule_error(self):\n mol = Molecule.from_smiles(\"CCO\")\n atom = Atom(6, 0, False)\n atom.molecule = mol\n with pytest.raises(AssertionError, match=\"already has an associated molecule\"):\n atom.molecule = mol","def test_validation_correct_molecules():\n paths = examples_paths()\n molecules = [\n {'name': 'toluene', 'leap': {'parameters': 'leaprc.gaff'}},\n {'name': 'toluene', 'leap': {'parameters': ['leaprc.gaff', 'toluene.frcmod']}},\n {'name': 'p-xylene', 'antechamber': {'charge_method': 'bcc'}},\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'},\n 'antechamber': {'charge_method': None}},\n {'name': 'p-xylene', 'antechamber': {'charge_method': 'bcc'},\n 'epik': {'ph': 7.6, 'ph_tolerance': 0.7, 'tautomerize': False, 'select': 0}},\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'},\n 'antechamber': {'charge_method': None}, 'epik': {'select': 1}},\n\n {'filepath': paths['abl']},\n {'filepath': paths['abl'], 'leap': {'parameters': 'leaprc.ff99SBildn'}},\n {'filepath': paths['abl'], 'leap': {'parameters': 'leaprc.ff99SBildn'}, 'select': 1},\n {'filepath': paths['abl'], 'select': 'all'},\n {'filepath': paths['abl'], 'select': 'all', 'strip_protons': True},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {}},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'add_missing_residues': True}},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'add_missing_atoms': 'all', 'ph': '8.0'}},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'remove_heterogens': 'all'}},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'replace_nonstandard_residues': True}},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'apply_mutations': {'chain_id': 'A', 'mutations': 'T85I'}}},\n {'filepath': paths['abl'], 'select': 'all', 'modeller': {'apply_mutations': {'chain_id': 'A', 'mutations': 'T85I'}}},\n {'filepath': paths['abl'], 'select': 'all', 'modeller': {'apply_mutations': {'chain_id': 'A', 'mutations': 'WT'}}},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'apply_mutations': {'chain_id': 'A', 'mutations': 'I8A/T9A'}}},\n {'filepath': paths['toluene'], 'leap': {'parameters': 'leaprc.gaff'}},\n {'filepath': paths['benzene'], 'epik': {'select': 1, 'tautomerize': False}},\n # Regions tests, make sure all other combos still work\n {'name': 'toluene', 'regions': {'a_region': 4}},\n {'name': 'toluene', 'regions': {'a_region': 'dsl string'}},\n {'name': 'toluene', 'regions': {'a_region': [0, 2, 3]}},\n {'name': 'toluene', 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}},\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': 4}},\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': 'dsl string'}},\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': [0, 2, 3]}},\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}},\n {'filepath': paths['abl'], 'regions': {'a_region': 4}},\n {'filepath': paths['abl'], 'regions': {'a_region': 'dsl string'}},\n {'filepath': paths['abl'], 'regions': {'a_region': [0, 2, 3]}},\n {'filepath': paths['abl'], 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}},\n {'filepath': paths['toluene'], 'regions': {'a_region': 4}},\n {'filepath': paths['toluene'], 'regions': {'a_region': 'dsl string'}},\n {'filepath': paths['toluene'], 'regions': {'a_region': [0, 2, 3]}},\n {'filepath': paths['toluene'], 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}}\n ]\n for molecule in molecules:\n yield ExperimentBuilder._validate_molecules, {'mol': molecule}","def test_get_composition(self):\n pass","def test_get_molecule_least_similar_to(self):\n csv_fpath = self.smiles_seq_to_xl_or_csv(ftype=\"csv\")\n for descriptor in SUPPORTED_FPRINTS:\n for similarity_measure in SUPPORTED_SIMILARITIES:\n molecule_set = MoleculeSet(\n molecule_database_src=csv_fpath,\n molecule_database_src_type=\"csv\",\n fingerprint_type=descriptor,\n similarity_measure=similarity_measure,\n is_verbose=False,\n )\n for mol_smile, mol in zip(TEST_SMILES,\n molecule_set.molecule_database):\n compare_task = CompareTargetMolecule(\n target_molecule_smiles=mol_smile)\n [furthest_mol], [similarity] = compare_task.\\\n get_hits_dissimilar_to(molecule_set)\n mol_similarities = molecule_set.compare_against_molecule(\n mol)\n self.assertEqual(\n np.min(mol_similarities),\n mol.get_similarity_to(\n molecule_set.molecule_database[furthest_mol],\n molecule_set.similarity_measure\n ),\n f\"Expected furthest mol to have minimum \"\n f\"similarity to target molecule \"\n f\"using similarity measure: {similarity_measure}, \"\n f\"descriptor: {descriptor}, \"\n f\"for molecule {mol.mol_text}\",\n )\n self.assertGreaterEqual(similarity, 0.,\n \"Expected similarity value to \"\n \"be >= 0.\"\n f\"using similarity measure: \"\n f\"{similarity_measure}, \"\n f\"descriptor: {descriptor}, \"\n f\"for molecule {mol.mol_text}\")\n self.assertLessEqual(similarity, 1.,\n \"Expected similarity value to \"\n \"be <= 1.\"\n f\"using similarity measure: \"\n f\"{similarity_measure}, \"\n f\"descriptor: {descriptor}, \"\n f\"for molecule {mol.mol_text}\"\n )","def _vmd_script_molecule(mole, filename=\"molecule.xyz\"):\n output = \"# load new molecule\\n\"\n if len(mole.atom) == 0:\n raise ValueError(\"Need at least one molecule file with coordinates.\")\n atoms = mole.atom\n natoms = len(mole.atom[0:, 0])\n f = open(filename, \"w\")\n f.write(str(natoms) + \"\\n\\n\")\n for i in range(0, natoms):\n symb = str(atoms[i, 0])\n coord = \" \".join(map(str, atoms[i, 1].tolist()))\n f.write(symb + \" \" + coord + \"\\n\")\n f.close()\n output += (\n \"mol {0} {1} type {2} first 0 last -1 step 1 filebonds 1 autobonds 1 waitfor all\"\n \"\\n\".format(\"new\", filename, \"{xyz}\")\n )\n output += \"#\\n\" \"# representation of the atoms\\n\"\n output += \"mol representation CPK 1.000000 0.300000 118.000000 131.000000\\n\"\n output += (\n \"mol delrep 0 top\\n\"\n \"mol color Element\\n\"\n \"mol selection {{all}}\\n\"\n \"mol material Opaque\\n\"\n \"mol addrep top\\n\"\n \"#\\n\"\n )\n return output","def fetchCooler(c, regions, coolerFetch = lambda coo, ext:coo.matrix(balance=True, sparse=True).fetch(ext),\n mask=True, force=False, ):\n regions = [list(i) for i in regions]\n resolution = c.binsize\n\n for i in regions:\n if i[1] == None:\n i[1] = 0 \n if i[2] == None:\n i[2] = c.chromsizes[i[0]]\n\n \n for a in regions: \n if str(a[0]) not in c.chromnames:\n raise ValueError(\"Chromosome {0} from regions not found in cooler\".format(a))\n if (a[1] % resolution) != 0:\n raise ValueError(\"Start of an region should be a multiple fo resolution\")\n \n# bins = c.bins()[:]\n \n# # managing masks \n# if mask is False: \n# bins[\"mask\"] = 1 \n# elif mask is None:\n# assert \"mask\" in bins.columns\n# elif mask is True: \n# pass \n# elif callable(mask):\n# pass \n# else:\n# bins[\"mask\"] = mask \n \n \n for region in regions:\n matrix = coolerFetch(c, region)\n try: # setting matrix nans to zeros.\n matrix.data = np.nan_to_num(matrix.data, copy=False)\n except TypeError: #workaround for old numpy versions\n matrix.data = np.nan_to_num(matrix.data)\n# st,end = c.extent(region)\n# subbins = bins[st:end].copy()\n if mask is True: \n newmask = np.array((matrix.sum(axis=0) > 0 ))[0]\n# if callable(mask):\n# new_mask = mask(matrix)\n# subbins[\"mask\"] = newmask \n\n assert len(newmask) == matrix.shape[0]\n\n yield matrix, newmask","def test_compute_partial_charges(self):\n # TODO: Test only one molecule for speed?\n # TODO: Do we need to deepcopy each molecule, or is setUp called separately for each test method?\n import numpy as np\n from simtk import unit\n\n # Do not modify original molecules.\n molecules = copy.deepcopy(mini_drug_bank())\n\n # Test a single toolkit at a time\n # Removed ['amber', 'amberff94'] from OE list, as those won't find the residue types they're expecting\n toolkit_to_charge_method = {\n OpenEyeToolkitWrapper: [\n \"mmff\",\n \"mmff94\",\n \"am1bcc\",\n \"am1bccnosymspt\",\n \"am1bccelf10\",\n ],\n AmberToolsToolkitWrapper: [\"bcc\", \"gas\", \"mul\"],\n }\n\n manual_skips = []\n\n manual_skips.append(\n \"ZINC1564378\"\n ) # Warning: OEMMFF94Charges: assigning OEMMFFAtomTypes failed on mol .\n manual_skips.append(\n \"ZINC00265517\"\n ) # Warning: OEMMFF94Charges: assigning OEMMFFAtomTypes failed on mol .\n\n for toolkit in list(toolkit_to_charge_method.keys()):\n toolkit_registry = ToolkitRegistry(toolkit_precedence=[toolkit])\n for charge_model in toolkit_to_charge_method[toolkit]:\n c = 0\n for molecule in molecules[:1]: # Just test first molecule to save time\n c += 1\n if molecule.name in manual_skips: # Manual skips, hopefully rare\n continue\n molecule.compute_partial_charges(\n charge_model=charge_model, toolkit_registry=toolkit_registry\n )\n charges1 = molecule._partial_charges\n # Make sure everything isn't 0s\n assert (abs(charges1 / unit.elementary_charge) > 0.01).any()\n # Check total charge\n charges_sum_unitless = charges1.sum() / unit.elementary_charge\n # if abs(charges_sum_unitless - float(molecule.total_charge)) > 0.0001:\n # print('c {} molecule {} charge_sum {} molecule.total_charge {}'.format(c, molecule.name,\n # charges_sum_unitless,\n # molecule.total_charge))\n # assert_almost_equal(charges_sum_unitless, molecule.total_charge, decimal=4)\n\n # Call should be faster second time due to caching\n # TODO: Implement caching\n molecule.compute_partial_charges(\n charge_model=charge_model, toolkit_registry=toolkit_registry\n )\n charges2 = molecule._partial_charges\n assert np.allclose(charges1, charges2, atol=0.002)","def fixture_output_block():\n return Mock()","def test_sample_container_init(self):\n self.assertEqual({}, self.container._data)","def mol_from_cbor(cbor_str: str) -> masm.Molecule:\n serializer = masm.JsonSerialization\n cbor_binary = serializer.base_64_decode(cbor_str)\n cbor_format = serializer.BinaryFormat.CBOR\n serialization = serializer(cbor_binary, cbor_format)\n return serialization.to_molecule()","def __init__(self, nr_molecules, surface_size):\n self.molecules = []\n for i in range(nr_molecules):\n self.try_add_molecule(100, surface_size)\n print(\"nr_molecules:\", len(self.molecules))","def test_input_sanity():\n energy = MagicMock()\n\n with raises(NotImplementedError) as exception:\n MonteCarlo(sum, [1, 1, 1], 0e0)\n with raises(ValueError) as exception:\n MonteCarlo(energy, [1, 1, 1], temperature=-1e0)\n\n with raises(TypeError) as exception:\n MonteCarlo(energy, [1.0, 2, 3])\n with raises(ValueError) as exception:\n MonteCarlo(energy, [-1, 2, 3])\n with raises(ValueError) as exception:\n MonteCarlo(energy, [[1, 2, 3], [3, 4, 5]])\n with raises(ValueError) as exception:\n MonteCarlo(energy, [3])\n with raises(ValueError) as exception:\n MonteCarlo(energy, [0, 0])","def test_package_1():\n\n @package\n def resdiv(gnd, vin, vout):\n res = Part(\"Device\", \"R\", dest=TEMPLATE)\n r1 = res(value=\"1k\")\n r2 = res(value=\"500\")\n\n cap = Part(\"Device\", \"C\", dest=TEMPLATE)\n c1 = cap()\n c2 = cap(value=\"1uF\")\n\n bus1 = Bus(\"BB\", 10)\n\n vin += r1[1], c1[1] # Connect the input to the first resistor.\n gnd += r2[2], c2[2] # Connect the second resistor to ground.\n vout += (\n r1[2],\n c1[2],\n r2[1],\n c2[1],\n ) # Output comes from the connection of the two resistors.\n\n resdiv1 = resdiv()\n resdiv2 = resdiv()\n\n vin, vout, gnd = Net(\"VI\"), Net(\"VO\"), Net(\"GND\")\n\n resdiv1.gnd += gnd\n resdiv1.vin += vin\n resdiv1.vout += vout\n\n resdiv2[\"gnd\"] += gnd\n resdiv2[\"vin\"] += vin\n resdiv2[\"vout\"] += vout\n\n gnd += Pin()\n vin += Pin()\n\n default_circuit.instantiate_packages()\n\n assert len(Net.fetch(\"GND\")) == 5\n assert len(Net.fetch(\"VI\")) == 5\n assert len(Net.fetch(\"VO\")) == 8\n\n assert len(resdiv1.gnd) == 5\n assert len(resdiv1.vin) == 5\n assert len(resdiv1.vout) == 8\n\n assert len(resdiv2[\"gnd\"]) == 5\n assert len(resdiv2[\"vin\"]) == 5\n assert len(resdiv2[\"vout\"]) == 8","def getStructureType(entry, seed_index=0, supercell = 2,return_SS=False):\n \n \n # Entry is a list of the necessary components of the TSA. \n # Makes it easier to parallelize\n structure, tol, mp_id = entry\n norm_tol=tol-1\n\n s = copy.deepcopy(structure)\n heterogeneous = False\n heterogeneous_SS = False\n\n # Distance matrix (rowA, columnB) shows distance between\n # atoms A and B, taking PBCs into account.\n \n binary_matrix = getDistMat(s,norm_tol)\n cluster = buildNetwork(binary_matrix,seed_index)\n\n compo = Composition.from_dict(Counter([s[l].specie.name for \n l in list(cluster)]))\n if compo.reduced_formula != s.composition.reduced_formula:\n # i.e. the cluster does not have the same composition\n # as the overall crystal; therefore there are other\n # clusters of varying composition.\n heterogeneous = True\n og_cluster = set()\n og_cluster.update(cluster)\n old_cluster_size = len(cluster)\n # Increase structure to determine dimensionality\n\n s = copy.deepcopy(structure)\n s.make_supercell(supercell)\n seed_index*=supercell**3\n\n\n\n binary_matrix = getDistMat(s,norm_tol)\n cluster = buildNetwork(binary_matrix,seed_index)\n\n\n if cluster!=set():\n new_cluster_size = len(cluster)\n # Get ratio of original and final cluster lengths\n scale = new_cluster_size/old_cluster_size\n compo = Composition.from_dict(Counter([s[l].specie.name for l in\n list(cluster)]))\n if compo.reduced_formula != s.composition.reduced_formula:\n # i.e. the cluster does not have the same composition\n # as the overall crystal; therefore there are other\n # clusters of varying composition.\n heterogeneous_SS = True\n motiif = getDim(scale,supercell)\n if heterogeneous or heterogeneous_SS:\n motiif += \"_heter\"\n\n if return_SS:\n return [motiif,mp_id,tol,compo.reduced_formula,list(cluster)]\n else:\n return [motiif,mp_id,tol,compo.reduced_formula,list(og_cluster)]","def mock_component():\n component = Mock()\n component.free_parameters = flex.double([1.0])\n component.free_parameter_esds = None\n component.n_params = 1\n component.var_cov_matrix = sparse.matrix(1, 1)\n return component","def featurize(self):\n\n self.make_molecule()\n\n self.described_molecules = self.calculator.pandas(self.data.molecules)\n self.described_molecules.index = self.data.index\n\n self.described_molecules = pd.concat([self.data, self.described_molecules], axis=1)\n\n return self.described_molecules","def get_mol_info(self):\n return","def test_simulationRun(self):\n self.opt = { 'temperature' : 300.0, 'friction' : 1, 'dt' : 0.00002,\n 'nIter' : 2, 'nstepsNC' : 2, 'nstepsMD' : 1, 'nprop' : 1,\n 'nonbondedMethod' : 'NoCutoff', 'constraints': 'HBonds',\n 'trajectory_interval' : 1, 'reporter_interval' : 1,\n 'outfname' : 'mc-test',\n 'platform' : None,\n 'constraints' : 'HBonds',\n 'mc_per_iter' : 2 }\n\n structure = self.full_struct\n class SetRotationMove(RandomLigandRotationMove):\n def __init__(self, structure, resname='LIG'):\n super(SetRotationMove, self).__init__(structure, resname)\n\n def move(self, context):\n \"\"\"Function that performs a random rotation about the\n center of mass of the ligand.\n \"\"\"\n #TODO: check if we need to deepcopy\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\n\n self.positions = positions[self.atom_indices]\n self.center_of_mass = self.getCenterOfMass(self.positions, self.masses)\n reduced_pos = self.positions - self.center_of_mass\n\n # Define random rotational move on the ligand\n #set rotation so that test is reproducible\n set_rotation_matrix = np.array([[-0.62297988, -0.17349253, 0.7627558 ],\n [ 0.55082352, -0.78964857, 0.27027502],\n [ 0.55541834, 0.58851973, 0.58749893]])\n\n\n #set_rotation_matrix = np.array([[1, 0, 0],\n # [0, 1, 0],\n # [0, 0, 1]])\n\n #multiply lig coordinates by rot matrix and add back COM translation from origin\n rot_move = np.dot(reduced_pos, set_rotation_matrix) * positions.unit + self.center_of_mass\n\n # Update ligand positions in nc_sim\n for index, atomidx in enumerate(self.atom_indices):\n positions[atomidx] = rot_move[index]\n context.setPositions(positions)\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\n self.positions = positions[self.atom_indices]\n return context\n\n\n self.model = SetRotationMove(structure, resname='ALA')\n #self.model = RandomLigandRotationMove(structure, resname='ALA')\n\n self.model.atom_indices = range(22)\n self.model.topology = structure[self.model.atom_indices].topology\n self.model.positions = structure[self.model.atom_indices].positions\n self.model.calculateProperties()\n\n self.mover = MoveEngine(self.model)\n #Initialize the SimulationFactory object\n sims = SimulationFactory(structure, self.mover, **self.opt)\n #print(sims)\n system = sims.generateSystem(structure, **self.opt)\n simdict = sims.createSimulationSet()\n alch_system = sims.generateAlchSystem(system, self.model.atom_indices)\n self.nc_sim = sims.generateSimFromStruct(structure, self.mover, alch_system, ncmc=True, **self.opt)\n self.model.calculateProperties()\n self.initial_positions = self.nc_sim.context.getState(getPositions=True).getPositions(asNumpy=True)\n mc_sim = Simulation(sims, self.mover, **self.opt)\n #monkeypatch to access acceptance value\n def nacceptRejectMC(self, temperature=300, **opt):\n \"\"\"Function that chooses to accept or reject the proposed move.\n \"\"\"\n md_state0 = self.current_state['md']['state0']\n md_state1 = self.current_state['md']['state1']\n log_mc = (md_state1['potential_energy'] - md_state0['potential_energy']) * (-1.0/self.nc_sim.context._integrator.kT)\n randnum = math.log(np.random.random())\n\n if log_mc > randnum:\n self.accept += 1\n print('MC MOVE ACCEPTED: log_mc {} > randnum {}'.format(log_mc, randnum) )\n self.md_sim.context.setPositions(md_state1['positions'])\n else:\n self.reject += 1\n print('MC MOVE REJECTED: log_mc {} < {}'.format(log_mc, randnum) )\n self.md_sim.context.setPositions(md_state0['positions'])\n self.log_mc = log_mc\n self.md_sim.context.setVelocitiesToTemperature(self.opt['temperature'])\n mc_sim.acceptRejectMC = nacceptRejectMC\n nacceptRejectMC.__get__(mc_sim)\n mc_sim.acceptRejectMC = types.MethodType(nacceptRejectMC, mc_sim)\n mc_sim.runMC(self.opt['nIter'])\n #get log acceptance\n print(mc_sim.log_mc)\n #if mc is working, should be around -24.1\n assert mc_sim.log_mc <= -23.8 and mc_sim.log_mc >= -24.3","def test_from_qcschema_no_client(self):\n\n import json\n\n # As the method can take a record instance or a dict with JSON encoding test both\n # test incomplete dict\n example_dict = {\"name\": \"CH4\"}\n with pytest.raises(KeyError):\n mol = Molecule.from_qcschema(example_dict)\n\n # test an object that is not a record\n wrong_object = \"CH4\"\n with pytest.raises(AttributeError):\n mol = Molecule.from_qcschema(wrong_object)\n\n with open(get_data_file_path(\"molecules/qcportal_molecules.json\")) as json_file:\n # test loading the dict representation from a json file\n json_mol = json.load(json_file)\n mol = Molecule.from_qcschema(json_mol)\n # now make a molecule from the canonical smiles and make sure they are isomorphic\n can_mol = Molecule.from_smiles(\n json_mol[\"attributes\"][\"canonical_isomeric_smiles\"]\n )\n assert mol.is_isomorphic_with(can_mol) is True","def test_from_qcschema_no_client(self):\n\n import json\n\n # As the method can take a record instance or a dict with JSON encoding test both\n # test incomplete dict\n example_dict = {\"name\": \"CH4\"}\n with pytest.raises(KeyError):\n mol = Molecule.from_qcschema(example_dict)\n\n # test an object that is not a record\n wrong_object = \"CH4\"\n with pytest.raises(AttributeError):\n mol = Molecule.from_qcschema(wrong_object)\n\n with open(get_data_file_path(\"molecules/qcportal_molecules.json\")) as json_file:\n # test loading the dict representation from a json file\n json_mol = json.load(json_file)\n mol = Molecule.from_qcschema(json_mol)\n # now make a molecule from the canonical smiles and make sure they are isomorphic\n can_mol = Molecule.from_smiles(\n json_mol[\"attributes\"][\"canonical_isomeric_smiles\"]\n )\n assert mol.is_isomorphic_with(can_mol) is True","def ReadMaterialInfoAndMakeMaterialsMolFiles(OutputPath,MaterialPathList,CutOff,Multiple,PDBCharges,MaterialInputFormat):\r\n\r\n MaterialInfoList=[]\r\n ID=0\r\n Time = time.strftime('%Y-%m-%d', time.localtime(time.time()))\r\n\r\n if os.path.exists(os.path.join(OutputPath,'Mols')): pass\r\n else: os.mkdir(os.path.join(OutputPath,'Mols'))\r\n\r\n for Range,MaterialPath in enumerate(MaterialPathList):\r\n\r\n\r\n AtomNum=0\r\n MaterialsCharge = 0.0\r\n MaterialInfo,ElementList,CellLength,CellAngle,AtomInfo,AtomInfoList,CellSize=[],[],[],[],[],[],[]\r\n\r\n MaterialName=os.path.splitext(MaterialPath.split('/')[-1])[0]\r\n MaterialInfo.append(MaterialName)\r\n MaterialNewName=re.sub('\\W','',MaterialName)\r\n\r\n if len(MaterialNewName) > 20:\r\n ID+=1\r\n MaterialNewName=MaterialNewName[:20]\r\n MaterialNewName=MaterialNewName+'_ID_'+str(ID)\r\n\r\n if MaterialInputFormat == 'pdb':\r\n with open(MaterialPath,'r') as File:\r\n with open(os.path.join(OutputPath,'Mols',MaterialNewName)+'.mol','w') as Mol:\r\n\r\n for Line in File.readlines():\r\n if Line[0:6] == 'CRYST1':\r\n CellLength.append(float('%.3f' % (float(Line[6:15].strip()))))\r\n CellLength.append(float('%.3f' % (float(Line[15:24].strip()))))\r\n CellLength.append(float('%.3f' % (float(Line[24:33].strip()))))\r\n CellAngle.append(float('%.2f' % (float(Line[33:40].strip()))))\r\n CellAngle.append(float('%.2f' % (float(Line[40:47].strip()))))\r\n CellAngle.append(float('%.2f' % (float(Line[47:54].strip()))))\r\n elif Line[0:6] == 'ATOM ':\r\n AtomNum += 1\r\n AtomInfo = []\r\n AtomInfo.append(int(Line[6:11].strip())) # serial\r\n AtomInfo.append(str(Line[12:16].strip())) # atom name\r\n AtomInfo.append(float(Line[30:38].strip())) # x\r\n AtomInfo.append(float(Line[38:46].strip())) # y\r\n AtomInfo.append(float(Line[46:54].strip())) # z\r\n\r\n if PDBCharges == True:\r\n AtomInfo.append(float(Line[54:60].strip())) # charge\r\n MaterialsCharge += float(Line[54:60].strip())\r\n else:\r\n AtomInfo.append(float('0.0')) # charge\r\n\r\n ElementList.append(str(Line[12:16].strip())) # atom name list\r\n AtomInfoList.append(AtomInfo)\r\n\r\n if abs(MaterialsCharge) < 0.001:\r\n Mol.write('# Basic Molecule Information\\n# Created by PyMSATm at %s\\n'\r\n 'Molecule_name: %s \\n\\nCoord_Info: Listed Cartesian None\\n' % (Time, MaterialNewName))\r\n else: Mol.write('# Basic Molecule Information\\n# Created by PyMSATm at %s\\n'\r\n 'Molecule_name: %s CHARGED\\n\\nCoord_Info: Listed Cartesian None\\n' % (Time, MaterialNewName))\r\n\r\n Mol.write(' %d\\n'%(AtomNum))\r\n\r\n for AtomInfo2 in AtomInfoList:\r\n Mol.write('{:<6d} {:>8} {:>8} {:>8} {:>6} {:>6} 0 0\\n'.format(AtomInfo2[0],\r\n AtomInfo2[2],AtomInfo2[3],AtomInfo2[4],AtomInfo2[1],AtomInfo2[5]))\r\n\r\n Mol.write('\\nFundcell_Info: Listed\\n%.5f %.5f %.5f\\n%.5f %.5f %.5f\\n0.00000 0.00000 0.00000\\n%.5f %.5f %.5f'%(CellLength[0],\r\n CellLength[1],CellLength[2],CellAngle[0],CellAngle[1],CellAngle[2],CellLength[0],CellLength[1],CellLength[2]))\r\n\r\n if MaterialInputFormat == 'mol':\r\n\r\n KeyOne,KeyTwo,KeyThree= False,False,False\r\n\r\n with open(MaterialPath, 'r') as File:\r\n with open(os.path.join(OutputPath, 'Mols', MaterialNewName) + '.mol', 'w') as Mol:\r\n\r\n for Line in File.readlines():\r\n if Line.strip(): # skip blank\r\n WordList = Line.strip().split()\r\n if WordList[0] == 'Coord_Info:':\r\n KeyOne = True\r\n elif WordList[0] == 'Fundcell_Info:':\r\n KeyOne = False\r\n KeyTwo = True\r\n elif len(WordList) > 1 and KeyOne == True:\r\n AtomNum += 1\r\n AtomInfo = []\r\n AtomInfo.append(int(WordList[0].strip())) # serial\r\n AtomInfo.append(str(WordList[4].strip())) # atom name\r\n AtomInfo.append(float(WordList[1].strip())) # x\r\n AtomInfo.append(float(WordList[2].strip())) # y\r\n AtomInfo.append(float(WordList[3].strip())) # z\r\n AtomInfo.append(float(WordList[5].strip())) # charge\r\n ElementList.append(str(WordList[4].strip())) # atom name list\r\n AtomInfoList.append(AtomInfo)\r\n MaterialsCharge += float(WordList[5].strip())\r\n elif len(WordList) > 1 and KeyTwo == True:\r\n KeyTwo = False\r\n KeyThree = True\r\n CellLength.append(float('%.3f' % (float(WordList[0].strip()))))\r\n CellLength.append(float('%.3f' % (float(WordList[1].strip()))))\r\n CellLength.append(float('%.3f' % (float(WordList[2].strip()))))\r\n elif len(WordList) > 1 and KeyThree == True:\r\n KeyThree = False\r\n CellAngle.append(float('%.2f' % (float(WordList[0].strip()))))\r\n CellAngle.append(float('%.2f' % (float(WordList[1].strip()))))\r\n CellAngle.append(float('%.2f' % (float(WordList[2].strip()))))\r\n\r\n if abs(MaterialsCharge) < 0.001:\r\n Mol.write('# Basic Molecule Information\\n# Created by PyMSATm at %s\\n'\r\n 'Molecule_name: %s \\n\\nCoord_Info: Listed Cartesian None\\n' % (\r\n Time, MaterialNewName))\r\n else:\r\n Mol.write('# Basic Molecule Information\\n# Created by PyMSATm at %s\\n'\r\n 'Molecule_name: %s CHARGED\\n\\nCoord_Info: Listed Cartesian None\\n' % (\r\n Time, MaterialNewName))\r\n\r\n Mol.write(' %d\\n' % (AtomNum))\r\n\r\n for AtomInfo2 in AtomInfoList:\r\n Mol.write('{:<6d} {:>8.4f} {:>8.4f} {:>8.4f} {:>8s} {:>10.6f} 0 0\\n'.format(AtomInfo2[0], AtomInfo2[2],\r\n AtomInfo2[3], AtomInfo2[4],\r\n AtomInfo2[1], AtomInfo2[5]))\r\n\r\n Mol.write(\r\n '\\nFundcell_Info: Listed\\n%.4f %.4f %.4f\\n%.4f %.4f %.4f\\n0.00000 0.00000 0.00000\\n%.4f %.4f %.4f' % (\r\n CellLength[0], CellLength[1], CellLength[2], CellAngle[0], CellAngle[1], CellAngle[2],\r\n CellLength[0], CellLength[1], CellLength[2]))\r\n\r\n if CellAngle[0] == 90.0 and CellAngle[1] == 90.0 and CellAngle[2] == 90.0:\r\n Orthogonality = True\r\n else: Orthogonality=False\r\n\r\n if Orthogonality == True:\r\n for Length in CellLength:\r\n Count = 1\r\n while Length * Count < CutOff * Multiple+1:\r\n Count += 1\r\n CellSize.append(str(Count))\r\n else: # definite the lengths of x, y, z in orthogonal directions\r\n\r\n SinA, SinB, SinC = math.sin(math.radians(CellAngle[0])), math.sin(math.radians(CellAngle[1])), math.sin(math.radians(CellAngle[2]))\r\n CosA, CosB, CosC = math.cos(math.radians(CellAngle[0])), math.cos(math.radians(CellAngle[1])), math.cos(math.radians(CellAngle[2]))\r\n CosParameterA = (CosC * CosA - CosB) / (SinC * SinA)\r\n SinParameterA = math.sqrt(1 - CosParameterA ** 2)\r\n CosParameterB = (CosA * CosB - CosC) / (SinA * SinB)\r\n SinParameterB = math.sqrt(1 - CosParameterB ** 2)\r\n CosParameterC = (CosB * CosC - CosA) / (SinB * SinC)\r\n SinParameterC = math.sqrt(1 - CosParameterC ** 2)\r\n x=CellLength[0]*SinC*SinParameterA\r\n y=CellLength[1]*SinA*SinParameterB\r\n z=CellLength[2]*SinB*SinParameterC\r\n TransLength=[x,y,z]\r\n\r\n for Length in TransLength:\r\n Count = 1\r\n while float(Length) * Count < CutOff * Multiple+1:\r\n Count += 1\r\n CellSize.append(str(Count))\r\n\r\n MaterialInfo.append(AtomNum)\r\n MaterialInfo.append(CellLength)\r\n MaterialInfo.append(CellAngle)\r\n MaterialInfo.append(CellSize)\r\n MaterialInfo.append(list(set(ElementList)))\r\n MaterialInfo.append(Orthogonality)\r\n MaterialInfo.append(MaterialNewName)\r\n MaterialInfoList.append(MaterialInfo)\r\n\r\n return MaterialInfoList","def testExecute(self):\n client = ICSClientFactory(self.config, 'slave', 'master') \n\n #Test reading and writing coils\n reply = client.execute(cst.READ_COILS, 10, 2)\n assert reply[0] == False \n assert reply[1] == False\n reply = client.execute(cst.WRITE_SINGLE_COIL, 10, 1, output_value=1)\n reply = client.execute(cst.READ_COILS, 10, 2)\n assert reply[0] == True\n assert reply[1] == False\n reply = client.execute(cst.WRITE_MULTIPLE_COILS, 10, 2,\n output_value=[0,1])\n reply = client.execute(cst.READ_COILS, 10, 2)\n assert reply[1] == True\n assert reply[0] == False\n \n #Test reading and writing input regs\n #reply = client.execute(cst.READ_INPUT_REGISTERS, 30002, 1)\n #print \"BRDEBUG: Reply: \", reply\n #assert reply[0] == 17\n\n #Test reading and setting holding regs\n reply = client.execute(cst.READ_HOLDING_REGISTERS, 40003, 2)\n #print \"BRDEBUG: Reply\", reply\n assert reply[0] == 16752 \n assert reply[1] == 0 \n reply = client.execute(cst.WRITE_SINGLE_REGISTER, 40003, 1,\n output_value = 10)\n reply = client.execute(cst.READ_HOLDING_REGISTERS, 40003, 1)\n #print \"BRDEBUG: Reply\", reply\n assert reply[0] == 10","def testExecute(self):\n client = ICSClientFactory(self.config, 'slave', 'master') \n\n #Test reading and writing coils\n reply = client.execute(cst.READ_COILS, 10, 2)\n assert reply[0] == False \n assert reply[1] == False\n reply = client.execute(cst.WRITE_SINGLE_COIL, 10, 1, output_value=1)\n reply = client.execute(cst.READ_COILS, 10, 2)\n assert reply[0] == True\n assert reply[1] == False\n reply = client.execute(cst.WRITE_MULTIPLE_COILS, 10, 2,\n output_value=[0,1])\n reply = client.execute(cst.READ_COILS, 10, 2)\n assert reply[1] == True\n assert reply[0] == False\n \n #Test reading and writing input regs\n #reply = client.execute(cst.READ_INPUT_REGISTERS, 30002, 1)\n #print \"BRDEBUG: Reply: \", reply\n #assert reply[0] == 17\n\n #Test reading and setting holding regs\n reply = client.execute(cst.READ_HOLDING_REGISTERS, 40003, 1)\n assert reply[0] == 15.0\n reply = client.execute(cst.WRITE_SINGLE_REGISTER, 40003, 1,\n output_value = 10)\n reply = client.execute(cst.READ_HOLDING_REGISTERS, 40003, 1)\n assert reply[0] == 10.0","def _make_mock_container_get(bad_config_names: list[str], folder: str = \"media\"):\n mount = {\n \"Type\": \"bind\",\n \"Source\": f\"/mnt/data/supervisor/{folder}\",\n \"Destination\": f\"/{folder}\",\n \"Mode\": \"rw\",\n \"RW\": True,\n \"Propagation\": \"rprivate\",\n }\n\n def mock_container_get(name):\n out = MagicMock()\n out.status = \"running\"\n out.attrs = {\"State\": {}, \"Mounts\": []}\n if name in bad_config_names:\n out.attrs[\"Mounts\"].append(mount)\n\n return out\n\n return mock_container_get","def meta_res(simulatedata_cbma, meta, random):\n _, (_, dataset) = simulatedata_cbma\n # CHECK IF META/KERNEL WORK TOGETHER\n ####################################\n meta_expectation = does_not_raise()\n\n with meta_expectation:\n res = meta.fit(dataset)\n # if creating the result failed (expected), do not continue\n if isinstance(meta_expectation, type(pytest.raises(ValueError))):\n pytest.xfail(\"this meta-analysis & kernel combo fails\")\n # instantiate meta-analysis estimator\n return res","def none_molecule() -> UniqueMolecule:\n return UniqueMolecule(rd_mol=Chem.MolFromSmiles(\"\"))","def test_run_read(self):\n\n self.ictrl[0] = 1 + 2 + 4 + 8\n vmec_f90wrap.runvmec(self.ictrl, self.filename, self.verbose, \\\n self.fcomm, reset_file)\n\n self.assertTrue(self.ictrl[1] in success_codes)\n\n self.assertEqual(vmec_f90wrap.vmec_input.nfp, 3)\n self.assertEqual(vmec_f90wrap.vmec_input.mpol, 4)\n self.assertEqual(vmec_f90wrap.vmec_input.ntor, 3)\n print('rbc.shape:', vmec_f90wrap.vmec_input.rbc.shape)\n print('rbc:',vmec_f90wrap.vmec_input.rbc[101:103, 0:4])\n\n # n = 0, m = 0:\n self.assertAlmostEqual(vmec_f90wrap.vmec_input.rbc[101,0], 1.3782)\n\n # n = 0, m = 1:\n self.assertAlmostEqual(vmec_f90wrap.vmec_input.zbs[101,1], 4.6465E-01)\n\n # n = 1, m = 1:\n self.assertAlmostEqual(vmec_f90wrap.vmec_input.zbs[102,1], 1.6516E-01)\n\n # Now try reading in the output\n wout_file = os.path.join(os.path.dirname(__file__), 'wout_li383_low_res.nc')\n ierr = 0\n vmec_f90wrap.read_wout_mod.read_wout_file(wout_file, ierr)\n self.assertEqual(ierr, 0)\n self.assertAlmostEqual(vmec_f90wrap.read_wout_mod.betatot, \\\n 0.0426215030653306, places=4)\n\n print('iotaf.shape:',vmec_f90wrap.read_wout_mod.iotaf.shape)\n print('rmnc.shape:',vmec_f90wrap.read_wout_mod.rmnc.shape)\n\n self.assertAlmostEqual(vmec_f90wrap.read_wout_mod.iotaf[-1], \\\n 0.654868168783638, places=4)\n\n self.assertAlmostEqual(vmec_f90wrap.read_wout_mod.rmnc[0, 0], \\\n 1.4773028173065, places=4)","def build_molecule(nresidues):\n molecule = vermouth.molecule.Molecule()\n residue_template = vermouth.molecule.Molecule()\n residue_template.add_nodes_from(\n (idx, {\"chain\": \"\", \"atomname\": str(idx), \"resname\": \"DUMMY\", \"resid\": 1})\n for idx in range(3)\n )\n for _ in range(nresidues):\n molecule.merge_molecule(residue_template)\n return molecule","def test_get_individual_entries_of_matrices_simulation_example():\n task = get_individual_entries_of_matrices(\n lambda_2=2,\n lambda_1_1=0.1,\n lambda_1_2=0.5,\n mu_1=2,\n mu_2=1,\n num_of_servers_1=2,\n num_of_servers_2=2,\n threshold_1=3,\n threshold_2=5,\n system_capacity_1=4,\n system_capacity_2=6,\n buffer_capacity_1=2,\n buffer_capacity_2=2,\n target=2,\n alpha=0.5,\n use_simulation=True,\n runtime=300,\n num_of_trials=3,\n warm_up_time=5,\n seed_num_1=0,\n seed_num_2=0,\n )\n\n assert da.is_dask_collection(task)\n values = da.compute(task)\n assert np.allclose(\n values,\n (\n (\n 3,\n 5,\n 0.7613063676529543,\n 1 - 0.0006520260736895711,\n 1 - 0.027937014444158834,\n ),\n ),\n )","def call(self, x, mask=None):\n # Add trainable weights\n self.build()\n outputs = x[0]\n atom_split = x[1]\n\n if self.gaussian_expand:\n outputs = self.gaussian_histogram(outputs)\n\n output_molecules = tf.segment_sum(outputs, atom_split)\n\n if self.gaussian_expand:\n output_molecules = tf.matmul(output_molecules, self.W) + self.b\n output_molecules = self.activation(output_molecules)\n return output_molecules","def test_corr_transform_smoke(meta_cres_small):\n assert isinstance(meta_cres_small, MetaResult)","def torchani(ret_data):\n\n import numpy as np\n import torch\n import torchani\n\n device = torch.device('cpu')\n builtin = torchani.neurochem.Builtins()\n\n # Failure flag\n ret_data[\"success\"] = False\n\n # Build model\n model = get_model(ret_data[\"model\"][\"method\"])\n if model is False:\n ret_data[\"error_message\"] = \"run_torchani only accepts the ANI1 method.\"\n return ret_data\n\n # Build species\n species = \"\".join(ret_data[\"molecule\"][\"symbols\"])\n unknown_sym = set(species) - {\"H\", \"C\", \"N\", \"O\"}\n if unknown_sym:\n ret_data[\"error_message\"] = \"The '{}' model does not support symbols: {}.\".format(\n ret_data[\"model\"][\"method\"], unknown_sym)\n return ret_data\n\n species = builtin.consts.species_to_tensor(species).to(device).unsqueeze(0)\n\n # Build coord array\n geom_array = np.array(ret_data[\"molecule\"][\"geometry\"]).reshape(1, -1, 3) * units.bohr_to_angstrom\n coordinates = torch.tensor(geom_array.tolist(), requires_grad=True, device=device)\n\n _, energy = model((species, coordinates))\n ret_data[\"properties\"] = {\"return_energy\": energy.item()}\n\n if ret_data[\"driver\"] == \"energy\":\n ret_data[\"return_result\"] = ret_data[\"properties\"][\"return_energy\"]\n elif ret_data[\"driver\"] == \"gradient\":\n derivative = torch.autograd.grad(energy.sum(), coordinates)[0].squeeze()\n ret_data[\"return_result\"] = np.asarray(derivative / units.bohr_to_angstrom).ravel().tolist()\n else:\n ret_data[\"error_message\"] = \"run_torchani did not understand driver method '{}'.\".format(ret_data[\"driver\"])\n return ret_data\n\n ret_data[\"provenance\"] = {\"creator\": \"torchani\", \"version\": \"unknown\", \"routine\": \"torchani.builtin.aev_computer\"}\n\n ret_data[\"schema_name\"] = \"qc_schema_output\"\n ret_data[\"success\"] = True\n\n return ret_data","async def test_fetch_filtered_dataset_call(self):\n pool = asynctest.CoroutineMock()\n db_response = {\"referenceBases\": '', \"alternateBases\": '', \"variantType\": \"\",\n \"referenceName\": 'Chr38',\n \"frequency\": 0, \"callCount\": 0, \"sampleCount\": 0, \"variantCount\": 0,\n \"start\": 0, \"end\": 0, \"accessType\": \"PUBLIC\", \"datasetId\": \"test\"}\n pool.acquire().__aenter__.return_value = Connection(accessData=[db_response])\n assembly_id = 'GRCh38'\n position = (10, 20, None, None, None, None)\n chromosome = 1\n reference = 'A'\n alternate = ('DUP', None)\n result = await fetch_filtered_dataset(pool, assembly_id, position, chromosome, reference, alternate, None, None, False)\n # for now it can return empty dataset\n # in order to get a response we will have to mock it\n # in Connection() class\n expected = {'referenceName': 'Chr38', 'callCount': 0, 'sampleCount': 0, 'variantCount': 0, 'datasetId': 'test',\n 'referenceBases': '', 'alternateBases': '', 'variantType': '', 'start': 0, 'end': 0, 'frequency': 0,\n 'info': {'accessType': 'PUBLIC'},\n 'datasetHandover': [{'handoverType': {'id': 'CUSTOM', 'label': 'Variants'},\n 'description': 'browse the variants matched by the query',\n 'url': 'https://examplebrowser.org/dataset/test/browser/variant/Chr38-1--'},\n {'handoverType': {'id': 'CUSTOM', 'label': 'Region'},\n 'description': 'browse data of the region matched by the query',\n 'url': 'https://examplebrowser.org/dataset/test/browser/region/Chr38-1-1'},\n {'handoverType': {'id': 'CUSTOM', 'label': 'Data'},\n 'description': 'retrieve information of the datasets',\n 'url': 'https://examplebrowser.org/dataset/test/browser'}]}\n\n self.assertEqual(result, [expected])","def test_multi_molecules_cycle_one(self, multi_mol_system_irregular):\n sequence = \"A\"\n expected = [sequence] * (15 * 3)\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(multi_mol_system_irregular)\n found = self.sequence_from_system(multi_mol_system_irregular, \"test\")\n assert found == expected","def test_diatomic_dummy_molecule_rotation_around_molecule_axis():\n mol = Molecule()\n mol.atoms = ['C'] * 2\n mol.coordinates = np.array([[1, 0, 0], [0, 1, 0]])\n mol.rotate(([0, 0, 0], [0, 0, 1]), np.pi / 2, center=True)\n assert np.allclose(mol.coordinates, [[1, 1, 0], [0, 0, 0]])\n mol.rotate(([0, 0, 0], [0, 0, 1]), np.pi, center=True)\n assert np.allclose(mol.coordinates, [[0, 0, 0], [1, 1, 0]])","def get_smarts(prefix, atom_idxs):\n\n offmol = Molecule.from_file(prefix + '.mol2')\n fix_carboxylate_bond_orders(offmol)\n remove_charge_and_bond_order_from_guanidinium(offmol)\n remove_charge_and_bond_order_from_imidazole(offmol)\n if prefix in prefix2pmd_struct:\n pmd_struct = prefix2pmd_struct[prefix]\n else: \n pmd_struct = ParmEd.load_file(prefix + '.prmtop')\n prefix2pmd_struct[prefix] = pmd_struct\n oemol = offmol.to_openeye()\n residues_of_interest = set()\n atom_indices_of_interest = set()\n for atom_idx in atom_idxs:\n residues_of_interest.add(pmd_struct.atoms[atom_idx].residue.idx)\n for oeatom, pmd_atom in zip(oemol.GetAtoms(), pmd_struct.atoms):\n\n # Delete all non-residue-of-interest atoms\n if (pmd_atom.residue.idx in residues_of_interest):\n atom_indices_of_interest.add(pmd_atom.idx)\n\n # Assign tags to atoms of interest\n if (oeatom.GetIdx() in atom_idxs):\n map_index = atom_idxs.index(oeatom.GetIdx()) + 1\n oeatom.SetMapIdx(map_index)\n\n # Make a \"Subset\" molecule, so that we don't get weird charges\n # around where we cleave the residues\n subsetmol = OEChem.OEGraphMol()\n oepred = OEChem.PyAtomPredicate(lambda x:x.GetIdx() in atom_indices_of_interest)\n OEChem.OESubsetMol(subsetmol, oemol, oepred)\n #OEAssignAromaticFlags(subsetmol, \n smiles_options = (OEChem.OESMILESFlag_Canonical | OEChem.OESMILESFlag_Isotopes |\n OEChem.OESMILESFlag_RGroups)\n # Add the atom and bond stereo flags\n smiles_options |= OEChem.OESMILESFlag_AtomStereo | OEChem.OESMILESFlag_BondStereo\n\n # Add the hydrogen flag\n smiles_options |= OEChem.OESMILESFlag_Hydrogens\n smiles_options |= OEChem.OESMILESFlag_AtomMaps\n smiles = OEChem.OECreateSmiString(subsetmol, smiles_options)\n\n # Replace \"$\" characters (bond order 4) with \"~\" (wildcard bond)\n smiles = smiles.replace('$', '~')\n return smiles","def _load_molecule(self):\n self.pymol = pybel.readstring(self.input_format, self.file_dic['input'])","def test_rdkit_conf_from_mol(self):\n b_mol = converter.molecules_from_xyz(self.xyz5['dict'])[1]\n conf, rd_mol = converter.rdkit_conf_from_mol(mol=b_mol, xyz=self.xyz5['dict'])\n self.assertTrue(conf.Is3D())\n self.assertEqual(rd_mol.GetNumAtoms(), 5)","def test_return_spin_pipe_fail(self):\n\n # Try to get a spin from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')","def test_modul1(self):\n\n self.delayDisplay(\"Starting the test\")\n #\n # first, get some data\n #\n import urllib\n downloads = (\n ('http://slicer.kitware.com/midas3/download?items=5767', 'FA.nrrd', slicer.util.loadVolume),\n )\n\n for url,name,loader in downloads:\n filePath = slicer.app.temporaryPath + '/' + name\n if not os.path.exists(filePath) or os.stat(filePath).st_size == 0:\n logging.info('Requesting download %s from %s...\\n' % (name, url))\n urllib.urlretrieve(url, filePath)\n if loader:\n logging.info('Loading %s...' % (name,))\n loader(filePath)\n self.delayDisplay('Finished with download and loading')\n\n volumeNode = slicer.util.getNode(pattern=\"FA\")\n logic = modulLogic()\n self.assertTrue( logic.hasImageData(volumeNode) )\n self.delayDisplay('Test passed!')","def get_slab(self):\n return self.c.get_atoms(simulation_cell=True)","def get_redo_workflow(self, qchem_input_params, sp_params, max_iterations=3):\n\n if self.db is None:\n raise RuntimeError(\"Cannot access database to determine what\"\n \"molecules need to be re-calculated.\")\n\n fws = []\n\n collection = self.db.db[\"molecules\"]\n\n for mol in collection.find({}):\n frequencies = mol[\"output\"][\"frequencies\"]\n\n if any([True if x < 0 else False for x in frequencies]):\n min_molecule_perturb_scale = 0.1\n max_molecule_perturb_scale = 0.3\n scale_grid = 10\n perturb_scale_grid = (max_molecule_perturb_scale -\n min_molecule_perturb_scale) / scale_grid\n msc = MoleculeStructureComparator()\n\n old_molecule = None\n\n for calc in mol[\"calcs_reversed\"]:\n if calc[\"task\"][\"type\"] in [\"freq\", \"frequency\"] and old_molecule is None:\n negative_freq_vecs = calc.get(\"frequency_mode_vectors\")[0]\n old_coords = calc.get(\"initial_geometry\")\n old_molecule = Molecule.from_dict(calc.get(\"initial_molecule\"))\n\n structure_successfully_perturbed = False\n\n for molecule_perturb_scale in np.arange(\n max_molecule_perturb_scale, min_molecule_perturb_scale,\n -perturb_scale_grid):\n new_coords = perturb_coordinates(\n old_coords=old_coords,\n negative_freq_vecs=negative_freq_vecs,\n molecule_perturb_scale=molecule_perturb_scale,\n reversed_direction=False)\n new_molecule = Molecule(\n species=old_molecule.species,\n coords=new_coords,\n charge=old_molecule.charge,\n spin_multiplicity=old_molecule.spin_multiplicity)\n if msc.are_equal(old_molecule, new_molecule):\n structure_successfully_perturbed = True\n break\n if not structure_successfully_perturbed:\n raise Exception(\n \"Unable to perturb coordinates to remove negative frequency without changing the bonding structure\"\n )\n\n mol_id = mol[\"mol_id\"]\n dir_name = mol[\"dir_name\"].split(\"/\")[-1]\n\n if dir_name not in listdir(self.base_dir):\n os.mkdir(join(self.base_dir, dir_name))\n\n fws.append(OptFreqSPFW(molecule=new_molecule,\n name=\"Flattening: {}/{}\".format(mol_id,\n dir_name),\n qchem_cmd=\"qchem -slurm\",\n input_file=join(self.base_dir,\n dir_name,\n mol_id + \".in\"),\n output_file=join(self.base_dir,\n dir_name,\n mol_id + \".out\"),\n qclog_file=join(self.base_dir,\n dir_name,\n mol_id + \".qclog\"),\n max_cores=32,\n max_iterations=max_iterations,\n qchem_input_params=qchem_input_params,\n sp_params=sp_params,\n db_file=self.db_file))\n\n if len(fws) == 0:\n return None\n else:\n return Workflow(fws)","def get_container_output(container_name: Optional[pulumi.Input[str]] = None,\n device_name: Optional[pulumi.Input[str]] = None,\n resource_group_name: Optional[pulumi.Input[str]] = None,\n storage_account_name: Optional[pulumi.Input[str]] = None,\n opts: Optional[pulumi.InvokeOptions] = None) -> pulumi.Output[GetContainerResult]:\n ...","def process(self, name_and_sequence):\n name, sequence = name_and_sequence\n yield preprocess_utils.get_pacbio_molecule_name(name), sequence","def test_random_circuit(self, device, tol, ret):\n n_wires = 2\n dev = device(n_wires)\n dev_def = qml.device(\"default.qubit\", wires=n_wires)\n\n if dev.name == dev_def.name:\n pytest.skip(\"Device is default.qubit.\")\n\n supports_tensor = (\n \"supports_tensor_observables\" in dev.capabilities()\n and dev.capabilities()[\"supports_tensor_observables\"]\n )\n\n if not supports_tensor:\n pytest.skip(\"Device does not support tensor observables.\")\n\n if dev.shots is not None:\n pytest.skip(\"Device is in non-analytical mode.\")\n\n n_layers = np.random.randint(1, 5)\n weights = 2 * np.pi * np.random.rand(n_layers, 1)\n\n ret_type = getattr(qml, ret)\n\n def circuit(weights):\n RandomLayers(weights, wires=range(n_wires))\n return ret_type(qml.PauliZ(wires=0) @ qml.PauliX(wires=1))\n\n qnode_def = qml.QNode(circuit, dev_def)\n qnode = qml.QNode(circuit, dev)\n\n grad_def = qml.grad(qnode_def, argnum=0)\n grad = qml.grad(qnode, argnum=0)\n\n assert np.allclose(qnode(weights), qnode_def(weights), atol=tol(dev.shots))\n assert np.allclose(grad(weights), grad_def(weights), atol=tol(dev.shots))","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def get_data(self, molecule, base_dir, bo_list, dt, istep, calc_force_only):\n self.copy_files(molecule, istep, calc_force_only)\n super().get_data(base_dir, calc_force_only)\n self.get_input(molecule, istep, bo_list, calc_force_only)\n self.run_QM(base_dir, istep, bo_list)\n self.extract_QM(molecule, istep, bo_list, dt, calc_force_only)\n self.move_dir(base_dir)","def test_volume():\n structure = Material(input)\n assert (structure.volume == 90.725624999999965)"],"string":"[\n \"def test_return_molecule_pipe_fail(self):\\n\\n # Try to get a molecule from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_molecule_loop(self):\\n\\n # Loop over the molecules.\\n for mol in mol_res_spin.molecule_loop('#RNA'):\\n # Test the molecule name.\\n self.assertEqual(mol.name, 'RNA')\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)\",\n \"def test_molecule_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the molecules.\\n i = 0\\n for molecule in mol_res_spin.molecule_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_return_residue(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_residue(':1')\\n res2 = mol_res_spin.return_residue(selection=':2')\\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1.num, 1)\\n self.assertEqual(res1.name, None)\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2.num, 2)\\n self.assertEqual(res2.name, 'Glu')\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4.num, 4)\\n self.assertEqual(res4.name, 'Pro')\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5.num, -5)\\n self.assertEqual(res5.name, None)\\n self.assertEqual(res5.spin[1].name, 'N5')\",\n \"def test_molecule_loop_no_selection(self):\\n\\n # Molecule data.\\n name = ['Ap4Aase', 'RNA']\\n\\n # Loop over the molecules.\\n i = 0\\n for mol in mol_res_spin.molecule_loop():\\n # Test the molecule names.\\n self.assertEqual(mol.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def test_run_molecule(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def test_return_single_residue_info(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_single_residue_info('1')\\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\\n res5 = mol_res_spin.return_single_residue_info('-5')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1, (1, None))\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2, (2, 'Glu'))\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4, (4, 'Pro'))\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5, (-5, None))\",\n \"def test_set_molecule(self):\\n mol = Molecule.from_smiles(\\\"CCO\\\")\\n atom = Atom(6, 0, False)\\n atom.molecule = mol\",\n \"def molecule(self):\\n return self._molecule\",\n \"def make_molecule(self):\\n\\n self.data.molecules = self.data.Smiles.apply(Chem.MolFromSmiles)\\n\\n return self.data.molecules\",\n \"def test_get_container(self):\\n pass\",\n \"def setUp(self):\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Name the first molecule.\\n cdp.mol[0].name = 'Ap4Aase'\\n\\n # Add a second molecule to the system.\\n cdp.mol.add_item(mol_name='RNA')\\n\\n # Add two more residues to the first molecule (and set the residue number of the first).\\n cdp.mol[0].res[0].num = 1\\n cdp.mol[0].res.add_item(res_num=2, res_name='Glu')\\n cdp.mol[0].res.add_item(res_num=4, res_name='Pro')\\n\\n # Add some spin info to this molecule.\\n cdp.mol[0].res[0].spin[0].name = 'NH'\\n cdp.mol[0].res[0].spin[0].num = 60\\n cdp.mol[0].res[1].spin[0].name = 'NH'\\n cdp.mol[0].res[1].spin[0].num = 63\\n\\n # Add one more residue to the second molecule (and set the residue number of the first).\\n cdp.mol[1].res[0].num = -5\\n cdp.mol[1].res.add_item(res_num=-4)\\n\\n # Add a second set of spins to the second molecule (naming the first set first).\\n cdp.mol[1].res[0].spin[0].name = 'C8'\\n cdp.mol[1].res[1].spin[0].name = 'C8'\\n cdp.mol[1].res[0].spin.add_item(spin_name='N5')\\n cdp.mol[1].res[1].spin.add_item(spin_name='N5')\\n cdp.mol[1].res[1].spin.add_item(spin_name='2H', spin_num=132)\\n\\n # Deselect a number of spins.\\n cdp.mol[0].res[0].spin[0].select = 0\\n cdp.mol[0].res[2].spin[0].select = 0\\n cdp.mol[1].res[0].spin[0].select = 0\\n cdp.mol[1].res[1].spin[1].select = 0\\n\\n # Update the metadata.\\n mol_res_spin.metadata_update()\",\n \"def test_single_molecule(self, single_mol_system, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def test_container_get_set(self): \\n circdich1 = self.circdich1\\n \\n cntnr = CircDichSpectrumContainer()\\n cntnr.set_axis(circdich1.axis)\\n cntnr.set_spectrum(circdich1, tag='tester')\\n spec = cntnr.get_spectrum(tag='tester')\\n \\n numpy.testing.assert_array_equal(circdich1.data, spec.data)\",\n \"def init_molecule():\\n \\n pos1 = np.array([[0.2],[0.2]])\\n pos2 = np.array([[0.8],[0.8]])\\n mol = Molecule(pos1, pos2, 10, 20, 1, 0.5)\\n \\n return mol\",\n \"def get_molecules(root):\\n mols = get_records_with_tag(root,'molecule')\\n if not mols: mols = [root] # Assume tree consists of a molecule at the root\\n return mols\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def _get_components(\\n design_unit: oechem.OEDesignUnit\\n ) -> Tuple[oechem.OEGraphMol(), oechem.OEGraphMol(), oechem.OEGraphMol()]:\\n from openeye import oechem\\n\\n protein, solvent, ligand = oechem.OEGraphMol(), oechem.OEGraphMol(), oechem.OEGraphMol()\\n\\n logging.debug(\\\"Extracting molecular components ...\\\")\\n design_unit.GetProtein(protein)\\n design_unit.GetSolvent(solvent)\\n design_unit.GetLigand(ligand)\\n\\n # delete protein atoms with no name (found in prepared protein of 4ll0)\\n for atom in protein.GetAtoms():\\n if not atom.GetName().strip():\\n logging.debug(\\\"Deleting unknown atom ...\\\")\\n protein.DeleteAtom(atom)\\n\\n # perceive residues to remove artifacts of other design units in the sequence of the protein\\n # preserve certain properties to assure correct behavior of the pipeline,\\n # e.g. deletion of chains in OEKLIFSKinaseApoFeaturizer._process_kinase_domain method\\n preserved_info = (\\n oechem.OEPreserveResInfo_ResidueNumber\\n | oechem.OEPreserveResInfo_ResidueName\\n | oechem.OEPreserveResInfo_AtomName\\n | oechem.OEPreserveResInfo_ChainID\\n | oechem.OEPreserveResInfo_HetAtom\\n | oechem.OEPreserveResInfo_InsertCode\\n | oechem.OEPreserveResInfo_AlternateLocation\\n )\\n oechem.OEPerceiveResidues(protein, preserved_info)\\n oechem.OEPerceiveResidues(solvent, preserved_info)\\n oechem.OEPerceiveResidues(ligand)\\n\\n logging.debug(\\n \\\"Number of component atoms: \\\" +\\n f\\\"Protein - {protein.NumAtoms()}, \\\" +\\n f\\\"Solvent - {solvent.NumAtoms()}, \\\" +\\n f\\\"Ligand - {ligand.NumAtoms()}.\\\"\\n )\\n return protein, solvent, ligand\",\n \"def test_to_from_rdkit(self, molecule):\\n # import pickle\\n from openforcefield.utils.toolkits import UndefinedStereochemistryError\\n\\n undefined_stereo = molecule.name in rdkit_drugbank_undefined_stereo_mols\\n\\n toolkit_wrapper = RDKitToolkitWrapper()\\n\\n rdmol = molecule.to_rdkit()\\n molecule_smiles = molecule.to_smiles(toolkit_registry=toolkit_wrapper)\\n\\n # First test making a molecule using the Molecule(oemol) method\\n\\n # If this is a known failure, check that it raises UndefinedStereochemistryError\\n # and proceed with the test ignoring it.\\n test_mol = None\\n if undefined_stereo:\\n with pytest.raises(UndefinedStereochemistryError):\\n Molecule(rdmol)\\n test_mol = Molecule(rdmol, allow_undefined_stereo=True)\\n else:\\n test_mol = Molecule(rdmol)\\n\\n test_mol_smiles = test_mol.to_smiles(toolkit_registry=toolkit_wrapper)\\n assert molecule_smiles == test_mol_smiles\\n\\n # Check that the two topologies are isomorphic.\\n assert_molecule_is_equal(\\n molecule, test_mol, \\\"Molecule.to_rdkit()/Molecule(rdmol) round trip failed\\\"\\n )\\n\\n # Second, test making a molecule using the Molecule.from_openeye(oemol) method\\n\\n # If this is a known failure, check that it raises UndefinedStereochemistryError\\n # and proceed with the test.\\n if undefined_stereo:\\n with pytest.raises(UndefinedStereochemistryError):\\n Molecule.from_rdkit(rdmol)\\n test_mol = Molecule.from_rdkit(rdmol, allow_undefined_stereo=True)\\n else:\\n test_mol = Molecule.from_rdkit(rdmol)\\n\\n test_mol_smiles = test_mol.to_smiles(toolkit_registry=toolkit_wrapper)\\n assert molecule_smiles == test_mol_smiles\\n\\n # Check that the two topologies are isomorphic.\\n assert_molecule_is_equal(\\n molecule, test_mol, \\\"Molecule.to_rdkit()/from_rdkit() round trip failed\\\"\\n )\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_return_single_residue_info_fail(self):\\n\\n # Ask for a few residues.\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')\",\n \"def test_molecule_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for molecule in mol_res_spin.molecule_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_get_thermo_data(self):\\n output_directory = os.path.join(self.mop4.settings.fileStore, '..', '..')\\n self.mop4.set_default_output_directory(output_directory)\\n self.gauss3.set_default_output_directory(output_directory)\\n self.molpro1.set_default_output_directory(output_directory)\\n\\n mol = Molecule().from_smiles('C1=CC=C2C=CC=CC2=C1')\\n\\n with self.assertRaises(Exception):\\n self.mop4.get_thermo_data(mol)\\n self.gauss3.get_thermo_data(mol)\\n self.molpro1.get_thermo_data(mol)\",\n \"def test_to_from_rdkit(self, molecule):\\n # import pickle\\n from openff.toolkit.utils.toolkits import UndefinedStereochemistryError\\n\\n undefined_stereo = molecule.name in rdkit_drugbank_undefined_stereo_mols\\n\\n toolkit_wrapper = RDKitToolkitWrapper()\\n\\n rdmol = molecule.to_rdkit()\\n molecule_smiles = molecule.to_smiles(toolkit_registry=toolkit_wrapper)\\n\\n # First test making a molecule using the Molecule(oemol) method\\n\\n # If this is a known failure, check that it raises UndefinedStereochemistryError\\n # and proceed with the test ignoring it.\\n test_mol = None\\n if undefined_stereo:\\n with pytest.raises(UndefinedStereochemistryError):\\n Molecule(rdmol)\\n test_mol = Molecule(rdmol, allow_undefined_stereo=True)\\n else:\\n test_mol = Molecule(rdmol)\\n\\n test_mol_smiles = test_mol.to_smiles(toolkit_registry=toolkit_wrapper)\\n assert molecule_smiles == test_mol_smiles\\n\\n # Check that the two topologies are isomorphic.\\n assert_molecule_is_equal(\\n molecule, test_mol, \\\"Molecule.to_rdkit()/Molecule(rdmol) round trip failed\\\"\\n )\\n\\n # Second, test making a molecule using the Molecule.from_openeye(oemol) method\\n\\n # If this is a known failure, check that it raises UndefinedStereochemistryError\\n # and proceed with the test.\\n if undefined_stereo:\\n with pytest.raises(UndefinedStereochemistryError):\\n Molecule.from_rdkit(rdmol)\\n test_mol = Molecule.from_rdkit(rdmol, allow_undefined_stereo=True)\\n else:\\n test_mol = Molecule.from_rdkit(rdmol)\\n\\n test_mol_smiles = test_mol.to_smiles(toolkit_registry=toolkit_wrapper)\\n assert molecule_smiles == test_mol_smiles\\n\\n # Check that the two topologies are isomorphic.\\n assert_molecule_is_equal(\\n molecule, test_mol, \\\"Molecule.to_rdkit()/from_rdkit() round trip failed\\\"\\n )\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def storeMolecule():\\n pass\",\n \"def __init__(self,\\n molinit=None,\\n dtype=None,\\n\\n geom=None,\\n elea=None,\\n elez=None,\\n elem=None,\\n mass=None,\\n real=None,\\n elbl=None,\\n\\n name=None,\\n units='Angstrom',\\n input_units_to_au=None,\\n fix_com=None,\\n fix_orientation=None,\\n fix_symmetry=None,\\n\\n fragment_separators=None,\\n fragment_charges=None,\\n fragment_multiplicities=None,\\n\\n molecular_charge=None,\\n molecular_multiplicity=None,\\n\\n enable_qm=True,\\n enable_efp=True,\\n missing_enabled_return_qm='none',\\n missing_enabled_return_efp='none',\\n\\n missing_enabled_return='error',\\n tooclose=0.1,\\n zero_ghost_fragments=False,\\n nonphysical=False,\\n mtol=1.e-3,\\n verbose=1):\\n super(Molecule, self).__init__()\\n\\n if molinit is not None or geom is not None:\\n if isinstance(molinit, dict):\\n molrec = molinit\\n\\n elif isinstance(molinit, basestring):\\n compound_molrec = molparse.from_string(\\n molstr=molinit,\\n dtype=dtype,\\n name=name,\\n fix_com=fix_com,\\n fix_orientation=fix_orientation,\\n fix_symmetry=fix_symmetry,\\n return_processed=False,\\n enable_qm=enable_qm,\\n enable_efp=enable_efp,\\n missing_enabled_return_qm=missing_enabled_return_qm,\\n missing_enabled_return_efp=missing_enabled_return_efp,\\n verbose=verbose)\\n molrec = compound_molrec['qm']\\n\\n elif molinit is None and geom is not None:\\n molrec = molparse.from_arrays(\\n geom=geom,\\n elea=elea,\\n elez=elez,\\n elem=elem,\\n mass=mass,\\n real=real,\\n elbl=elbl,\\n name=name,\\n units=units,\\n input_units_to_au=input_units_to_au,\\n fix_com=fix_com,\\n fix_orientation=fix_orientation,\\n fix_symmetry=fix_symmetry,\\n fragment_separators=fragment_separators,\\n fragment_charges=fragment_charges,\\n fragment_multiplicities=fragment_multiplicities,\\n molecular_charge=molecular_charge,\\n molecular_multiplicity=molecular_multiplicity,\\n domain='qm',\\n missing_enabled_return=missing_enabled_return,\\n tooclose=tooclose,\\n zero_ghost_fragments=zero_ghost_fragments,\\n nonphysical=nonphysical,\\n mtol=mtol,\\n verbose=verbose)\\n\\n # ok, got the molrec dictionary; now build the thing\\n self._internal_from_dict(molrec, verbose=verbose)\\n\\n # The comment line\\n self.tagline = \\\"\\\"\",\n \"def __call__(self, mol):\\n return self.choose(mol)\",\n \"def __init__(self,\\n num_masks=1,\\n num_fake=0,\\n epsilon_greedy=0.0,\\n num_classes = 2,\\n num_samples = 1000,\\n max_length = 30,\\n ambiguity=False,\\n num_bondtypes=1):\\n\\n self.num_masks = num_masks\\n self.num_fake = num_fake\\n self.epsilon_greedy = epsilon_greedy\\n self.num_classes = num_classes\\n self.num_samples = num_samples\\n\\n self.molecule_generator = MoleculeGenerator(num_classes=num_classes, \\n max_length=max_length, \\n ambiguity=ambiguity,\\n num_bondtypes=num_bondtypes)\\n\\n self.corruption = CorruptionTransform(num_masks=num_masks, num_fake=num_fake, epsilon=epsilon_greedy)\\n\\n\\n self.data = []\\n\\n\\n for i in range(self.num_samples):\\n molecule = self.molecule_generator.generate_molecule()\\n molecule = chem.AddHs(molecule)\\n\\n\\n Adj = chem.rdmolops.GetAdjacencyMatrix(molecule)\\n atoms = np.asarray([periodic_table[atom.GetAtomicNum()] for atom in molecule.GetAtoms()])\\n smiles = chem.MolToSmiles(molecule)\\n self.data += [MoleculeSample(atoms, Adj, {}, smiles)]\",\n \"def test_validation_wrong_molecules():\\n paths = examples_paths()\\n paths['wrongformat'] = utils.get_data_filename(os.path.join('tests', 'data', 'README.md'))\\n molecules = [\\n {'antechamber': {'charge_method': 'bcc'}},\\n {'filepath': paths['wrongformat']},\\n {'name': 'p-xylene', 'antechamber': {'charge_method': 'bcc'}, 'unknown': 4},\\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'}},\\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'invalid'},\\n 'antechamber': {'charge_method': None}},\\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'},\\n 'antechamber': {'charge_method': 'bcc'}},\\n {'filepath': 'nonexistentfile.pdb', 'leap': {'parameters': 'leaprc.ff14SB'}},\\n {'filepath': paths['toluene'], 'smiles': 'Cc1ccccc1'},\\n {'filepath': paths['toluene'], 'strip_protons': True},\\n {'filepath': paths['abl'], 'leap': {'parameters': 'oldff/leaprc.ff14SB'}, 'epik': {'select': 0}},\\n {'name': 'toluene', 'epik': 0},\\n {'name': 'toluene', 'epik': {'tautomerize': 6}},\\n {'name': 'toluene', 'epik': {'extract_range': 1}},\\n {'name': 'toluene', 'smiles': 'Cc1ccccc1'},\\n {'name': 3},\\n {'smiles': 'Cc1ccccc1', 'select': 1},\\n {'name': 'Cc1ccccc1', 'select': 1},\\n {'filepath': paths['abl'], 'leap': {'parameters': 'oldff/leaprc.ff14SB'}, 'select': 'notanoption'},\\n {'filepath': paths['abl'], 'regions': 5},\\n {'filepath': paths['abl'], 'regions': {'a_region': [-56, 5.23]}},\\n {'filepath': paths['toluene'], 'leap': {'parameters': 'leaprc.gaff'}, 'strip_protons': True},\\n ]\\n for molecule in molecules:\\n yield assert_raises, YamlParseError, ExperimentBuilder._validate_molecules, {'mol': molecule}\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_get_thermo_data_mopac(self):\\n output_directory = os.path.join(self.mop1.settings.fileStore, '..', '..')\\n self.mop1.set_default_output_directory(output_directory)\\n self.mop2.set_default_output_directory(output_directory)\\n self.mop3.set_default_output_directory(output_directory)\\n\\n mol = Molecule().from_smiles('C1=CC=C2C=CC=CC2=C1')\\n\\n for directory in (self.mop1.settings.fileStore, self.mop1.settings.scratchDirectory):\\n shutil.rmtree(directory, ignore_errors=True)\\n\\n for directory in (self.mop2.settings.fileStore, self.mop2.settings.scratchDirectory):\\n shutil.rmtree(directory, ignore_errors=True)\\n\\n for directory in (self.mop3.settings.fileStore, self.mop3.settings.scratchDirectory):\\n shutil.rmtree(directory, ignore_errors=True)\\n\\n thermo1 = self.mop1.get_thermo_data(mol)\\n thermo2 = self.mop2.get_thermo_data(mol)\\n thermo3 = self.mop3.get_thermo_data(mol)\\n\\n self.assertTrue(thermo1.comment.startswith('QM MopacMolPM3'))\\n self.assertTrue(thermo2.comment.startswith('QM MopacMolPM6'))\\n self.assertTrue(thermo3.comment.startswith('QM MopacMolPM7'))\\n\\n self.assertAlmostEqual(thermo1.H298.value_si, 169708.0608, 1) # to 1 decimal place\\n self.assertAlmostEqual(thermo1.S298.value_si, 334.5007584, 1) # to 1 decimal place\\n self.assertAlmostEqual(thermo2.H298.value_si, 167704.4270, 1) # to 1 decimal place\\n self.assertAlmostEqual(thermo2.S298.value_si, 338.0999241, 1) # to 1 decimal place\\n self.assertAlmostEqual(thermo3.H298.value_si, 166168.8571, 1) # to 1 decimal place\\n self.assertAlmostEqual(thermo3.S298.value_si, 336.3330406, 1) # to 1 decimal place\",\n \"def molecule_data(self) -> Union[QMolecule, WatsonHamiltonian]:\\n return self._molecule_data\",\n \"def test_generate_random_container_list():\\n random_container = main.generate_random_container(10, 100, False)\\n assert len(random_container) == 10\",\n \"def test_chemistries():\\n chems = [\\n utils.Chemistry(\\n potion_map=stones_and_potions.all_fixed_potion_map(),\\n stone_map=stones_and_potions.all_fixed_stone_map(),\\n graph=graphs.create_graph_from_constraint(\\n graphs.no_bottleneck_constraints()[0]),\\n rotation=np.eye(3)),\\n utils.Chemistry(\\n potion_map=stones_and_potions.PotionMap([1, 0, 2], [1, 1, -1]),\\n stone_map=stones_and_potions.StoneMap(np.array([-1, 1, -1])),\\n graph=graphs.create_graph_from_constraint(\\n graphs.bottleneck1_constraints()[0]),\\n rotation=stones_and_potions.possible_rotations()[-1])]\\n for r in stones_and_potions.possible_rotations():\\n for sm in stones_and_potions.possible_stone_maps():\\n chems.append(utils.Chemistry(\\n potion_map=stones_and_potions.all_fixed_potion_map(),\\n stone_map=sm,\\n graph=graphs.create_graph_from_constraint(\\n graphs.no_bottleneck_constraints()[0]),\\n rotation=r))\\n return chems\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def _result_wrapper(self, result, _pymatgen) -> List[ase.atoms.Atoms]:\\n if _pymatgen:\\n _, fname = tempfile.mkstemp(text=True)\\n with open(fname, \\\"w\\\") as f:\\n f.write(result.to(\\\"poscar\\\"))\\n return ase.io.read(fname, index=':', format=\\\"vasp\\\")\\n else:\\n import json\\n result = json.load(result)\\n if result[\\\"valid_response\\\"]:\\n _, fname = tempfile.mkstemp(text=True)\\n with open(fname, \\\"w\\\") as f:\\n f.write(result[\\\"response\\\"][0][\\\"cif\\\"])\\n return ase.io.read(fname, index=':', format=\\\"cif\\\")\\n elif not result[\\\"api_key_valid\\\"]:\\n raise ValueError(f\\\"Invalid API_KEY: {self.API_KEY}. Check your API_KEY at https://www.materialsproject.org/open!\\\")\",\n \"def test_molecules_from_xyz(self):\\n s_mol, b_mol = converter.molecules_from_xyz(self.xyz6['dict'])\\n\\n # check that the atom order is the same\\n self.assertTrue(s_mol.atoms[0].is_sulfur())\\n self.assertTrue(b_mol.atoms[0].is_sulfur())\\n self.assertTrue(s_mol.atoms[1].is_oxygen())\\n self.assertTrue(b_mol.atoms[1].is_oxygen())\\n self.assertTrue(s_mol.atoms[2].is_oxygen())\\n self.assertTrue(b_mol.atoms[2].is_oxygen())\\n self.assertTrue(s_mol.atoms[3].is_nitrogen())\\n self.assertTrue(b_mol.atoms[3].is_nitrogen())\\n self.assertTrue(s_mol.atoms[4].is_carbon())\\n self.assertTrue(b_mol.atoms[4].is_carbon())\\n self.assertTrue(s_mol.atoms[5].is_hydrogen())\\n self.assertTrue(b_mol.atoms[5].is_hydrogen())\\n self.assertTrue(s_mol.atoms[6].is_hydrogen())\\n self.assertTrue(b_mol.atoms[6].is_hydrogen())\\n self.assertTrue(s_mol.atoms[7].is_hydrogen())\\n self.assertTrue(b_mol.atoms[7].is_hydrogen())\\n self.assertTrue(s_mol.atoms[8].is_hydrogen())\\n self.assertTrue(b_mol.atoms[8].is_hydrogen())\\n self.assertTrue(s_mol.atoms[9].is_hydrogen())\\n self.assertTrue(b_mol.atoms[9].is_hydrogen())\\n\\n s_mol, b_mol = converter.molecules_from_xyz(self.xyz7['dict'])\\n self.assertTrue(s_mol.atoms[0].is_oxygen())\\n self.assertTrue(b_mol.atoms[0].is_oxygen())\\n self.assertTrue(s_mol.atoms[2].is_carbon())\\n self.assertTrue(b_mol.atoms[2].is_carbon())\\n\\n expected_bonded_adjlist = \\\"\\\"\\\"multiplicity 2\\n1 O u0 p2 c0 {6,S} {10,S}\\n2 O u0 p2 c0 {3,S} {28,S}\\n3 C u0 p0 c0 {2,S} {8,S} {14,S} {15,S}\\n4 C u0 p0 c0 {7,S} {16,S} {17,S} {18,S}\\n5 C u0 p0 c0 {7,S} {19,S} {20,S} {21,S}\\n6 C u0 p0 c0 {1,S} {22,S} {23,S} {24,S}\\n7 C u1 p0 c0 {4,S} {5,S} {9,S}\\n8 C u0 p0 c0 {3,S} {10,D} {11,S}\\n9 C u0 p0 c0 {7,S} {11,D} {12,S}\\n10 C u0 p0 c0 {1,S} {8,D} {13,S}\\n11 C u0 p0 c0 {8,S} {9,D} {25,S}\\n12 C u0 p0 c0 {9,S} {13,D} {26,S}\\n13 C u0 p0 c0 {10,S} {12,D} {27,S}\\n14 H u0 p0 c0 {3,S}\\n15 H u0 p0 c0 {3,S}\\n16 H u0 p0 c0 {4,S}\\n17 H u0 p0 c0 {4,S}\\n18 H u0 p0 c0 {4,S}\\n19 H u0 p0 c0 {5,S}\\n20 H u0 p0 c0 {5,S}\\n21 H u0 p0 c0 {5,S}\\n22 H u0 p0 c0 {6,S}\\n23 H u0 p0 c0 {6,S}\\n24 H u0 p0 c0 {6,S}\\n25 H u0 p0 c0 {11,S}\\n26 H u0 p0 c0 {12,S}\\n27 H u0 p0 c0 {13,S}\\n28 H u0 p0 c0 {2,S}\\n\\\"\\\"\\\"\\n expected_mol = Molecule().from_adjacency_list(expected_bonded_adjlist)\\n self.assertEqual(b_mol.to_adjacency_list(), expected_bonded_adjlist)\\n # the is_isomorphic test must come after the adjlist test since it changes the atom order\\n self.assertTrue(b_mol.is_isomorphic(expected_mol))\\n\\n s_mol, b_mol = converter.molecules_from_xyz(self.xyz10['dict'], multiplicity=1, charge=0)\\n self.assertIsNotNone(s_mol)\\n self.assertIsNotNone(b_mol)\\n for atom1, atom2 in zip(s_mol.atoms, b_mol.atoms):\\n self.assertEqual(atom1.symbol, atom2.symbol)\\n for atom1, symbol in zip(s_mol.atoms, self.xyz10['dict']['symbols']):\\n self.assertEqual(atom1.symbol, symbol)\\n\\n s_mol, b_mol = converter.molecules_from_xyz(self.xyz_dict_13, multiplicity=1, charge=0)\\n for atom1, atom2 in zip(s_mol.atoms, b_mol.atoms):\\n self.assertEqual(atom1.symbol, atom2.symbol)\\n for atom1, symbol in zip(s_mol.atoms, self.xyz_dict_13['symbols']):\\n self.assertEqual(atom1.symbol, symbol)\\n self.assertEqual(s_mol.multiplicity, 1)\\n self.assertEqual(b_mol.multiplicity, 1)\\n self.assertFalse(any(atom.radical_electrons for atom in b_mol.atoms))\",\n \"def test_rackspace_uploader_get_container(self, mock1):\\r\\n with patch('pybossa.uploader.rackspace.pyrax.cloudfiles') as mycf:\\r\\n cdn_enabled_mock = PropertyMock(return_value=False)\\r\\n type(fake_container).cdn_enabled = cdn_enabled_mock\\r\\n mycf.get_container.side_effect = NoSuchContainer\\r\\n\\r\\n calls = [call.get_container('user_3'),\\r\\n call.create_container('user_3'),\\r\\n call.make_container_public('user_3')\\r\\n ]\\r\\n u = RackspaceUploader()\\r\\n u.init_app(self.flask_app)\\r\\n assert u.get_container('user_3')\\r\\n mycf.assert_has_calls(calls, any_order=True)\",\n \"def __init__(self, struct_filename, name='molecules', cutoff=None, num_sampled_shards=None, max_num_atoms=None):\\n \\n print('Loading',name,'set')\\n self.name = name\\n \\n sharded_ds = shard.Sharded.load(struct_filename)\\n num_shards = sharded_ds.get_num_shards()\\n \\n self.num_atoms = []\\n self.symbols = []\\n self.charges = []\\n self.positions = []\\n self.index = []\\n self.data = []\\n self.data_keys = ['label'] # only one property here\\n \\n # Define indices and subsample if necessary \\n shard_indices = np.arange(num_shards)\\n if num_sampled_shards is not None and num_sampled_shards < num_shards:\\n shard_indices = np.random.choice(shard_indices, size=num_sampled_shards, replace=False, p=None)\\n \\n for shard_idx in shard_indices:\\n \\n struct_df = sharded_ds.read_shard(shard_idx)\\n labels_df = sharded_ds.read_shard(shard_idx, 'labels')\\n ensembles = labels_df['ensemble']\\n\\n for i, code in enumerate(ensembles):\\n\\n new_struct = struct_df[struct_df.ensemble==code]\\n new_labels = labels_df['label'][i]\\n\\n muta_chain = labels_df['chain'][i]\\n muta_resid = labels_df['residue'][i]\\n\\n # select the local environment of the mutated residue\\n sel_struct = select_environment(new_struct,muta_chain,muta_resid,cutoff)\\n print(code, len(new_struct),len(sel_struct))\\n\\n # move on with the next structure if this one is too large\\n if max_num_atoms is not None and len(sel_struct) > max_num_atoms:\\n continue\\n\\n subunits = sel_struct.subunit.unique()\\n for j, sub in enumerate(subunits):\\n\\n sub_df = sel_struct[sel_struct.subunit == sub]\\n sub_df = sub_df.reset_index(drop=True)\\n\\n # get element symbols\\n new_symbols = [ elem.title() for elem in sub_df.element ]\\n\\n # get atomic numbers\\n new_atnums = np.array([ pte.GetAtomicNumber(e.title()) for e in sub_df.element ])\\n # extract coordinates\\n conf_coord = dt.get_coordinates_from_df(sub_df)\\n \\n # append everything\\n self.symbols.append(new_symbols)\\n self.charges.append(new_atnums)\\n self.positions.append(conf_coord)\\n self.num_atoms.append(len(new_atnums))\\n\\n self.data.append(new_labels) # There will be twice as many structures as labels (order matters!!!)\\n \\n return\",\n \"def test_shared_wires(self):\\n wires = range(2)\\n estimation_wires = range(1, 3)\\n\\n with pytest.raises(ValueError, match=\\\"No wires can be shared between the wires\\\"):\\n quantum_monte_carlo(\\n lambda: None, wires=wires, target_wire=0, estimation_wires=estimation_wires\\n )\",\n \"def test_get_mass(self):\\n self.assertEqual(get_element_mass(1), (1.00782503224, 1)) # test input by integer\\n self.assertEqual(get_element_mass('Si'), (27.97692653465, 14)) # test string input and most common isotope\\n self.assertEqual(get_element_mass('C', 13), (13.00335483507, 6)) # test specific isotope\\n self.assertEqual(get_element_mass('Bk'), (247.0703073, 97)) # test a two-element array (no isotope data)\",\n \"def test_return_residue_pipe_fail(self):\\n\\n # Try to get a residue from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')\",\n \"def test_read_mol_input():\\n # good input\\n read_mol_input(os.path.join(TEST_DIR, \\\"example_mol_input_file.txt\\\"))\\n # good input with extra spaces\\n read_mol_input(os.path.join(TEST_DIR, \\\"example2_mol_input_file.txt\\\"))\\n # no such file error\\n assert_raises(FileNotFoundError, read_mol_input, 'no-such-file')\\n # qcm appears twice\\n assert_raises(ValueError, read_mol_input, os.path.join(TEST_DIR, \\\"bad1_mol_input_file.txt\\\"))\\n # missing struct type\\n assert_raises(ValueError, read_mol_input, os.path.join(TEST_DIR, \\\"bad2_mol_input_file.txt\\\"))\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_single_molecules_cycle_one(self, single_mol_system):\\n sequence = \\\"A\\\"\\n expected = [sequence] * (5 * 3)\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def _pyscf_molecule_object(basis, labels, coords):\\n mol = pyscf.gto.Mole(atom=zip(labels, coords),\\n unit=\\\"bohr\\\",\\n basis=basis)\\n mol.build()\\n return mol\",\n \"def test_call_wrapped_function(self):\\r\\n\\r\\n # adapted from test_app.test_cd_hit.test_cdhit_clusters_from_seqs\\r\\n\\r\\n exp = {'0': 'R27DLI_4812',\\r\\n '1': 'U1PLI_7889',\\r\\n '2': 'W3Cecum_4858',\\r\\n '3': 'R27DLI_3243',\\r\\n }\\r\\n app = GenericRepSetPicker(params={'Algorithm': 'most_abundant',\\r\\n 'ChoiceF': make_most_abundant, 'ChoiceFRequiresSeqs': True})\\r\\n obs = app(self.tmp_seq_filepath, self.tmp_otu_filepath)\\r\\n self.assertEqual(obs, exp)\",\n \"def test_molecule_venv(host):\\n\\n assert \\\"molecule\\\" in host.pip_package.get_packages(\\n pip_path=\\\"/opt/virtualenv/molecule/bin/pip\\\"\\n )\\n molecule_command = host.run(molecule_test_command)\\n\\n assert molecule_command.rc == 0\\n assert \\\"2.22\\\" in molecule_command.stdout\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_set_molecule_error(self):\\n mol = Molecule.from_smiles(\\\"CCO\\\")\\n atom = Atom(6, 0, False)\\n atom.molecule = mol\\n with pytest.raises(AssertionError, match=\\\"already has an associated molecule\\\"):\\n atom.molecule = mol\",\n \"def test_validation_correct_molecules():\\n paths = examples_paths()\\n molecules = [\\n {'name': 'toluene', 'leap': {'parameters': 'leaprc.gaff'}},\\n {'name': 'toluene', 'leap': {'parameters': ['leaprc.gaff', 'toluene.frcmod']}},\\n {'name': 'p-xylene', 'antechamber': {'charge_method': 'bcc'}},\\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'},\\n 'antechamber': {'charge_method': None}},\\n {'name': 'p-xylene', 'antechamber': {'charge_method': 'bcc'},\\n 'epik': {'ph': 7.6, 'ph_tolerance': 0.7, 'tautomerize': False, 'select': 0}},\\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'},\\n 'antechamber': {'charge_method': None}, 'epik': {'select': 1}},\\n\\n {'filepath': paths['abl']},\\n {'filepath': paths['abl'], 'leap': {'parameters': 'leaprc.ff99SBildn'}},\\n {'filepath': paths['abl'], 'leap': {'parameters': 'leaprc.ff99SBildn'}, 'select': 1},\\n {'filepath': paths['abl'], 'select': 'all'},\\n {'filepath': paths['abl'], 'select': 'all', 'strip_protons': True},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {}},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'add_missing_residues': True}},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'add_missing_atoms': 'all', 'ph': '8.0'}},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'remove_heterogens': 'all'}},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'replace_nonstandard_residues': True}},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'apply_mutations': {'chain_id': 'A', 'mutations': 'T85I'}}},\\n {'filepath': paths['abl'], 'select': 'all', 'modeller': {'apply_mutations': {'chain_id': 'A', 'mutations': 'T85I'}}},\\n {'filepath': paths['abl'], 'select': 'all', 'modeller': {'apply_mutations': {'chain_id': 'A', 'mutations': 'WT'}}},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'apply_mutations': {'chain_id': 'A', 'mutations': 'I8A/T9A'}}},\\n {'filepath': paths['toluene'], 'leap': {'parameters': 'leaprc.gaff'}},\\n {'filepath': paths['benzene'], 'epik': {'select': 1, 'tautomerize': False}},\\n # Regions tests, make sure all other combos still work\\n {'name': 'toluene', 'regions': {'a_region': 4}},\\n {'name': 'toluene', 'regions': {'a_region': 'dsl string'}},\\n {'name': 'toluene', 'regions': {'a_region': [0, 2, 3]}},\\n {'name': 'toluene', 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}},\\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': 4}},\\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': 'dsl string'}},\\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': [0, 2, 3]}},\\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}},\\n {'filepath': paths['abl'], 'regions': {'a_region': 4}},\\n {'filepath': paths['abl'], 'regions': {'a_region': 'dsl string'}},\\n {'filepath': paths['abl'], 'regions': {'a_region': [0, 2, 3]}},\\n {'filepath': paths['abl'], 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}},\\n {'filepath': paths['toluene'], 'regions': {'a_region': 4}},\\n {'filepath': paths['toluene'], 'regions': {'a_region': 'dsl string'}},\\n {'filepath': paths['toluene'], 'regions': {'a_region': [0, 2, 3]}},\\n {'filepath': paths['toluene'], 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}}\\n ]\\n for molecule in molecules:\\n yield ExperimentBuilder._validate_molecules, {'mol': molecule}\",\n \"def test_get_composition(self):\\n pass\",\n \"def test_get_molecule_least_similar_to(self):\\n csv_fpath = self.smiles_seq_to_xl_or_csv(ftype=\\\"csv\\\")\\n for descriptor in SUPPORTED_FPRINTS:\\n for similarity_measure in SUPPORTED_SIMILARITIES:\\n molecule_set = MoleculeSet(\\n molecule_database_src=csv_fpath,\\n molecule_database_src_type=\\\"csv\\\",\\n fingerprint_type=descriptor,\\n similarity_measure=similarity_measure,\\n is_verbose=False,\\n )\\n for mol_smile, mol in zip(TEST_SMILES,\\n molecule_set.molecule_database):\\n compare_task = CompareTargetMolecule(\\n target_molecule_smiles=mol_smile)\\n [furthest_mol], [similarity] = compare_task.\\\\\\n get_hits_dissimilar_to(molecule_set)\\n mol_similarities = molecule_set.compare_against_molecule(\\n mol)\\n self.assertEqual(\\n np.min(mol_similarities),\\n mol.get_similarity_to(\\n molecule_set.molecule_database[furthest_mol],\\n molecule_set.similarity_measure\\n ),\\n f\\\"Expected furthest mol to have minimum \\\"\\n f\\\"similarity to target molecule \\\"\\n f\\\"using similarity measure: {similarity_measure}, \\\"\\n f\\\"descriptor: {descriptor}, \\\"\\n f\\\"for molecule {mol.mol_text}\\\",\\n )\\n self.assertGreaterEqual(similarity, 0.,\\n \\\"Expected similarity value to \\\"\\n \\\"be >= 0.\\\"\\n f\\\"using similarity measure: \\\"\\n f\\\"{similarity_measure}, \\\"\\n f\\\"descriptor: {descriptor}, \\\"\\n f\\\"for molecule {mol.mol_text}\\\")\\n self.assertLessEqual(similarity, 1.,\\n \\\"Expected similarity value to \\\"\\n \\\"be <= 1.\\\"\\n f\\\"using similarity measure: \\\"\\n f\\\"{similarity_measure}, \\\"\\n f\\\"descriptor: {descriptor}, \\\"\\n f\\\"for molecule {mol.mol_text}\\\"\\n )\",\n \"def _vmd_script_molecule(mole, filename=\\\"molecule.xyz\\\"):\\n output = \\\"# load new molecule\\\\n\\\"\\n if len(mole.atom) == 0:\\n raise ValueError(\\\"Need at least one molecule file with coordinates.\\\")\\n atoms = mole.atom\\n natoms = len(mole.atom[0:, 0])\\n f = open(filename, \\\"w\\\")\\n f.write(str(natoms) + \\\"\\\\n\\\\n\\\")\\n for i in range(0, natoms):\\n symb = str(atoms[i, 0])\\n coord = \\\" \\\".join(map(str, atoms[i, 1].tolist()))\\n f.write(symb + \\\" \\\" + coord + \\\"\\\\n\\\")\\n f.close()\\n output += (\\n \\\"mol {0} {1} type {2} first 0 last -1 step 1 filebonds 1 autobonds 1 waitfor all\\\"\\n \\\"\\\\n\\\".format(\\\"new\\\", filename, \\\"{xyz}\\\")\\n )\\n output += \\\"#\\\\n\\\" \\\"# representation of the atoms\\\\n\\\"\\n output += \\\"mol representation CPK 1.000000 0.300000 118.000000 131.000000\\\\n\\\"\\n output += (\\n \\\"mol delrep 0 top\\\\n\\\"\\n \\\"mol color Element\\\\n\\\"\\n \\\"mol selection {{all}}\\\\n\\\"\\n \\\"mol material Opaque\\\\n\\\"\\n \\\"mol addrep top\\\\n\\\"\\n \\\"#\\\\n\\\"\\n )\\n return output\",\n \"def fetchCooler(c, regions, coolerFetch = lambda coo, ext:coo.matrix(balance=True, sparse=True).fetch(ext),\\n mask=True, force=False, ):\\n regions = [list(i) for i in regions]\\n resolution = c.binsize\\n\\n for i in regions:\\n if i[1] == None:\\n i[1] = 0 \\n if i[2] == None:\\n i[2] = c.chromsizes[i[0]]\\n\\n \\n for a in regions: \\n if str(a[0]) not in c.chromnames:\\n raise ValueError(\\\"Chromosome {0} from regions not found in cooler\\\".format(a))\\n if (a[1] % resolution) != 0:\\n raise ValueError(\\\"Start of an region should be a multiple fo resolution\\\")\\n \\n# bins = c.bins()[:]\\n \\n# # managing masks \\n# if mask is False: \\n# bins[\\\"mask\\\"] = 1 \\n# elif mask is None:\\n# assert \\\"mask\\\" in bins.columns\\n# elif mask is True: \\n# pass \\n# elif callable(mask):\\n# pass \\n# else:\\n# bins[\\\"mask\\\"] = mask \\n \\n \\n for region in regions:\\n matrix = coolerFetch(c, region)\\n try: # setting matrix nans to zeros.\\n matrix.data = np.nan_to_num(matrix.data, copy=False)\\n except TypeError: #workaround for old numpy versions\\n matrix.data = np.nan_to_num(matrix.data)\\n# st,end = c.extent(region)\\n# subbins = bins[st:end].copy()\\n if mask is True: \\n newmask = np.array((matrix.sum(axis=0) > 0 ))[0]\\n# if callable(mask):\\n# new_mask = mask(matrix)\\n# subbins[\\\"mask\\\"] = newmask \\n\\n assert len(newmask) == matrix.shape[0]\\n\\n yield matrix, newmask\",\n \"def test_compute_partial_charges(self):\\n # TODO: Test only one molecule for speed?\\n # TODO: Do we need to deepcopy each molecule, or is setUp called separately for each test method?\\n import numpy as np\\n from simtk import unit\\n\\n # Do not modify original molecules.\\n molecules = copy.deepcopy(mini_drug_bank())\\n\\n # Test a single toolkit at a time\\n # Removed ['amber', 'amberff94'] from OE list, as those won't find the residue types they're expecting\\n toolkit_to_charge_method = {\\n OpenEyeToolkitWrapper: [\\n \\\"mmff\\\",\\n \\\"mmff94\\\",\\n \\\"am1bcc\\\",\\n \\\"am1bccnosymspt\\\",\\n \\\"am1bccelf10\\\",\\n ],\\n AmberToolsToolkitWrapper: [\\\"bcc\\\", \\\"gas\\\", \\\"mul\\\"],\\n }\\n\\n manual_skips = []\\n\\n manual_skips.append(\\n \\\"ZINC1564378\\\"\\n ) # Warning: OEMMFF94Charges: assigning OEMMFFAtomTypes failed on mol .\\n manual_skips.append(\\n \\\"ZINC00265517\\\"\\n ) # Warning: OEMMFF94Charges: assigning OEMMFFAtomTypes failed on mol .\\n\\n for toolkit in list(toolkit_to_charge_method.keys()):\\n toolkit_registry = ToolkitRegistry(toolkit_precedence=[toolkit])\\n for charge_model in toolkit_to_charge_method[toolkit]:\\n c = 0\\n for molecule in molecules[:1]: # Just test first molecule to save time\\n c += 1\\n if molecule.name in manual_skips: # Manual skips, hopefully rare\\n continue\\n molecule.compute_partial_charges(\\n charge_model=charge_model, toolkit_registry=toolkit_registry\\n )\\n charges1 = molecule._partial_charges\\n # Make sure everything isn't 0s\\n assert (abs(charges1 / unit.elementary_charge) > 0.01).any()\\n # Check total charge\\n charges_sum_unitless = charges1.sum() / unit.elementary_charge\\n # if abs(charges_sum_unitless - float(molecule.total_charge)) > 0.0001:\\n # print('c {} molecule {} charge_sum {} molecule.total_charge {}'.format(c, molecule.name,\\n # charges_sum_unitless,\\n # molecule.total_charge))\\n # assert_almost_equal(charges_sum_unitless, molecule.total_charge, decimal=4)\\n\\n # Call should be faster second time due to caching\\n # TODO: Implement caching\\n molecule.compute_partial_charges(\\n charge_model=charge_model, toolkit_registry=toolkit_registry\\n )\\n charges2 = molecule._partial_charges\\n assert np.allclose(charges1, charges2, atol=0.002)\",\n \"def fixture_output_block():\\n return Mock()\",\n \"def test_sample_container_init(self):\\n self.assertEqual({}, self.container._data)\",\n \"def mol_from_cbor(cbor_str: str) -> masm.Molecule:\\n serializer = masm.JsonSerialization\\n cbor_binary = serializer.base_64_decode(cbor_str)\\n cbor_format = serializer.BinaryFormat.CBOR\\n serialization = serializer(cbor_binary, cbor_format)\\n return serialization.to_molecule()\",\n \"def __init__(self, nr_molecules, surface_size):\\n self.molecules = []\\n for i in range(nr_molecules):\\n self.try_add_molecule(100, surface_size)\\n print(\\\"nr_molecules:\\\", len(self.molecules))\",\n \"def test_input_sanity():\\n energy = MagicMock()\\n\\n with raises(NotImplementedError) as exception:\\n MonteCarlo(sum, [1, 1, 1], 0e0)\\n with raises(ValueError) as exception:\\n MonteCarlo(energy, [1, 1, 1], temperature=-1e0)\\n\\n with raises(TypeError) as exception:\\n MonteCarlo(energy, [1.0, 2, 3])\\n with raises(ValueError) as exception:\\n MonteCarlo(energy, [-1, 2, 3])\\n with raises(ValueError) as exception:\\n MonteCarlo(energy, [[1, 2, 3], [3, 4, 5]])\\n with raises(ValueError) as exception:\\n MonteCarlo(energy, [3])\\n with raises(ValueError) as exception:\\n MonteCarlo(energy, [0, 0])\",\n \"def test_package_1():\\n\\n @package\\n def resdiv(gnd, vin, vout):\\n res = Part(\\\"Device\\\", \\\"R\\\", dest=TEMPLATE)\\n r1 = res(value=\\\"1k\\\")\\n r2 = res(value=\\\"500\\\")\\n\\n cap = Part(\\\"Device\\\", \\\"C\\\", dest=TEMPLATE)\\n c1 = cap()\\n c2 = cap(value=\\\"1uF\\\")\\n\\n bus1 = Bus(\\\"BB\\\", 10)\\n\\n vin += r1[1], c1[1] # Connect the input to the first resistor.\\n gnd += r2[2], c2[2] # Connect the second resistor to ground.\\n vout += (\\n r1[2],\\n c1[2],\\n r2[1],\\n c2[1],\\n ) # Output comes from the connection of the two resistors.\\n\\n resdiv1 = resdiv()\\n resdiv2 = resdiv()\\n\\n vin, vout, gnd = Net(\\\"VI\\\"), Net(\\\"VO\\\"), Net(\\\"GND\\\")\\n\\n resdiv1.gnd += gnd\\n resdiv1.vin += vin\\n resdiv1.vout += vout\\n\\n resdiv2[\\\"gnd\\\"] += gnd\\n resdiv2[\\\"vin\\\"] += vin\\n resdiv2[\\\"vout\\\"] += vout\\n\\n gnd += Pin()\\n vin += Pin()\\n\\n default_circuit.instantiate_packages()\\n\\n assert len(Net.fetch(\\\"GND\\\")) == 5\\n assert len(Net.fetch(\\\"VI\\\")) == 5\\n assert len(Net.fetch(\\\"VO\\\")) == 8\\n\\n assert len(resdiv1.gnd) == 5\\n assert len(resdiv1.vin) == 5\\n assert len(resdiv1.vout) == 8\\n\\n assert len(resdiv2[\\\"gnd\\\"]) == 5\\n assert len(resdiv2[\\\"vin\\\"]) == 5\\n assert len(resdiv2[\\\"vout\\\"]) == 8\",\n \"def getStructureType(entry, seed_index=0, supercell = 2,return_SS=False):\\n \\n \\n # Entry is a list of the necessary components of the TSA. \\n # Makes it easier to parallelize\\n structure, tol, mp_id = entry\\n norm_tol=tol-1\\n\\n s = copy.deepcopy(structure)\\n heterogeneous = False\\n heterogeneous_SS = False\\n\\n # Distance matrix (rowA, columnB) shows distance between\\n # atoms A and B, taking PBCs into account.\\n \\n binary_matrix = getDistMat(s,norm_tol)\\n cluster = buildNetwork(binary_matrix,seed_index)\\n\\n compo = Composition.from_dict(Counter([s[l].specie.name for \\n l in list(cluster)]))\\n if compo.reduced_formula != s.composition.reduced_formula:\\n # i.e. the cluster does not have the same composition\\n # as the overall crystal; therefore there are other\\n # clusters of varying composition.\\n heterogeneous = True\\n og_cluster = set()\\n og_cluster.update(cluster)\\n old_cluster_size = len(cluster)\\n # Increase structure to determine dimensionality\\n\\n s = copy.deepcopy(structure)\\n s.make_supercell(supercell)\\n seed_index*=supercell**3\\n\\n\\n\\n binary_matrix = getDistMat(s,norm_tol)\\n cluster = buildNetwork(binary_matrix,seed_index)\\n\\n\\n if cluster!=set():\\n new_cluster_size = len(cluster)\\n # Get ratio of original and final cluster lengths\\n scale = new_cluster_size/old_cluster_size\\n compo = Composition.from_dict(Counter([s[l].specie.name for l in\\n list(cluster)]))\\n if compo.reduced_formula != s.composition.reduced_formula:\\n # i.e. the cluster does not have the same composition\\n # as the overall crystal; therefore there are other\\n # clusters of varying composition.\\n heterogeneous_SS = True\\n motiif = getDim(scale,supercell)\\n if heterogeneous or heterogeneous_SS:\\n motiif += \\\"_heter\\\"\\n\\n if return_SS:\\n return [motiif,mp_id,tol,compo.reduced_formula,list(cluster)]\\n else:\\n return [motiif,mp_id,tol,compo.reduced_formula,list(og_cluster)]\",\n \"def mock_component():\\n component = Mock()\\n component.free_parameters = flex.double([1.0])\\n component.free_parameter_esds = None\\n component.n_params = 1\\n component.var_cov_matrix = sparse.matrix(1, 1)\\n return component\",\n \"def featurize(self):\\n\\n self.make_molecule()\\n\\n self.described_molecules = self.calculator.pandas(self.data.molecules)\\n self.described_molecules.index = self.data.index\\n\\n self.described_molecules = pd.concat([self.data, self.described_molecules], axis=1)\\n\\n return self.described_molecules\",\n \"def get_mol_info(self):\\n return\",\n \"def test_simulationRun(self):\\n self.opt = { 'temperature' : 300.0, 'friction' : 1, 'dt' : 0.00002,\\n 'nIter' : 2, 'nstepsNC' : 2, 'nstepsMD' : 1, 'nprop' : 1,\\n 'nonbondedMethod' : 'NoCutoff', 'constraints': 'HBonds',\\n 'trajectory_interval' : 1, 'reporter_interval' : 1,\\n 'outfname' : 'mc-test',\\n 'platform' : None,\\n 'constraints' : 'HBonds',\\n 'mc_per_iter' : 2 }\\n\\n structure = self.full_struct\\n class SetRotationMove(RandomLigandRotationMove):\\n def __init__(self, structure, resname='LIG'):\\n super(SetRotationMove, self).__init__(structure, resname)\\n\\n def move(self, context):\\n \\\"\\\"\\\"Function that performs a random rotation about the\\n center of mass of the ligand.\\n \\\"\\\"\\\"\\n #TODO: check if we need to deepcopy\\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\\n\\n self.positions = positions[self.atom_indices]\\n self.center_of_mass = self.getCenterOfMass(self.positions, self.masses)\\n reduced_pos = self.positions - self.center_of_mass\\n\\n # Define random rotational move on the ligand\\n #set rotation so that test is reproducible\\n set_rotation_matrix = np.array([[-0.62297988, -0.17349253, 0.7627558 ],\\n [ 0.55082352, -0.78964857, 0.27027502],\\n [ 0.55541834, 0.58851973, 0.58749893]])\\n\\n\\n #set_rotation_matrix = np.array([[1, 0, 0],\\n # [0, 1, 0],\\n # [0, 0, 1]])\\n\\n #multiply lig coordinates by rot matrix and add back COM translation from origin\\n rot_move = np.dot(reduced_pos, set_rotation_matrix) * positions.unit + self.center_of_mass\\n\\n # Update ligand positions in nc_sim\\n for index, atomidx in enumerate(self.atom_indices):\\n positions[atomidx] = rot_move[index]\\n context.setPositions(positions)\\n positions = context.getState(getPositions=True).getPositions(asNumpy=True)\\n self.positions = positions[self.atom_indices]\\n return context\\n\\n\\n self.model = SetRotationMove(structure, resname='ALA')\\n #self.model = RandomLigandRotationMove(structure, resname='ALA')\\n\\n self.model.atom_indices = range(22)\\n self.model.topology = structure[self.model.atom_indices].topology\\n self.model.positions = structure[self.model.atom_indices].positions\\n self.model.calculateProperties()\\n\\n self.mover = MoveEngine(self.model)\\n #Initialize the SimulationFactory object\\n sims = SimulationFactory(structure, self.mover, **self.opt)\\n #print(sims)\\n system = sims.generateSystem(structure, **self.opt)\\n simdict = sims.createSimulationSet()\\n alch_system = sims.generateAlchSystem(system, self.model.atom_indices)\\n self.nc_sim = sims.generateSimFromStruct(structure, self.mover, alch_system, ncmc=True, **self.opt)\\n self.model.calculateProperties()\\n self.initial_positions = self.nc_sim.context.getState(getPositions=True).getPositions(asNumpy=True)\\n mc_sim = Simulation(sims, self.mover, **self.opt)\\n #monkeypatch to access acceptance value\\n def nacceptRejectMC(self, temperature=300, **opt):\\n \\\"\\\"\\\"Function that chooses to accept or reject the proposed move.\\n \\\"\\\"\\\"\\n md_state0 = self.current_state['md']['state0']\\n md_state1 = self.current_state['md']['state1']\\n log_mc = (md_state1['potential_energy'] - md_state0['potential_energy']) * (-1.0/self.nc_sim.context._integrator.kT)\\n randnum = math.log(np.random.random())\\n\\n if log_mc > randnum:\\n self.accept += 1\\n print('MC MOVE ACCEPTED: log_mc {} > randnum {}'.format(log_mc, randnum) )\\n self.md_sim.context.setPositions(md_state1['positions'])\\n else:\\n self.reject += 1\\n print('MC MOVE REJECTED: log_mc {} < {}'.format(log_mc, randnum) )\\n self.md_sim.context.setPositions(md_state0['positions'])\\n self.log_mc = log_mc\\n self.md_sim.context.setVelocitiesToTemperature(self.opt['temperature'])\\n mc_sim.acceptRejectMC = nacceptRejectMC\\n nacceptRejectMC.__get__(mc_sim)\\n mc_sim.acceptRejectMC = types.MethodType(nacceptRejectMC, mc_sim)\\n mc_sim.runMC(self.opt['nIter'])\\n #get log acceptance\\n print(mc_sim.log_mc)\\n #if mc is working, should be around -24.1\\n assert mc_sim.log_mc <= -23.8 and mc_sim.log_mc >= -24.3\",\n \"def test_from_qcschema_no_client(self):\\n\\n import json\\n\\n # As the method can take a record instance or a dict with JSON encoding test both\\n # test incomplete dict\\n example_dict = {\\\"name\\\": \\\"CH4\\\"}\\n with pytest.raises(KeyError):\\n mol = Molecule.from_qcschema(example_dict)\\n\\n # test an object that is not a record\\n wrong_object = \\\"CH4\\\"\\n with pytest.raises(AttributeError):\\n mol = Molecule.from_qcschema(wrong_object)\\n\\n with open(get_data_file_path(\\\"molecules/qcportal_molecules.json\\\")) as json_file:\\n # test loading the dict representation from a json file\\n json_mol = json.load(json_file)\\n mol = Molecule.from_qcschema(json_mol)\\n # now make a molecule from the canonical smiles and make sure they are isomorphic\\n can_mol = Molecule.from_smiles(\\n json_mol[\\\"attributes\\\"][\\\"canonical_isomeric_smiles\\\"]\\n )\\n assert mol.is_isomorphic_with(can_mol) is True\",\n \"def test_from_qcschema_no_client(self):\\n\\n import json\\n\\n # As the method can take a record instance or a dict with JSON encoding test both\\n # test incomplete dict\\n example_dict = {\\\"name\\\": \\\"CH4\\\"}\\n with pytest.raises(KeyError):\\n mol = Molecule.from_qcschema(example_dict)\\n\\n # test an object that is not a record\\n wrong_object = \\\"CH4\\\"\\n with pytest.raises(AttributeError):\\n mol = Molecule.from_qcschema(wrong_object)\\n\\n with open(get_data_file_path(\\\"molecules/qcportal_molecules.json\\\")) as json_file:\\n # test loading the dict representation from a json file\\n json_mol = json.load(json_file)\\n mol = Molecule.from_qcschema(json_mol)\\n # now make a molecule from the canonical smiles and make sure they are isomorphic\\n can_mol = Molecule.from_smiles(\\n json_mol[\\\"attributes\\\"][\\\"canonical_isomeric_smiles\\\"]\\n )\\n assert mol.is_isomorphic_with(can_mol) is True\",\n \"def ReadMaterialInfoAndMakeMaterialsMolFiles(OutputPath,MaterialPathList,CutOff,Multiple,PDBCharges,MaterialInputFormat):\\r\\n\\r\\n MaterialInfoList=[]\\r\\n ID=0\\r\\n Time = time.strftime('%Y-%m-%d', time.localtime(time.time()))\\r\\n\\r\\n if os.path.exists(os.path.join(OutputPath,'Mols')): pass\\r\\n else: os.mkdir(os.path.join(OutputPath,'Mols'))\\r\\n\\r\\n for Range,MaterialPath in enumerate(MaterialPathList):\\r\\n\\r\\n\\r\\n AtomNum=0\\r\\n MaterialsCharge = 0.0\\r\\n MaterialInfo,ElementList,CellLength,CellAngle,AtomInfo,AtomInfoList,CellSize=[],[],[],[],[],[],[]\\r\\n\\r\\n MaterialName=os.path.splitext(MaterialPath.split('/')[-1])[0]\\r\\n MaterialInfo.append(MaterialName)\\r\\n MaterialNewName=re.sub('\\\\W','',MaterialName)\\r\\n\\r\\n if len(MaterialNewName) > 20:\\r\\n ID+=1\\r\\n MaterialNewName=MaterialNewName[:20]\\r\\n MaterialNewName=MaterialNewName+'_ID_'+str(ID)\\r\\n\\r\\n if MaterialInputFormat == 'pdb':\\r\\n with open(MaterialPath,'r') as File:\\r\\n with open(os.path.join(OutputPath,'Mols',MaterialNewName)+'.mol','w') as Mol:\\r\\n\\r\\n for Line in File.readlines():\\r\\n if Line[0:6] == 'CRYST1':\\r\\n CellLength.append(float('%.3f' % (float(Line[6:15].strip()))))\\r\\n CellLength.append(float('%.3f' % (float(Line[15:24].strip()))))\\r\\n CellLength.append(float('%.3f' % (float(Line[24:33].strip()))))\\r\\n CellAngle.append(float('%.2f' % (float(Line[33:40].strip()))))\\r\\n CellAngle.append(float('%.2f' % (float(Line[40:47].strip()))))\\r\\n CellAngle.append(float('%.2f' % (float(Line[47:54].strip()))))\\r\\n elif Line[0:6] == 'ATOM ':\\r\\n AtomNum += 1\\r\\n AtomInfo = []\\r\\n AtomInfo.append(int(Line[6:11].strip())) # serial\\r\\n AtomInfo.append(str(Line[12:16].strip())) # atom name\\r\\n AtomInfo.append(float(Line[30:38].strip())) # x\\r\\n AtomInfo.append(float(Line[38:46].strip())) # y\\r\\n AtomInfo.append(float(Line[46:54].strip())) # z\\r\\n\\r\\n if PDBCharges == True:\\r\\n AtomInfo.append(float(Line[54:60].strip())) # charge\\r\\n MaterialsCharge += float(Line[54:60].strip())\\r\\n else:\\r\\n AtomInfo.append(float('0.0')) # charge\\r\\n\\r\\n ElementList.append(str(Line[12:16].strip())) # atom name list\\r\\n AtomInfoList.append(AtomInfo)\\r\\n\\r\\n if abs(MaterialsCharge) < 0.001:\\r\\n Mol.write('# Basic Molecule Information\\\\n# Created by PyMSATm at %s\\\\n'\\r\\n 'Molecule_name: %s \\\\n\\\\nCoord_Info: Listed Cartesian None\\\\n' % (Time, MaterialNewName))\\r\\n else: Mol.write('# Basic Molecule Information\\\\n# Created by PyMSATm at %s\\\\n'\\r\\n 'Molecule_name: %s CHARGED\\\\n\\\\nCoord_Info: Listed Cartesian None\\\\n' % (Time, MaterialNewName))\\r\\n\\r\\n Mol.write(' %d\\\\n'%(AtomNum))\\r\\n\\r\\n for AtomInfo2 in AtomInfoList:\\r\\n Mol.write('{:<6d} {:>8} {:>8} {:>8} {:>6} {:>6} 0 0\\\\n'.format(AtomInfo2[0],\\r\\n AtomInfo2[2],AtomInfo2[3],AtomInfo2[4],AtomInfo2[1],AtomInfo2[5]))\\r\\n\\r\\n Mol.write('\\\\nFundcell_Info: Listed\\\\n%.5f %.5f %.5f\\\\n%.5f %.5f %.5f\\\\n0.00000 0.00000 0.00000\\\\n%.5f %.5f %.5f'%(CellLength[0],\\r\\n CellLength[1],CellLength[2],CellAngle[0],CellAngle[1],CellAngle[2],CellLength[0],CellLength[1],CellLength[2]))\\r\\n\\r\\n if MaterialInputFormat == 'mol':\\r\\n\\r\\n KeyOne,KeyTwo,KeyThree= False,False,False\\r\\n\\r\\n with open(MaterialPath, 'r') as File:\\r\\n with open(os.path.join(OutputPath, 'Mols', MaterialNewName) + '.mol', 'w') as Mol:\\r\\n\\r\\n for Line in File.readlines():\\r\\n if Line.strip(): # skip blank\\r\\n WordList = Line.strip().split()\\r\\n if WordList[0] == 'Coord_Info:':\\r\\n KeyOne = True\\r\\n elif WordList[0] == 'Fundcell_Info:':\\r\\n KeyOne = False\\r\\n KeyTwo = True\\r\\n elif len(WordList) > 1 and KeyOne == True:\\r\\n AtomNum += 1\\r\\n AtomInfo = []\\r\\n AtomInfo.append(int(WordList[0].strip())) # serial\\r\\n AtomInfo.append(str(WordList[4].strip())) # atom name\\r\\n AtomInfo.append(float(WordList[1].strip())) # x\\r\\n AtomInfo.append(float(WordList[2].strip())) # y\\r\\n AtomInfo.append(float(WordList[3].strip())) # z\\r\\n AtomInfo.append(float(WordList[5].strip())) # charge\\r\\n ElementList.append(str(WordList[4].strip())) # atom name list\\r\\n AtomInfoList.append(AtomInfo)\\r\\n MaterialsCharge += float(WordList[5].strip())\\r\\n elif len(WordList) > 1 and KeyTwo == True:\\r\\n KeyTwo = False\\r\\n KeyThree = True\\r\\n CellLength.append(float('%.3f' % (float(WordList[0].strip()))))\\r\\n CellLength.append(float('%.3f' % (float(WordList[1].strip()))))\\r\\n CellLength.append(float('%.3f' % (float(WordList[2].strip()))))\\r\\n elif len(WordList) > 1 and KeyThree == True:\\r\\n KeyThree = False\\r\\n CellAngle.append(float('%.2f' % (float(WordList[0].strip()))))\\r\\n CellAngle.append(float('%.2f' % (float(WordList[1].strip()))))\\r\\n CellAngle.append(float('%.2f' % (float(WordList[2].strip()))))\\r\\n\\r\\n if abs(MaterialsCharge) < 0.001:\\r\\n Mol.write('# Basic Molecule Information\\\\n# Created by PyMSATm at %s\\\\n'\\r\\n 'Molecule_name: %s \\\\n\\\\nCoord_Info: Listed Cartesian None\\\\n' % (\\r\\n Time, MaterialNewName))\\r\\n else:\\r\\n Mol.write('# Basic Molecule Information\\\\n# Created by PyMSATm at %s\\\\n'\\r\\n 'Molecule_name: %s CHARGED\\\\n\\\\nCoord_Info: Listed Cartesian None\\\\n' % (\\r\\n Time, MaterialNewName))\\r\\n\\r\\n Mol.write(' %d\\\\n' % (AtomNum))\\r\\n\\r\\n for AtomInfo2 in AtomInfoList:\\r\\n Mol.write('{:<6d} {:>8.4f} {:>8.4f} {:>8.4f} {:>8s} {:>10.6f} 0 0\\\\n'.format(AtomInfo2[0], AtomInfo2[2],\\r\\n AtomInfo2[3], AtomInfo2[4],\\r\\n AtomInfo2[1], AtomInfo2[5]))\\r\\n\\r\\n Mol.write(\\r\\n '\\\\nFundcell_Info: Listed\\\\n%.4f %.4f %.4f\\\\n%.4f %.4f %.4f\\\\n0.00000 0.00000 0.00000\\\\n%.4f %.4f %.4f' % (\\r\\n CellLength[0], CellLength[1], CellLength[2], CellAngle[0], CellAngle[1], CellAngle[2],\\r\\n CellLength[0], CellLength[1], CellLength[2]))\\r\\n\\r\\n if CellAngle[0] == 90.0 and CellAngle[1] == 90.0 and CellAngle[2] == 90.0:\\r\\n Orthogonality = True\\r\\n else: Orthogonality=False\\r\\n\\r\\n if Orthogonality == True:\\r\\n for Length in CellLength:\\r\\n Count = 1\\r\\n while Length * Count < CutOff * Multiple+1:\\r\\n Count += 1\\r\\n CellSize.append(str(Count))\\r\\n else: # definite the lengths of x, y, z in orthogonal directions\\r\\n\\r\\n SinA, SinB, SinC = math.sin(math.radians(CellAngle[0])), math.sin(math.radians(CellAngle[1])), math.sin(math.radians(CellAngle[2]))\\r\\n CosA, CosB, CosC = math.cos(math.radians(CellAngle[0])), math.cos(math.radians(CellAngle[1])), math.cos(math.radians(CellAngle[2]))\\r\\n CosParameterA = (CosC * CosA - CosB) / (SinC * SinA)\\r\\n SinParameterA = math.sqrt(1 - CosParameterA ** 2)\\r\\n CosParameterB = (CosA * CosB - CosC) / (SinA * SinB)\\r\\n SinParameterB = math.sqrt(1 - CosParameterB ** 2)\\r\\n CosParameterC = (CosB * CosC - CosA) / (SinB * SinC)\\r\\n SinParameterC = math.sqrt(1 - CosParameterC ** 2)\\r\\n x=CellLength[0]*SinC*SinParameterA\\r\\n y=CellLength[1]*SinA*SinParameterB\\r\\n z=CellLength[2]*SinB*SinParameterC\\r\\n TransLength=[x,y,z]\\r\\n\\r\\n for Length in TransLength:\\r\\n Count = 1\\r\\n while float(Length) * Count < CutOff * Multiple+1:\\r\\n Count += 1\\r\\n CellSize.append(str(Count))\\r\\n\\r\\n MaterialInfo.append(AtomNum)\\r\\n MaterialInfo.append(CellLength)\\r\\n MaterialInfo.append(CellAngle)\\r\\n MaterialInfo.append(CellSize)\\r\\n MaterialInfo.append(list(set(ElementList)))\\r\\n MaterialInfo.append(Orthogonality)\\r\\n MaterialInfo.append(MaterialNewName)\\r\\n MaterialInfoList.append(MaterialInfo)\\r\\n\\r\\n return MaterialInfoList\",\n \"def testExecute(self):\\n client = ICSClientFactory(self.config, 'slave', 'master') \\n\\n #Test reading and writing coils\\n reply = client.execute(cst.READ_COILS, 10, 2)\\n assert reply[0] == False \\n assert reply[1] == False\\n reply = client.execute(cst.WRITE_SINGLE_COIL, 10, 1, output_value=1)\\n reply = client.execute(cst.READ_COILS, 10, 2)\\n assert reply[0] == True\\n assert reply[1] == False\\n reply = client.execute(cst.WRITE_MULTIPLE_COILS, 10, 2,\\n output_value=[0,1])\\n reply = client.execute(cst.READ_COILS, 10, 2)\\n assert reply[1] == True\\n assert reply[0] == False\\n \\n #Test reading and writing input regs\\n #reply = client.execute(cst.READ_INPUT_REGISTERS, 30002, 1)\\n #print \\\"BRDEBUG: Reply: \\\", reply\\n #assert reply[0] == 17\\n\\n #Test reading and setting holding regs\\n reply = client.execute(cst.READ_HOLDING_REGISTERS, 40003, 2)\\n #print \\\"BRDEBUG: Reply\\\", reply\\n assert reply[0] == 16752 \\n assert reply[1] == 0 \\n reply = client.execute(cst.WRITE_SINGLE_REGISTER, 40003, 1,\\n output_value = 10)\\n reply = client.execute(cst.READ_HOLDING_REGISTERS, 40003, 1)\\n #print \\\"BRDEBUG: Reply\\\", reply\\n assert reply[0] == 10\",\n \"def testExecute(self):\\n client = ICSClientFactory(self.config, 'slave', 'master') \\n\\n #Test reading and writing coils\\n reply = client.execute(cst.READ_COILS, 10, 2)\\n assert reply[0] == False \\n assert reply[1] == False\\n reply = client.execute(cst.WRITE_SINGLE_COIL, 10, 1, output_value=1)\\n reply = client.execute(cst.READ_COILS, 10, 2)\\n assert reply[0] == True\\n assert reply[1] == False\\n reply = client.execute(cst.WRITE_MULTIPLE_COILS, 10, 2,\\n output_value=[0,1])\\n reply = client.execute(cst.READ_COILS, 10, 2)\\n assert reply[1] == True\\n assert reply[0] == False\\n \\n #Test reading and writing input regs\\n #reply = client.execute(cst.READ_INPUT_REGISTERS, 30002, 1)\\n #print \\\"BRDEBUG: Reply: \\\", reply\\n #assert reply[0] == 17\\n\\n #Test reading and setting holding regs\\n reply = client.execute(cst.READ_HOLDING_REGISTERS, 40003, 1)\\n assert reply[0] == 15.0\\n reply = client.execute(cst.WRITE_SINGLE_REGISTER, 40003, 1,\\n output_value = 10)\\n reply = client.execute(cst.READ_HOLDING_REGISTERS, 40003, 1)\\n assert reply[0] == 10.0\",\n \"def _make_mock_container_get(bad_config_names: list[str], folder: str = \\\"media\\\"):\\n mount = {\\n \\\"Type\\\": \\\"bind\\\",\\n \\\"Source\\\": f\\\"/mnt/data/supervisor/{folder}\\\",\\n \\\"Destination\\\": f\\\"/{folder}\\\",\\n \\\"Mode\\\": \\\"rw\\\",\\n \\\"RW\\\": True,\\n \\\"Propagation\\\": \\\"rprivate\\\",\\n }\\n\\n def mock_container_get(name):\\n out = MagicMock()\\n out.status = \\\"running\\\"\\n out.attrs = {\\\"State\\\": {}, \\\"Mounts\\\": []}\\n if name in bad_config_names:\\n out.attrs[\\\"Mounts\\\"].append(mount)\\n\\n return out\\n\\n return mock_container_get\",\n \"def meta_res(simulatedata_cbma, meta, random):\\n _, (_, dataset) = simulatedata_cbma\\n # CHECK IF META/KERNEL WORK TOGETHER\\n ####################################\\n meta_expectation = does_not_raise()\\n\\n with meta_expectation:\\n res = meta.fit(dataset)\\n # if creating the result failed (expected), do not continue\\n if isinstance(meta_expectation, type(pytest.raises(ValueError))):\\n pytest.xfail(\\\"this meta-analysis & kernel combo fails\\\")\\n # instantiate meta-analysis estimator\\n return res\",\n \"def none_molecule() -> UniqueMolecule:\\n return UniqueMolecule(rd_mol=Chem.MolFromSmiles(\\\"\\\"))\",\n \"def test_run_read(self):\\n\\n self.ictrl[0] = 1 + 2 + 4 + 8\\n vmec_f90wrap.runvmec(self.ictrl, self.filename, self.verbose, \\\\\\n self.fcomm, reset_file)\\n\\n self.assertTrue(self.ictrl[1] in success_codes)\\n\\n self.assertEqual(vmec_f90wrap.vmec_input.nfp, 3)\\n self.assertEqual(vmec_f90wrap.vmec_input.mpol, 4)\\n self.assertEqual(vmec_f90wrap.vmec_input.ntor, 3)\\n print('rbc.shape:', vmec_f90wrap.vmec_input.rbc.shape)\\n print('rbc:',vmec_f90wrap.vmec_input.rbc[101:103, 0:4])\\n\\n # n = 0, m = 0:\\n self.assertAlmostEqual(vmec_f90wrap.vmec_input.rbc[101,0], 1.3782)\\n\\n # n = 0, m = 1:\\n self.assertAlmostEqual(vmec_f90wrap.vmec_input.zbs[101,1], 4.6465E-01)\\n\\n # n = 1, m = 1:\\n self.assertAlmostEqual(vmec_f90wrap.vmec_input.zbs[102,1], 1.6516E-01)\\n\\n # Now try reading in the output\\n wout_file = os.path.join(os.path.dirname(__file__), 'wout_li383_low_res.nc')\\n ierr = 0\\n vmec_f90wrap.read_wout_mod.read_wout_file(wout_file, ierr)\\n self.assertEqual(ierr, 0)\\n self.assertAlmostEqual(vmec_f90wrap.read_wout_mod.betatot, \\\\\\n 0.0426215030653306, places=4)\\n\\n print('iotaf.shape:',vmec_f90wrap.read_wout_mod.iotaf.shape)\\n print('rmnc.shape:',vmec_f90wrap.read_wout_mod.rmnc.shape)\\n\\n self.assertAlmostEqual(vmec_f90wrap.read_wout_mod.iotaf[-1], \\\\\\n 0.654868168783638, places=4)\\n\\n self.assertAlmostEqual(vmec_f90wrap.read_wout_mod.rmnc[0, 0], \\\\\\n 1.4773028173065, places=4)\",\n \"def build_molecule(nresidues):\\n molecule = vermouth.molecule.Molecule()\\n residue_template = vermouth.molecule.Molecule()\\n residue_template.add_nodes_from(\\n (idx, {\\\"chain\\\": \\\"\\\", \\\"atomname\\\": str(idx), \\\"resname\\\": \\\"DUMMY\\\", \\\"resid\\\": 1})\\n for idx in range(3)\\n )\\n for _ in range(nresidues):\\n molecule.merge_molecule(residue_template)\\n return molecule\",\n \"def test_get_individual_entries_of_matrices_simulation_example():\\n task = get_individual_entries_of_matrices(\\n lambda_2=2,\\n lambda_1_1=0.1,\\n lambda_1_2=0.5,\\n mu_1=2,\\n mu_2=1,\\n num_of_servers_1=2,\\n num_of_servers_2=2,\\n threshold_1=3,\\n threshold_2=5,\\n system_capacity_1=4,\\n system_capacity_2=6,\\n buffer_capacity_1=2,\\n buffer_capacity_2=2,\\n target=2,\\n alpha=0.5,\\n use_simulation=True,\\n runtime=300,\\n num_of_trials=3,\\n warm_up_time=5,\\n seed_num_1=0,\\n seed_num_2=0,\\n )\\n\\n assert da.is_dask_collection(task)\\n values = da.compute(task)\\n assert np.allclose(\\n values,\\n (\\n (\\n 3,\\n 5,\\n 0.7613063676529543,\\n 1 - 0.0006520260736895711,\\n 1 - 0.027937014444158834,\\n ),\\n ),\\n )\",\n \"def call(self, x, mask=None):\\n # Add trainable weights\\n self.build()\\n outputs = x[0]\\n atom_split = x[1]\\n\\n if self.gaussian_expand:\\n outputs = self.gaussian_histogram(outputs)\\n\\n output_molecules = tf.segment_sum(outputs, atom_split)\\n\\n if self.gaussian_expand:\\n output_molecules = tf.matmul(output_molecules, self.W) + self.b\\n output_molecules = self.activation(output_molecules)\\n return output_molecules\",\n \"def test_corr_transform_smoke(meta_cres_small):\\n assert isinstance(meta_cres_small, MetaResult)\",\n \"def torchani(ret_data):\\n\\n import numpy as np\\n import torch\\n import torchani\\n\\n device = torch.device('cpu')\\n builtin = torchani.neurochem.Builtins()\\n\\n # Failure flag\\n ret_data[\\\"success\\\"] = False\\n\\n # Build model\\n model = get_model(ret_data[\\\"model\\\"][\\\"method\\\"])\\n if model is False:\\n ret_data[\\\"error_message\\\"] = \\\"run_torchani only accepts the ANI1 method.\\\"\\n return ret_data\\n\\n # Build species\\n species = \\\"\\\".join(ret_data[\\\"molecule\\\"][\\\"symbols\\\"])\\n unknown_sym = set(species) - {\\\"H\\\", \\\"C\\\", \\\"N\\\", \\\"O\\\"}\\n if unknown_sym:\\n ret_data[\\\"error_message\\\"] = \\\"The '{}' model does not support symbols: {}.\\\".format(\\n ret_data[\\\"model\\\"][\\\"method\\\"], unknown_sym)\\n return ret_data\\n\\n species = builtin.consts.species_to_tensor(species).to(device).unsqueeze(0)\\n\\n # Build coord array\\n geom_array = np.array(ret_data[\\\"molecule\\\"][\\\"geometry\\\"]).reshape(1, -1, 3) * units.bohr_to_angstrom\\n coordinates = torch.tensor(geom_array.tolist(), requires_grad=True, device=device)\\n\\n _, energy = model((species, coordinates))\\n ret_data[\\\"properties\\\"] = {\\\"return_energy\\\": energy.item()}\\n\\n if ret_data[\\\"driver\\\"] == \\\"energy\\\":\\n ret_data[\\\"return_result\\\"] = ret_data[\\\"properties\\\"][\\\"return_energy\\\"]\\n elif ret_data[\\\"driver\\\"] == \\\"gradient\\\":\\n derivative = torch.autograd.grad(energy.sum(), coordinates)[0].squeeze()\\n ret_data[\\\"return_result\\\"] = np.asarray(derivative / units.bohr_to_angstrom).ravel().tolist()\\n else:\\n ret_data[\\\"error_message\\\"] = \\\"run_torchani did not understand driver method '{}'.\\\".format(ret_data[\\\"driver\\\"])\\n return ret_data\\n\\n ret_data[\\\"provenance\\\"] = {\\\"creator\\\": \\\"torchani\\\", \\\"version\\\": \\\"unknown\\\", \\\"routine\\\": \\\"torchani.builtin.aev_computer\\\"}\\n\\n ret_data[\\\"schema_name\\\"] = \\\"qc_schema_output\\\"\\n ret_data[\\\"success\\\"] = True\\n\\n return ret_data\",\n \"async def test_fetch_filtered_dataset_call(self):\\n pool = asynctest.CoroutineMock()\\n db_response = {\\\"referenceBases\\\": '', \\\"alternateBases\\\": '', \\\"variantType\\\": \\\"\\\",\\n \\\"referenceName\\\": 'Chr38',\\n \\\"frequency\\\": 0, \\\"callCount\\\": 0, \\\"sampleCount\\\": 0, \\\"variantCount\\\": 0,\\n \\\"start\\\": 0, \\\"end\\\": 0, \\\"accessType\\\": \\\"PUBLIC\\\", \\\"datasetId\\\": \\\"test\\\"}\\n pool.acquire().__aenter__.return_value = Connection(accessData=[db_response])\\n assembly_id = 'GRCh38'\\n position = (10, 20, None, None, None, None)\\n chromosome = 1\\n reference = 'A'\\n alternate = ('DUP', None)\\n result = await fetch_filtered_dataset(pool, assembly_id, position, chromosome, reference, alternate, None, None, False)\\n # for now it can return empty dataset\\n # in order to get a response we will have to mock it\\n # in Connection() class\\n expected = {'referenceName': 'Chr38', 'callCount': 0, 'sampleCount': 0, 'variantCount': 0, 'datasetId': 'test',\\n 'referenceBases': '', 'alternateBases': '', 'variantType': '', 'start': 0, 'end': 0, 'frequency': 0,\\n 'info': {'accessType': 'PUBLIC'},\\n 'datasetHandover': [{'handoverType': {'id': 'CUSTOM', 'label': 'Variants'},\\n 'description': 'browse the variants matched by the query',\\n 'url': 'https://examplebrowser.org/dataset/test/browser/variant/Chr38-1--'},\\n {'handoverType': {'id': 'CUSTOM', 'label': 'Region'},\\n 'description': 'browse data of the region matched by the query',\\n 'url': 'https://examplebrowser.org/dataset/test/browser/region/Chr38-1-1'},\\n {'handoverType': {'id': 'CUSTOM', 'label': 'Data'},\\n 'description': 'retrieve information of the datasets',\\n 'url': 'https://examplebrowser.org/dataset/test/browser'}]}\\n\\n self.assertEqual(result, [expected])\",\n \"def test_multi_molecules_cycle_one(self, multi_mol_system_irregular):\\n sequence = \\\"A\\\"\\n expected = [sequence] * (15 * 3)\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(multi_mol_system_irregular)\\n found = self.sequence_from_system(multi_mol_system_irregular, \\\"test\\\")\\n assert found == expected\",\n \"def test_diatomic_dummy_molecule_rotation_around_molecule_axis():\\n mol = Molecule()\\n mol.atoms = ['C'] * 2\\n mol.coordinates = np.array([[1, 0, 0], [0, 1, 0]])\\n mol.rotate(([0, 0, 0], [0, 0, 1]), np.pi / 2, center=True)\\n assert np.allclose(mol.coordinates, [[1, 1, 0], [0, 0, 0]])\\n mol.rotate(([0, 0, 0], [0, 0, 1]), np.pi, center=True)\\n assert np.allclose(mol.coordinates, [[0, 0, 0], [1, 1, 0]])\",\n \"def get_smarts(prefix, atom_idxs):\\n\\n offmol = Molecule.from_file(prefix + '.mol2')\\n fix_carboxylate_bond_orders(offmol)\\n remove_charge_and_bond_order_from_guanidinium(offmol)\\n remove_charge_and_bond_order_from_imidazole(offmol)\\n if prefix in prefix2pmd_struct:\\n pmd_struct = prefix2pmd_struct[prefix]\\n else: \\n pmd_struct = ParmEd.load_file(prefix + '.prmtop')\\n prefix2pmd_struct[prefix] = pmd_struct\\n oemol = offmol.to_openeye()\\n residues_of_interest = set()\\n atom_indices_of_interest = set()\\n for atom_idx in atom_idxs:\\n residues_of_interest.add(pmd_struct.atoms[atom_idx].residue.idx)\\n for oeatom, pmd_atom in zip(oemol.GetAtoms(), pmd_struct.atoms):\\n\\n # Delete all non-residue-of-interest atoms\\n if (pmd_atom.residue.idx in residues_of_interest):\\n atom_indices_of_interest.add(pmd_atom.idx)\\n\\n # Assign tags to atoms of interest\\n if (oeatom.GetIdx() in atom_idxs):\\n map_index = atom_idxs.index(oeatom.GetIdx()) + 1\\n oeatom.SetMapIdx(map_index)\\n\\n # Make a \\\"Subset\\\" molecule, so that we don't get weird charges\\n # around where we cleave the residues\\n subsetmol = OEChem.OEGraphMol()\\n oepred = OEChem.PyAtomPredicate(lambda x:x.GetIdx() in atom_indices_of_interest)\\n OEChem.OESubsetMol(subsetmol, oemol, oepred)\\n #OEAssignAromaticFlags(subsetmol, \\n smiles_options = (OEChem.OESMILESFlag_Canonical | OEChem.OESMILESFlag_Isotopes |\\n OEChem.OESMILESFlag_RGroups)\\n # Add the atom and bond stereo flags\\n smiles_options |= OEChem.OESMILESFlag_AtomStereo | OEChem.OESMILESFlag_BondStereo\\n\\n # Add the hydrogen flag\\n smiles_options |= OEChem.OESMILESFlag_Hydrogens\\n smiles_options |= OEChem.OESMILESFlag_AtomMaps\\n smiles = OEChem.OECreateSmiString(subsetmol, smiles_options)\\n\\n # Replace \\\"$\\\" characters (bond order 4) with \\\"~\\\" (wildcard bond)\\n smiles = smiles.replace('$', '~')\\n return smiles\",\n \"def _load_molecule(self):\\n self.pymol = pybel.readstring(self.input_format, self.file_dic['input'])\",\n \"def test_rdkit_conf_from_mol(self):\\n b_mol = converter.molecules_from_xyz(self.xyz5['dict'])[1]\\n conf, rd_mol = converter.rdkit_conf_from_mol(mol=b_mol, xyz=self.xyz5['dict'])\\n self.assertTrue(conf.Is3D())\\n self.assertEqual(rd_mol.GetNumAtoms(), 5)\",\n \"def test_return_spin_pipe_fail(self):\\n\\n # Try to get a spin from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')\",\n \"def test_modul1(self):\\n\\n self.delayDisplay(\\\"Starting the test\\\")\\n #\\n # first, get some data\\n #\\n import urllib\\n downloads = (\\n ('http://slicer.kitware.com/midas3/download?items=5767', 'FA.nrrd', slicer.util.loadVolume),\\n )\\n\\n for url,name,loader in downloads:\\n filePath = slicer.app.temporaryPath + '/' + name\\n if not os.path.exists(filePath) or os.stat(filePath).st_size == 0:\\n logging.info('Requesting download %s from %s...\\\\n' % (name, url))\\n urllib.urlretrieve(url, filePath)\\n if loader:\\n logging.info('Loading %s...' % (name,))\\n loader(filePath)\\n self.delayDisplay('Finished with download and loading')\\n\\n volumeNode = slicer.util.getNode(pattern=\\\"FA\\\")\\n logic = modulLogic()\\n self.assertTrue( logic.hasImageData(volumeNode) )\\n self.delayDisplay('Test passed!')\",\n \"def get_slab(self):\\n return self.c.get_atoms(simulation_cell=True)\",\n \"def get_redo_workflow(self, qchem_input_params, sp_params, max_iterations=3):\\n\\n if self.db is None:\\n raise RuntimeError(\\\"Cannot access database to determine what\\\"\\n \\\"molecules need to be re-calculated.\\\")\\n\\n fws = []\\n\\n collection = self.db.db[\\\"molecules\\\"]\\n\\n for mol in collection.find({}):\\n frequencies = mol[\\\"output\\\"][\\\"frequencies\\\"]\\n\\n if any([True if x < 0 else False for x in frequencies]):\\n min_molecule_perturb_scale = 0.1\\n max_molecule_perturb_scale = 0.3\\n scale_grid = 10\\n perturb_scale_grid = (max_molecule_perturb_scale -\\n min_molecule_perturb_scale) / scale_grid\\n msc = MoleculeStructureComparator()\\n\\n old_molecule = None\\n\\n for calc in mol[\\\"calcs_reversed\\\"]:\\n if calc[\\\"task\\\"][\\\"type\\\"] in [\\\"freq\\\", \\\"frequency\\\"] and old_molecule is None:\\n negative_freq_vecs = calc.get(\\\"frequency_mode_vectors\\\")[0]\\n old_coords = calc.get(\\\"initial_geometry\\\")\\n old_molecule = Molecule.from_dict(calc.get(\\\"initial_molecule\\\"))\\n\\n structure_successfully_perturbed = False\\n\\n for molecule_perturb_scale in np.arange(\\n max_molecule_perturb_scale, min_molecule_perturb_scale,\\n -perturb_scale_grid):\\n new_coords = perturb_coordinates(\\n old_coords=old_coords,\\n negative_freq_vecs=negative_freq_vecs,\\n molecule_perturb_scale=molecule_perturb_scale,\\n reversed_direction=False)\\n new_molecule = Molecule(\\n species=old_molecule.species,\\n coords=new_coords,\\n charge=old_molecule.charge,\\n spin_multiplicity=old_molecule.spin_multiplicity)\\n if msc.are_equal(old_molecule, new_molecule):\\n structure_successfully_perturbed = True\\n break\\n if not structure_successfully_perturbed:\\n raise Exception(\\n \\\"Unable to perturb coordinates to remove negative frequency without changing the bonding structure\\\"\\n )\\n\\n mol_id = mol[\\\"mol_id\\\"]\\n dir_name = mol[\\\"dir_name\\\"].split(\\\"/\\\")[-1]\\n\\n if dir_name not in listdir(self.base_dir):\\n os.mkdir(join(self.base_dir, dir_name))\\n\\n fws.append(OptFreqSPFW(molecule=new_molecule,\\n name=\\\"Flattening: {}/{}\\\".format(mol_id,\\n dir_name),\\n qchem_cmd=\\\"qchem -slurm\\\",\\n input_file=join(self.base_dir,\\n dir_name,\\n mol_id + \\\".in\\\"),\\n output_file=join(self.base_dir,\\n dir_name,\\n mol_id + \\\".out\\\"),\\n qclog_file=join(self.base_dir,\\n dir_name,\\n mol_id + \\\".qclog\\\"),\\n max_cores=32,\\n max_iterations=max_iterations,\\n qchem_input_params=qchem_input_params,\\n sp_params=sp_params,\\n db_file=self.db_file))\\n\\n if len(fws) == 0:\\n return None\\n else:\\n return Workflow(fws)\",\n \"def get_container_output(container_name: Optional[pulumi.Input[str]] = None,\\n device_name: Optional[pulumi.Input[str]] = None,\\n resource_group_name: Optional[pulumi.Input[str]] = None,\\n storage_account_name: Optional[pulumi.Input[str]] = None,\\n opts: Optional[pulumi.InvokeOptions] = None) -> pulumi.Output[GetContainerResult]:\\n ...\",\n \"def process(self, name_and_sequence):\\n name, sequence = name_and_sequence\\n yield preprocess_utils.get_pacbio_molecule_name(name), sequence\",\n \"def test_random_circuit(self, device, tol, ret):\\n n_wires = 2\\n dev = device(n_wires)\\n dev_def = qml.device(\\\"default.qubit\\\", wires=n_wires)\\n\\n if dev.name == dev_def.name:\\n pytest.skip(\\\"Device is default.qubit.\\\")\\n\\n supports_tensor = (\\n \\\"supports_tensor_observables\\\" in dev.capabilities()\\n and dev.capabilities()[\\\"supports_tensor_observables\\\"]\\n )\\n\\n if not supports_tensor:\\n pytest.skip(\\\"Device does not support tensor observables.\\\")\\n\\n if dev.shots is not None:\\n pytest.skip(\\\"Device is in non-analytical mode.\\\")\\n\\n n_layers = np.random.randint(1, 5)\\n weights = 2 * np.pi * np.random.rand(n_layers, 1)\\n\\n ret_type = getattr(qml, ret)\\n\\n def circuit(weights):\\n RandomLayers(weights, wires=range(n_wires))\\n return ret_type(qml.PauliZ(wires=0) @ qml.PauliX(wires=1))\\n\\n qnode_def = qml.QNode(circuit, dev_def)\\n qnode = qml.QNode(circuit, dev)\\n\\n grad_def = qml.grad(qnode_def, argnum=0)\\n grad = qml.grad(qnode, argnum=0)\\n\\n assert np.allclose(qnode(weights), qnode_def(weights), atol=tol(dev.shots))\\n assert np.allclose(grad(weights), grad_def(weights), atol=tol(dev.shots))\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def get_data(self, molecule, base_dir, bo_list, dt, istep, calc_force_only):\\n self.copy_files(molecule, istep, calc_force_only)\\n super().get_data(base_dir, calc_force_only)\\n self.get_input(molecule, istep, bo_list, calc_force_only)\\n self.run_QM(base_dir, istep, bo_list)\\n self.extract_QM(molecule, istep, bo_list, dt, calc_force_only)\\n self.move_dir(base_dir)\",\n \"def test_volume():\\n structure = Material(input)\\n assert (structure.volume == 90.725624999999965)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.63652605","0.636043","0.6196237","0.61398995","0.6118704","0.59954035","0.5866117","0.5800223","0.57261777","0.56701607","0.56608844","0.55993","0.5499727","0.5499299","0.5475103","0.5424967","0.53821063","0.53715503","0.5311273","0.5283148","0.5275008","0.5256937","0.52392954","0.5228423","0.52204895","0.52194744","0.51822066","0.51679915","0.5141056","0.51047856","0.50894165","0.50868213","0.508006","0.50757563","0.50724983","0.5065108","0.50582093","0.50377053","0.5014988","0.50078267","0.50035775","0.49918157","0.49914932","0.4984711","0.49762553","0.49673563","0.49627694","0.49332595","0.49130496","0.49096373","0.49058083","0.49054244","0.49007434","0.49003598","0.48928422","0.48920855","0.48827192","0.4879412","0.48775417","0.48575807","0.4854187","0.48507467","0.4847778","0.48470235","0.48432115","0.4841274","0.4840882","0.48387","0.48385274","0.48349282","0.4830045","0.4830045","0.48269874","0.48203158","0.4817259","0.48058578","0.48057672","0.4800143","0.4784534","0.47785807","0.47766447","0.477352","0.477075","0.47698623","0.47698417","0.47690552","0.47687918","0.47610778","0.47594228","0.47588947","0.47572702","0.47536793","0.47534895","0.47511324","0.47496006","0.47452953","0.4743141","0.47368404","0.47362527","0.47307402"],"string":"[\n \"0.63652605\",\n \"0.636043\",\n \"0.6196237\",\n \"0.61398995\",\n \"0.6118704\",\n \"0.59954035\",\n \"0.5866117\",\n \"0.5800223\",\n \"0.57261777\",\n \"0.56701607\",\n \"0.56608844\",\n \"0.55993\",\n \"0.5499727\",\n \"0.5499299\",\n \"0.5475103\",\n \"0.5424967\",\n \"0.53821063\",\n \"0.53715503\",\n \"0.5311273\",\n \"0.5283148\",\n \"0.5275008\",\n \"0.5256937\",\n \"0.52392954\",\n \"0.5228423\",\n \"0.52204895\",\n \"0.52194744\",\n \"0.51822066\",\n \"0.51679915\",\n \"0.5141056\",\n \"0.51047856\",\n \"0.50894165\",\n \"0.50868213\",\n \"0.508006\",\n \"0.50757563\",\n \"0.50724983\",\n \"0.5065108\",\n \"0.50582093\",\n \"0.50377053\",\n \"0.5014988\",\n \"0.50078267\",\n \"0.50035775\",\n \"0.49918157\",\n \"0.49914932\",\n \"0.4984711\",\n \"0.49762553\",\n \"0.49673563\",\n \"0.49627694\",\n \"0.49332595\",\n \"0.49130496\",\n \"0.49096373\",\n \"0.49058083\",\n \"0.49054244\",\n \"0.49007434\",\n \"0.49003598\",\n \"0.48928422\",\n \"0.48920855\",\n \"0.48827192\",\n \"0.4879412\",\n \"0.48775417\",\n \"0.48575807\",\n \"0.4854187\",\n \"0.48507467\",\n \"0.4847778\",\n \"0.48470235\",\n \"0.48432115\",\n \"0.4841274\",\n \"0.4840882\",\n \"0.48387\",\n \"0.48385274\",\n \"0.48349282\",\n \"0.4830045\",\n \"0.4830045\",\n \"0.48269874\",\n \"0.48203158\",\n \"0.4817259\",\n \"0.48058578\",\n \"0.48057672\",\n \"0.4800143\",\n \"0.4784534\",\n \"0.47785807\",\n \"0.47766447\",\n \"0.477352\",\n \"0.477075\",\n \"0.47698623\",\n \"0.47698417\",\n \"0.47690552\",\n \"0.47687918\",\n \"0.47610778\",\n \"0.47594228\",\n \"0.47588947\",\n \"0.47572702\",\n \"0.47536793\",\n \"0.47534895\",\n \"0.47511324\",\n \"0.47496006\",\n \"0.47452953\",\n \"0.4743141\",\n \"0.47368404\",\n \"0.47362527\",\n \"0.47307402\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.82855994"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81498,"cells":{"query":{"kind":"string","value":"Test the failure of the function for returning the desired molecule data container. The function tested is pipe_control.mol_res_spin.return_molecule()."},"document":{"kind":"string","value":"def test_return_molecule_pipe_fail(self):\n\n # Try to get a molecule from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_return_molecule(self):\n\n # Ask for a few molecules.\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\n\n # Test the data of molecule 1.\n self.assertEqual(mol1.name, 'Ap4Aase')\n\n # Test the data of molecule 2.\n self.assertEqual(mol2.name, 'RNA')","def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_return_single_residue_info_fail(self):\n\n # Ask for a few residues.\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')","def test_return_residue_pipe_fail(self):\n\n # Try to get a residue from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_return_residue(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_residue(':1')\n res2 = mol_res_spin.return_residue(selection=':2')\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\n\n # Test the data of residue 1.\n self.assertEqual(res1.num, 1)\n self.assertEqual(res1.name, None)\n\n # Test the data of residue 2.\n self.assertEqual(res2.num, 2)\n self.assertEqual(res2.name, 'Glu')\n\n # Test the data of residue 4.\n self.assertEqual(res4.num, 4)\n self.assertEqual(res4.name, 'Pro')\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5.num, -5)\n self.assertEqual(res5.name, None)\n self.assertEqual(res5.spin[1].name, 'N5')","def test_return_spin_pipe_fail(self):\n\n # Try to get a spin from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')","def test_molecule_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for molecule in mol_res_spin.molecule_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_molecule_loop_no_selection(self):\n\n # Molecule data.\n name = ['Ap4Aase', 'RNA']\n\n # Loop over the molecules.\n i = 0\n for mol in mol_res_spin.molecule_loop():\n # Test the molecule names.\n self.assertEqual(mol.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def test_validation_wrong_molecules():\n paths = examples_paths()\n paths['wrongformat'] = utils.get_data_filename(os.path.join('tests', 'data', 'README.md'))\n molecules = [\n {'antechamber': {'charge_method': 'bcc'}},\n {'filepath': paths['wrongformat']},\n {'name': 'p-xylene', 'antechamber': {'charge_method': 'bcc'}, 'unknown': 4},\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'}},\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'invalid'},\n 'antechamber': {'charge_method': None}},\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'},\n 'antechamber': {'charge_method': 'bcc'}},\n {'filepath': 'nonexistentfile.pdb', 'leap': {'parameters': 'leaprc.ff14SB'}},\n {'filepath': paths['toluene'], 'smiles': 'Cc1ccccc1'},\n {'filepath': paths['toluene'], 'strip_protons': True},\n {'filepath': paths['abl'], 'leap': {'parameters': 'oldff/leaprc.ff14SB'}, 'epik': {'select': 0}},\n {'name': 'toluene', 'epik': 0},\n {'name': 'toluene', 'epik': {'tautomerize': 6}},\n {'name': 'toluene', 'epik': {'extract_range': 1}},\n {'name': 'toluene', 'smiles': 'Cc1ccccc1'},\n {'name': 3},\n {'smiles': 'Cc1ccccc1', 'select': 1},\n {'name': 'Cc1ccccc1', 'select': 1},\n {'filepath': paths['abl'], 'leap': {'parameters': 'oldff/leaprc.ff14SB'}, 'select': 'notanoption'},\n {'filepath': paths['abl'], 'regions': 5},\n {'filepath': paths['abl'], 'regions': {'a_region': [-56, 5.23]}},\n {'filepath': paths['toluene'], 'leap': {'parameters': 'leaprc.gaff'}, 'strip_protons': True},\n ]\n for molecule in molecules:\n yield assert_raises, YamlParseError, ExperimentBuilder._validate_molecules, {'mol': molecule}","def test_set_molecule_error(self):\n mol = Molecule.from_smiles(\"CCO\")\n atom = Atom(6, 0, False)\n atom.molecule = mol\n with pytest.raises(AssertionError, match=\"already has an associated molecule\"):\n atom.molecule = mol","def test_molecule_loop(self):\n\n # Loop over the molecules.\n for mol in mol_res_spin.molecule_loop('#RNA'):\n # Test the molecule name.\n self.assertEqual(mol.name, 'RNA')\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def test_get_thermo_data(self):\n output_directory = os.path.join(self.mop4.settings.fileStore, '..', '..')\n self.mop4.set_default_output_directory(output_directory)\n self.gauss3.set_default_output_directory(output_directory)\n self.molpro1.set_default_output_directory(output_directory)\n\n mol = Molecule().from_smiles('C1=CC=C2C=CC=CC2=C1')\n\n with self.assertRaises(Exception):\n self.mop4.get_thermo_data(mol)\n self.gauss3.get_thermo_data(mol)\n self.molpro1.get_thermo_data(mol)","def test_read_fail1(self):\n mod_fn = os.path.join(tests.TEST_DATA_PATH, 'segmentations', 'test_bad_data1.mod')\n with self.assertRaises(ValueError):\n modreader.get_data(mod_fn) # missing 'IMOD' start","def test_run_molecule(self, single_mol_system):\n sequence = \"ABCDE\"\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def test_return_single_residue_info(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_single_residue_info('1')\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\n res5 = mol_res_spin.return_single_residue_info('-5')\n\n # Test the data of residue 1.\n self.assertEqual(res1, (1, None))\n\n # Test the data of residue 2.\n self.assertEqual(res2, (2, 'Glu'))\n\n # Test the data of residue 4.\n self.assertEqual(res4, (4, 'Pro'))\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5, (-5, None))","def test_read_mol_input():\n # good input\n read_mol_input(os.path.join(TEST_DIR, \"example_mol_input_file.txt\"))\n # good input with extra spaces\n read_mol_input(os.path.join(TEST_DIR, \"example2_mol_input_file.txt\"))\n # no such file error\n assert_raises(FileNotFoundError, read_mol_input, 'no-such-file')\n # qcm appears twice\n assert_raises(ValueError, read_mol_input, os.path.join(TEST_DIR, \"bad1_mol_input_file.txt\"))\n # missing struct type\n assert_raises(ValueError, read_mol_input, os.path.join(TEST_DIR, \"bad2_mol_input_file.txt\"))","def test_get_data_fail(self):\n self.assertIsNone(get_data('this_must_fail', 5, 0))","def test_shared_wires(self):\n wires = range(2)\n estimation_wires = range(1, 3)\n\n with pytest.raises(ValueError, match=\"No wires can be shared between the wires\"):\n quantum_monte_carlo(\n lambda: None, wires=wires, target_wire=0, estimation_wires=estimation_wires\n )","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_input_sanity():\n energy = MagicMock()\n\n with raises(NotImplementedError) as exception:\n MonteCarlo(sum, [1, 1, 1], 0e0)\n with raises(ValueError) as exception:\n MonteCarlo(energy, [1, 1, 1], temperature=-1e0)\n\n with raises(TypeError) as exception:\n MonteCarlo(energy, [1.0, 2, 3])\n with raises(ValueError) as exception:\n MonteCarlo(energy, [-1, 2, 3])\n with raises(ValueError) as exception:\n MonteCarlo(energy, [[1, 2, 3], [3, 4, 5]])\n with raises(ValueError) as exception:\n MonteCarlo(energy, [3])\n with raises(ValueError) as exception:\n MonteCarlo(energy, [0, 0])","def test_residue_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for residue in mol_res_spin.residue_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_validation_correct_molecules():\n paths = examples_paths()\n molecules = [\n {'name': 'toluene', 'leap': {'parameters': 'leaprc.gaff'}},\n {'name': 'toluene', 'leap': {'parameters': ['leaprc.gaff', 'toluene.frcmod']}},\n {'name': 'p-xylene', 'antechamber': {'charge_method': 'bcc'}},\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'},\n 'antechamber': {'charge_method': None}},\n {'name': 'p-xylene', 'antechamber': {'charge_method': 'bcc'},\n 'epik': {'ph': 7.6, 'ph_tolerance': 0.7, 'tautomerize': False, 'select': 0}},\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'},\n 'antechamber': {'charge_method': None}, 'epik': {'select': 1}},\n\n {'filepath': paths['abl']},\n {'filepath': paths['abl'], 'leap': {'parameters': 'leaprc.ff99SBildn'}},\n {'filepath': paths['abl'], 'leap': {'parameters': 'leaprc.ff99SBildn'}, 'select': 1},\n {'filepath': paths['abl'], 'select': 'all'},\n {'filepath': paths['abl'], 'select': 'all', 'strip_protons': True},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {}},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'add_missing_residues': True}},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'add_missing_atoms': 'all', 'ph': '8.0'}},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'remove_heterogens': 'all'}},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'replace_nonstandard_residues': True}},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'apply_mutations': {'chain_id': 'A', 'mutations': 'T85I'}}},\n {'filepath': paths['abl'], 'select': 'all', 'modeller': {'apply_mutations': {'chain_id': 'A', 'mutations': 'T85I'}}},\n {'filepath': paths['abl'], 'select': 'all', 'modeller': {'apply_mutations': {'chain_id': 'A', 'mutations': 'WT'}}},\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'apply_mutations': {'chain_id': 'A', 'mutations': 'I8A/T9A'}}},\n {'filepath': paths['toluene'], 'leap': {'parameters': 'leaprc.gaff'}},\n {'filepath': paths['benzene'], 'epik': {'select': 1, 'tautomerize': False}},\n # Regions tests, make sure all other combos still work\n {'name': 'toluene', 'regions': {'a_region': 4}},\n {'name': 'toluene', 'regions': {'a_region': 'dsl string'}},\n {'name': 'toluene', 'regions': {'a_region': [0, 2, 3]}},\n {'name': 'toluene', 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}},\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': 4}},\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': 'dsl string'}},\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': [0, 2, 3]}},\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}},\n {'filepath': paths['abl'], 'regions': {'a_region': 4}},\n {'filepath': paths['abl'], 'regions': {'a_region': 'dsl string'}},\n {'filepath': paths['abl'], 'regions': {'a_region': [0, 2, 3]}},\n {'filepath': paths['abl'], 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}},\n {'filepath': paths['toluene'], 'regions': {'a_region': 4}},\n {'filepath': paths['toluene'], 'regions': {'a_region': 'dsl string'}},\n {'filepath': paths['toluene'], 'regions': {'a_region': [0, 2, 3]}},\n {'filepath': paths['toluene'], 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}}\n ]\n for molecule in molecules:\n yield ExperimentBuilder._validate_molecules, {'mol': molecule}","def test_to_from_rdkit(self, molecule):\n # import pickle\n from openforcefield.utils.toolkits import UndefinedStereochemistryError\n\n undefined_stereo = molecule.name in rdkit_drugbank_undefined_stereo_mols\n\n toolkit_wrapper = RDKitToolkitWrapper()\n\n rdmol = molecule.to_rdkit()\n molecule_smiles = molecule.to_smiles(toolkit_registry=toolkit_wrapper)\n\n # First test making a molecule using the Molecule(oemol) method\n\n # If this is a known failure, check that it raises UndefinedStereochemistryError\n # and proceed with the test ignoring it.\n test_mol = None\n if undefined_stereo:\n with pytest.raises(UndefinedStereochemistryError):\n Molecule(rdmol)\n test_mol = Molecule(rdmol, allow_undefined_stereo=True)\n else:\n test_mol = Molecule(rdmol)\n\n test_mol_smiles = test_mol.to_smiles(toolkit_registry=toolkit_wrapper)\n assert molecule_smiles == test_mol_smiles\n\n # Check that the two topologies are isomorphic.\n assert_molecule_is_equal(\n molecule, test_mol, \"Molecule.to_rdkit()/Molecule(rdmol) round trip failed\"\n )\n\n # Second, test making a molecule using the Molecule.from_openeye(oemol) method\n\n # If this is a known failure, check that it raises UndefinedStereochemistryError\n # and proceed with the test.\n if undefined_stereo:\n with pytest.raises(UndefinedStereochemistryError):\n Molecule.from_rdkit(rdmol)\n test_mol = Molecule.from_rdkit(rdmol, allow_undefined_stereo=True)\n else:\n test_mol = Molecule.from_rdkit(rdmol)\n\n test_mol_smiles = test_mol.to_smiles(toolkit_registry=toolkit_wrapper)\n assert molecule_smiles == test_mol_smiles\n\n # Check that the two topologies are isomorphic.\n assert_molecule_is_equal(\n molecule, test_mol, \"Molecule.to_rdkit()/from_rdkit() round trip failed\"\n )","def test_run_molecule_not_selected(self, single_mol_system):\n sequence = \"ABCDE\"\n processor = dssp.AnnotateResidues(\n \"test\", sequence, molecule_selector=lambda mol: False\n )\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert vermouth.utils.are_all_equal(found)\n assert found[0] is None","def validate_molecules(molecules):\n # The input should be a Design Group, a Molecule, or a list of Molecules. If\n # it is a Design Group, get the group number. Make sure the final result is\n # iterable and each entry is a Molecule\n error = False\n gn = None\n # molecules can be one of three things: a DesignGroup\n if isinstance(molecules, MOLECULES.DesignGroup):\n gn = molecules.number\n # A Molecule\n elif isinstance(molecules, MOLECULES.Molecule):\n molecules = [molecules]\n # Or a list of Molecules\n elif isinstance(molecules, list) and len(molecules) > 0:\n for obj in molecules:\n if not isinstance(obj, MOLECULES.Molecule):\n error = True\n break\n else:\n error = True\n # If molecules is not one of those three things\n if error:\n text = \"The functions in the CHARMM module will work with either a \"\n text +=\"Design Group, Molecule, or list of Molecules as input, but not:\"\n text += \"\\n\" + str(molecules)\n raise CHARMM_Error(text)\n # Make sure that all Molecules use the CHARMM force field and the identified\n # file format, and that each Molecule has a unique name\n names = []\n for molecule in molecules:\n # Check that it uses CHARMM\n if molecule.forceField != \"CHARMM\":\n text = \"All Molecules used by a function in the CHARMM module must \"\n text += \"use the CHARMM force field.\"\n raise CHARMM_Error(text)\n # And they have a consistent file format\n elif molecule.fileFormat != molecules[0].fileFormat:\n text = \"All Molecules used by a function in the CHARMM module must \"\n text += \"use the same file format.\"\n raise CHARMM_Error(text)\n # And that it has a unique name\n elif molecule.name in names:\n text = \"All Molecules used by a function in the CHARMM module must \"\n text += \"have a unique name.\"\n raise CHARMM_Error(text)\n # Otherwise store the Molecule's name\n else:\n names.append(molecule.name)\n # Return the pointer to the molecules, the identified group number, and the\n # file format\n return molecules, gn","def test_to_from_rdkit(self, molecule):\n # import pickle\n from openff.toolkit.utils.toolkits import UndefinedStereochemistryError\n\n undefined_stereo = molecule.name in rdkit_drugbank_undefined_stereo_mols\n\n toolkit_wrapper = RDKitToolkitWrapper()\n\n rdmol = molecule.to_rdkit()\n molecule_smiles = molecule.to_smiles(toolkit_registry=toolkit_wrapper)\n\n # First test making a molecule using the Molecule(oemol) method\n\n # If this is a known failure, check that it raises UndefinedStereochemistryError\n # and proceed with the test ignoring it.\n test_mol = None\n if undefined_stereo:\n with pytest.raises(UndefinedStereochemistryError):\n Molecule(rdmol)\n test_mol = Molecule(rdmol, allow_undefined_stereo=True)\n else:\n test_mol = Molecule(rdmol)\n\n test_mol_smiles = test_mol.to_smiles(toolkit_registry=toolkit_wrapper)\n assert molecule_smiles == test_mol_smiles\n\n # Check that the two topologies are isomorphic.\n assert_molecule_is_equal(\n molecule, test_mol, \"Molecule.to_rdkit()/Molecule(rdmol) round trip failed\"\n )\n\n # Second, test making a molecule using the Molecule.from_openeye(oemol) method\n\n # If this is a known failure, check that it raises UndefinedStereochemistryError\n # and proceed with the test.\n if undefined_stereo:\n with pytest.raises(UndefinedStereochemistryError):\n Molecule.from_rdkit(rdmol)\n test_mol = Molecule.from_rdkit(rdmol, allow_undefined_stereo=True)\n else:\n test_mol = Molecule.from_rdkit(rdmol)\n\n test_mol_smiles = test_mol.to_smiles(toolkit_registry=toolkit_wrapper)\n assert molecule_smiles == test_mol_smiles\n\n # Check that the two topologies are isomorphic.\n assert_molecule_is_equal(\n molecule, test_mol, \"Molecule.to_rdkit()/from_rdkit() round trip failed\"\n )","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_single_molecule(self, single_mol_system, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def test_read_fail2(self):\n mod_fn = os.path.join(tests.TEST_DATA_PATH, 'segmentations', 'test_bad_data2.mod')\n with self.assertRaises(ValueError):\n modreader.get_data(mod_fn) # missing 'IEOF' end","def test_qcschema_round_trip_raise_error(self):\n\n # get a molecule qcschema\n import qcportal as ptl\n\n client = ptl.FractalClient()\n ds = client.get_collection(\n \"TorsionDriveDataset\", \"OpenFF-benchmark-ligand-fragments-v1.0\"\n )\n # grab an entry from the torsiondrive data set\n entry = ds.get_entry(\n \"[H]c1[c:1]([c:2](c(c(c1[H])N([H])C(=O)[H])[H])[C:3]2=C(C(=C([S:4]2)[H])OC([H])([H])[H])Br)[H]\"\n )\n del entry.attributes[\"canonical_isomeric_explicit_hydrogen_mapped_smiles\"]\n # now make the molecule from the record instance with the geometry\n with pytest.raises(KeyError):\n Molecule.from_qcschema(entry, client)","def test_get_placement_w_exception(self, mock__get_nslcmop,\n mock__get_nsd,\n mock__get_vim_accounts,\n mock_create_ns_placement_data,\n mock_do_placement_computation):\n server = self.serverSetup()\n\n server.msgBus.aiowrite = _async_mock()\n mock__get_nsd.return_value = nsd_from_db\n mock__get_nsd.side_effect = RuntimeError('kaboom!')\n mock__get_vim_accounts.return_value = list_of_vims\n mock_do_placement_computation.return_value = \\\n [{'vimAccountId': 'bbbbbbbb-38f5-438d-b8ee-3f93b3531f87', 'member-vnf-index': '1'},\n {'vimAccountId': 'aaaaaaaa-38f5-438d-b8ee-3f93b3531f87', 'member-vnf-index': '2'},\n {'vimAccountId': 'aaaaaaaa-38f5-438d-b8ee-3f93b3531f87', 'member-vnf-index': '3'}]\n\n _run(server.get_placement(nslcmop_record_w_pinning['id']))\n self.assertTrue(server.msgBus.aiowrite.mock.called)\n args, kwargs = server.msgBus.aiowrite.mock.call_args\n rsp_payload = args[2]\n expected_keys = {'placement'}\n self.assertEqual(expected_keys, set(rsp_payload.keys()), \"placement response missing keys\")\n self.assertIs(type(rsp_payload['placement']['vnf']), list, 'vnf not a list')\n self.assertEqual([], rsp_payload['placement']['vnf'], 'vnf list not empty')\n self.assertEqual(nslcmop_record_w_pinning['id'], rsp_payload['placement']['nslcmopId'], \"nslcmopId invalid\")","def test_exception_list_empty(self):\n complex_id_list = range(1,4) #1~3\n dataloader = lambda d: d\n calc_func = lambda d1,d2: d1 + d2\n \n _, actual = complex_pairwise_calc(complex_id_list, dataloader, calc_func, symmetry=False)\n expected = []\n\n self.assertEqual(actual, expected)","def test_check_cluster1():\n with pytest.raises(AssertionError) as err_info:\n Check_BuoyDC.check_cluster(cluster_fail_1)\n assert str(err_info.value) == 'cluster type input not within range of index'","def setUp(self):\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Name the first molecule.\n cdp.mol[0].name = 'Ap4Aase'\n\n # Add a second molecule to the system.\n cdp.mol.add_item(mol_name='RNA')\n\n # Add two more residues to the first molecule (and set the residue number of the first).\n cdp.mol[0].res[0].num = 1\n cdp.mol[0].res.add_item(res_num=2, res_name='Glu')\n cdp.mol[0].res.add_item(res_num=4, res_name='Pro')\n\n # Add some spin info to this molecule.\n cdp.mol[0].res[0].spin[0].name = 'NH'\n cdp.mol[0].res[0].spin[0].num = 60\n cdp.mol[0].res[1].spin[0].name = 'NH'\n cdp.mol[0].res[1].spin[0].num = 63\n\n # Add one more residue to the second molecule (and set the residue number of the first).\n cdp.mol[1].res[0].num = -5\n cdp.mol[1].res.add_item(res_num=-4)\n\n # Add a second set of spins to the second molecule (naming the first set first).\n cdp.mol[1].res[0].spin[0].name = 'C8'\n cdp.mol[1].res[1].spin[0].name = 'C8'\n cdp.mol[1].res[0].spin.add_item(spin_name='N5')\n cdp.mol[1].res[1].spin.add_item(spin_name='N5')\n cdp.mol[1].res[1].spin.add_item(spin_name='2H', spin_num=132)\n\n # Deselect a number of spins.\n cdp.mol[0].res[0].spin[0].select = 0\n cdp.mol[0].res[2].spin[0].select = 0\n cdp.mol[1].res[0].spin[0].select = 0\n cdp.mol[1].res[1].spin[1].select = 0\n\n # Update the metadata.\n mol_res_spin.metadata_update()","def test_xyzp_qm_7b():\n subject = subject7\n\n with pytest.raises(qcelemental.MoleculeFormatError):\n final, intermed = qcelemental.molparse.from_string(subject, return_processed=True, dtype='xyz')","def test_wrong_len(mocker: MockFixture, tmp_path: Path):\n df = read_molecules(PATH_TEST / \"smiles_carboxylic.csv\")\n opts = create_options(tmp_path)\n\n mocked_df = pd.DataFrame.from_dict({'ligand': ['CO', 'CC'], 'V_bulk': [1, 2]})\n mocker.patch(\n \"flamingo.cat_interface.compute_property_using_cat\", return_value=mocked_df)\n\n data = compute_batch_bulkiness(df.smiles, opts, pd.Index(list(range(4))))\n\n assert np.all(np.isnan(data))","def test_molecule_from_pdb_error_non_canonical_aa(self):\n with pytest.raises(\n UnassignedChemistryInPDBError,\n match=(\n r\"The following residue names with unassigned atoms were \"\n + r\"not found in the substructure library. While the OpenFF \"\n + r\"Toolkit identifies residues by matching chemical \"\n + r\"substructures rather than by residue name, it currently \"\n + r\"only supports the 20 'canonical' amino acids\\.\\n\\s*DYE\"\n ),\n ):\n Molecule.from_polymer_pdb(\n get_data_file_path(\"proteins/fluoresceine_dyed_helix_capped.pdb\")\n )","def test_exception_result(self):\n raiser = self.make_wrapped_function()\n self.assertRaises(ZeroDivisionError, raiser, ZeroDivisionError())","def test_set_molecule(self):\n mol = Molecule.from_smiles(\"CCO\")\n atom = Atom(6, 0, False)\n atom.molecule = mol","def test_spin_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the spins.\n i = 0\n for spin in mol_res_spin.spin_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_exception_list_nonempty(self):\n complex_id_list = map(float, range(0,3)) #0.0 ~ 2.0\n dataloader = lambda d: d\n calc_func = lambda d1,d2: d1 / d2 #DivisionByZeroError\n \n actual_result, actual_exception = complex_pairwise_calc(complex_id_list, dataloader, calc_func, symmetry=False)\n expected_exception = [(1,0),(2,0),(0,0)]\n expected_result = [(0.0, 1.0, 0.0), (0.0, 2.0, 0.0), (1.0, 2.0, 0.5), (2.0, 1.0, 2.0), (1.0, 1.0, 1.0), (2.0, 2.0, 1.0)]\n \n self.assertEqual(actual_result, expected_result)\n self.assertEqual(actual_exception, expected_exception)","def test_get_center_invalid_errors(syn):\n with patch.object(\n syn, \"tableQuery\", return_value=QueryResponse\n ) as patch_query, patch.object(\n write_invalid_reasons, \"_combine_center_file_errors\", return_value=\"errors\"\n ) as patch_combine:\n center_invalid = write_invalid_reasons.get_center_invalid_errors(syn, \"syn3333\")\n assert center_invalid == {\"SAGE\": \"errors\", \"TEST\": \"errors\"}\n patch_query.assert_called_once_with(\"SELECT * FROM syn3333\")\n assert patch_combine.call_count == 2","def test_nothing_perceived_dipeptide(self):\n from openff.toolkit._tests.create_molecules import dipeptide as create_dipeptide\n\n dipeptide = create_dipeptide()\n\n with pytest.raises(KeyError):\n assert dipeptide.atoms[0].metadata[\"residue_name\"] is None\n with pytest.raises(KeyError):\n assert \"ALA\" == dipeptide.atoms[10].metadata[\"residue_name\"]\n with pytest.raises(KeyError):\n assert 1 == dipeptide.atoms[10].metadata[\"residue_number\"]\n with pytest.raises(KeyError):\n assert \" \" == dipeptide.atoms[10].metadata[\"insertion_code\"]\n with pytest.raises(AttributeError):\n dipeptide.residues[0]","def test_exceptions_optimal_sector(symbols, geometry, generators, num_electrons, msg_match):\n mol = qml.qchem.Molecule(symbols, geometry)\n hamiltonian = qml.qchem.diff_hamiltonian(mol)()\n\n with pytest.raises(ValueError, match=msg_match):\n optimal_sector(hamiltonian, generators, num_electrons)","def test_verify_mol_input():\n # good input with extra spaces\n mol_input_dict = read_mol_input(os.path.join(TEST_DIR, \"example2_mol_input_file.txt\"))\n verify_mol_input(mol_input_dict)\n\n # check the good file\n # {'qcm': 'hf', 'basis': 'sto-3g', 'struct_input': 'C=CC=C',\n # 'struct_type': 'smiles', 'prog': 'psi4', 'charge': '0', 'multip': '1'}\n mol_input_dict = read_mol_input(os.path.join(TEST_DIR, \"example_mol_input_file.txt\"))\n verify_mol_input(mol_input_dict)\n # reset all params that are modified by verification\n mol_input_dict[\"charge\"] = '0'\n mol_input_dict[\"multip\"] = '1'\n\n # struct input is spelt wrong\n mol_input_dict2 = read_mol_input(os.path.join(TEST_DIR, \"bad3_mol_input_file.txt\"))\n assert_raises(ValueError, verify_mol_input, mol_input_dict2)\n\n mol_input_dict[\"qcm\"] = \"not-a-method\"\n assert_raises(ValueError, verify_mol_input, mol_input_dict)\n mol_input_dict[\"qcm\"] = \"hf\"\n # reset all params that are modified by verification\n mol_input_dict[\"charge\"] = '0'\n mol_input_dict[\"multip\"] = '1'\n\n mol_input_dict[\"basis\"] = \"not-a-basis\"\n assert_raises(ValueError, verify_mol_input, mol_input_dict)\n mol_input_dict[\"basis\"] = \"sto-3g\"\n # reset all params that are modified by verification\n mol_input_dict[\"charge\"] = '0'\n mol_input_dict[\"multip\"] = '1'\n\n mol_input_dict[\"struct_input\"] = \"very-bad-smiles-string\"\n assert_raises(ValueError, verify_mol_input, mol_input_dict)\n mol_input_dict[\"struct_input\"] = \"C=CC=C\"\n # reset all params that are modified by verification\n mol_input_dict[\"charge\"] = '0'\n mol_input_dict[\"multip\"] = '1'\n\n mol_input_dict[\"struct_type\"] = \"not-an-option\"\n assert_raises(AssertionError, verify_mol_input, mol_input_dict)\n mol_input_dict[\"struct_type\"] = \"smiles\"\n # reset all params that are modified by verification\n mol_input_dict[\"charge\"] = '0'\n mol_input_dict[\"multip\"] = '1'\n\n mol_input_dict[\"prog\"] = \"unavailable-prog\"\n assert_raises(AssertionError, verify_mol_input, mol_input_dict)\n mol_input_dict[\"prog\"] = \"psi4\"\n # reset all params that are modified by verification\n mol_input_dict[\"charge\"] = '0'\n mol_input_dict[\"multip\"] = '1'\n\n mol_input_dict[\"charge\"] = \"0.34\"\n assert_raises(ValueError, verify_mol_input, mol_input_dict)\n mol_input_dict[\"charge\"] = \"0\"\n # reset all params that are modified by verification\n mol_input_dict[\"multip\"] = '1'\n\n mol_input_dict[\"multip\"] = \"-2\"\n assert_raises(AssertionError, verify_mol_input, mol_input_dict)","def test_result(self):\n result = compute()\n self.assertEqual(result, '4782')\n print(\"eulpy25Test passed\")","def exception_catcher(func):\n\n @wraps(func)\n def wrapper(*args, **kwargs):\n\n try:\n return func(*args, **kwargs)\n\n except Exception as exc:\n if len(args) >= 1 and hasattr(args[0], 'molecule'):\n if hasattr(args[0].molecule, 'bulk_run'):\n if not args[0].molecule.bulk_run:\n raise\n else:\n raise\n\n print(exc)\n\n return wrapper","def test_get_thermo_data_mopac(self):\n output_directory = os.path.join(self.mop1.settings.fileStore, '..', '..')\n self.mop1.set_default_output_directory(output_directory)\n self.mop2.set_default_output_directory(output_directory)\n self.mop3.set_default_output_directory(output_directory)\n\n mol = Molecule().from_smiles('C1=CC=C2C=CC=CC2=C1')\n\n for directory in (self.mop1.settings.fileStore, self.mop1.settings.scratchDirectory):\n shutil.rmtree(directory, ignore_errors=True)\n\n for directory in (self.mop2.settings.fileStore, self.mop2.settings.scratchDirectory):\n shutil.rmtree(directory, ignore_errors=True)\n\n for directory in (self.mop3.settings.fileStore, self.mop3.settings.scratchDirectory):\n shutil.rmtree(directory, ignore_errors=True)\n\n thermo1 = self.mop1.get_thermo_data(mol)\n thermo2 = self.mop2.get_thermo_data(mol)\n thermo3 = self.mop3.get_thermo_data(mol)\n\n self.assertTrue(thermo1.comment.startswith('QM MopacMolPM3'))\n self.assertTrue(thermo2.comment.startswith('QM MopacMolPM6'))\n self.assertTrue(thermo3.comment.startswith('QM MopacMolPM7'))\n\n self.assertAlmostEqual(thermo1.H298.value_si, 169708.0608, 1) # to 1 decimal place\n self.assertAlmostEqual(thermo1.S298.value_si, 334.5007584, 1) # to 1 decimal place\n self.assertAlmostEqual(thermo2.H298.value_si, 167704.4270, 1) # to 1 decimal place\n self.assertAlmostEqual(thermo2.S298.value_si, 338.0999241, 1) # to 1 decimal place\n self.assertAlmostEqual(thermo3.H298.value_si, 166168.8571, 1) # to 1 decimal place\n self.assertAlmostEqual(thermo3.S298.value_si, 336.3330406, 1) # to 1 decimal place","def _get_components(\n design_unit: oechem.OEDesignUnit\n ) -> Tuple[oechem.OEGraphMol(), oechem.OEGraphMol(), oechem.OEGraphMol()]:\n from openeye import oechem\n\n protein, solvent, ligand = oechem.OEGraphMol(), oechem.OEGraphMol(), oechem.OEGraphMol()\n\n logging.debug(\"Extracting molecular components ...\")\n design_unit.GetProtein(protein)\n design_unit.GetSolvent(solvent)\n design_unit.GetLigand(ligand)\n\n # delete protein atoms with no name (found in prepared protein of 4ll0)\n for atom in protein.GetAtoms():\n if not atom.GetName().strip():\n logging.debug(\"Deleting unknown atom ...\")\n protein.DeleteAtom(atom)\n\n # perceive residues to remove artifacts of other design units in the sequence of the protein\n # preserve certain properties to assure correct behavior of the pipeline,\n # e.g. deletion of chains in OEKLIFSKinaseApoFeaturizer._process_kinase_domain method\n preserved_info = (\n oechem.OEPreserveResInfo_ResidueNumber\n | oechem.OEPreserveResInfo_ResidueName\n | oechem.OEPreserveResInfo_AtomName\n | oechem.OEPreserveResInfo_ChainID\n | oechem.OEPreserveResInfo_HetAtom\n | oechem.OEPreserveResInfo_InsertCode\n | oechem.OEPreserveResInfo_AlternateLocation\n )\n oechem.OEPerceiveResidues(protein, preserved_info)\n oechem.OEPerceiveResidues(solvent, preserved_info)\n oechem.OEPerceiveResidues(ligand)\n\n logging.debug(\n \"Number of component atoms: \" +\n f\"Protein - {protein.NumAtoms()}, \" +\n f\"Solvent - {solvent.NumAtoms()}, \" +\n f\"Ligand - {ligand.NumAtoms()}.\"\n )\n return protein, solvent, ligand","def failure(self, result):\r\n raise NotImplementedError","def test():\r\n\tassert calcolatrice.__author__ == \"help@castellanidavide.it\", \"sanity test failed\"\r\n\t#assert calcolatrice.<function>(<values>) == <the result(s) you would like to have>, \"<the fail message>\"\r","def test_spin_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for spin in mol_res_spin.spin_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def test_deferred_failure_result(self):\n passthrough = self.make_wrapped_function()\n self.assertRaises(\n ZeroDivisionError, passthrough, fail(ZeroDivisionError()))","def testNoOutputCausesFailure(self):\n self._get_mock.return_value = (set(['foo_ci']), False)\n with self.assertRaises(RuntimeError):\n builders.GetTryBuilders(['foo_ci'])","def test_from_qcschema_no_client(self):\n\n import json\n\n # As the method can take a record instance or a dict with JSON encoding test both\n # test incomplete dict\n example_dict = {\"name\": \"CH4\"}\n with pytest.raises(KeyError):\n mol = Molecule.from_qcschema(example_dict)\n\n # test an object that is not a record\n wrong_object = \"CH4\"\n with pytest.raises(AttributeError):\n mol = Molecule.from_qcschema(wrong_object)\n\n with open(get_data_file_path(\"molecules/qcportal_molecules.json\")) as json_file:\n # test loading the dict representation from a json file\n json_mol = json.load(json_file)\n mol = Molecule.from_qcschema(json_mol)\n # now make a molecule from the canonical smiles and make sure they are isomorphic\n can_mol = Molecule.from_smiles(\n json_mol[\"attributes\"][\"canonical_isomeric_smiles\"]\n )\n assert mol.is_isomorphic_with(can_mol) is True","def test_from_qcschema_no_client(self):\n\n import json\n\n # As the method can take a record instance or a dict with JSON encoding test both\n # test incomplete dict\n example_dict = {\"name\": \"CH4\"}\n with pytest.raises(KeyError):\n mol = Molecule.from_qcschema(example_dict)\n\n # test an object that is not a record\n wrong_object = \"CH4\"\n with pytest.raises(AttributeError):\n mol = Molecule.from_qcschema(wrong_object)\n\n with open(get_data_file_path(\"molecules/qcportal_molecules.json\")) as json_file:\n # test loading the dict representation from a json file\n json_mol = json.load(json_file)\n mol = Molecule.from_qcschema(json_mol)\n # now make a molecule from the canonical smiles and make sure they are isomorphic\n can_mol = Molecule.from_smiles(\n json_mol[\"attributes\"][\"canonical_isomeric_smiles\"]\n )\n assert mol.is_isomorphic_with(can_mol) is True","def test_operator_with_invalid_wire(self, monkeypatch, test_batch_result):\n dev = QeQiskitDevice(\n wires=[\"a\", \"b\", \"c\"], shots=1000, backend=\"qasm_simulator\", analytic=False\n )\n\n with monkeypatch.context() as m:\n m.setattr(pennylane_orquestra.cli_actions, \"user_data_dir\", lambda *args: tmpdir)\n\n # Disable submitting to the Orquestra platform by mocking Popen\n m.setattr(subprocess, \"Popen\", lambda *args, **kwargs: MockPopen())\n m.setattr(\n pennylane_orquestra.orquestra_device,\n \"loop_until_finished\",\n lambda *args, **kwargs: test_batch_result,\n )\n\n @qml.qnode(dev)\n def circuit():\n return qml.expval(qml.PauliZ(0))\n\n with pytest.raises(\n qml.qnodes.base.QuantumFunctionError,\n match=\"Operation PauliZ applied to invalid wire\",\n ):\n circuit()","def test_library_charges_dont_parameterize_molecule_because_of_incomplete_coverage(\n self,\n ):\n molecules = [Molecule.from_file(get_data_file_path(\"molecules/toluene.sdf\"))]\n top = Topology.from_molecules(molecules)\n\n # The library charges in the FF should not be able to fully cover toluene\n ff = ForceField(\n get_data_file_path(\"test_forcefields/test_forcefield.offxml\"),\n xml_ethanol_library_charges_by_atom_ff,\n )\n # Delete the ToolkitAM1BCCHandler so the molecule won't get charges from anywhere\n del ff._parameter_handlers[\"ToolkitAM1BCC\"]\n with pytest.raises(\n RuntimeError, match=\"Cc1ccccc1 could not be fully assigned charges\"\n ):\n omm_system = ff.create_openmm_system(top)\n\n # If we do NOT delete the ToolkiAM1BCCHandler, then toluene should be assigned some nonzero partial charges.\n # The exact value will vary by toolkit, so we don't test that here.\n ff = ForceField(\n get_data_file_path(\"test_forcefields/test_forcefield.offxml\"),\n xml_ethanol_library_charges_by_atom_ff,\n )\n omm_system = ff.create_openmm_system(top)\n nonbondedForce = [\n f for f in omm_system.getForces() if type(f) == NonbondedForce\n ][0]\n for particle_index in range(top.n_atoms):\n q, _, _ = nonbondedForce.getParticleParameters(particle_index)\n assert q != 0 * unit.elementary_charge","def test_errors_on_metadata(self):\n mb = self.maria_backup\n\n # correct run\n sample_xtrabackup_info = \"\"\"\n uuid = a6336c86-1b33-11e8-8de6-080027f3a5d8\n tool_name = xtrabackup\n tool_command = –backup –target-dir=/Backups/base –datadir=/var/lib/mysql –user=root –password=… –galera-info\n tool_version = 2.4.9\n ibbackup_version = 2.4.9\n server_version = 5.7.19-17-57-log\n start_time = 2022-02-26 15:28:22\n end_time = 2022-02-26 15:28:48\n \"\"\"\n mock = mock_open(read_data=sample_xtrabackup_info)\n with patch('builtins.open', mock):\n self.assertFalse(mb.errors_on_metadata(''))\n\n # missing end_time\n sample_xtrabackup_info = \"\"\"\n uuid = a6336c86-1b33-11e8-8de6-080027f3a5d8\n tool_name = xtrabackup\n tool_command = –backup –target-dir=/Backups/base –datadir=/var/lib/mysql –user=root –password=… –galera-info\n tool_version = 2.4.9\n ibbackup_version = 2.4.9\n server_version = 5.7.19-17-57-log\n start_time = 2022-02-26 15:28:22\n \"\"\"\n mock = mock_open(read_data=sample_xtrabackup_info)\n with patch('builtins.open', mock):\n self.assertTrue(mb.errors_on_metadata(''))\n\n # simulate open error\n mock = mock_open(read_data=\"\")\n with patch('builtins.open', mock) as mocked_open:\n mocked_open.side_effect = OSError\n self.assertTrue(mb.errors_on_metadata(''))\n\n # simulate read error\n mock = mock_open(read_data=\"\")\n with patch('builtins.open', mock) as mocked_open:\n mocked_file = mocked_open.return_value\n mocked_file.read.side_effect = IOError\n self.assertTrue(mb.errors_on_metadata(''))","def test_wrong_output_provided(self):\n with self.assertRaises(VisualizationError):\n circuit_drawer(None, output='wrong_output')","def setup_molecule_output_check(exp_builder_db, mol_id, output_path):\n exp_builder_db._setup_molecules(mol_id)\n assert os.path.exists(output_path)\n assert os.path.getsize(output_path) > 0","def test_call_incompatible_data(self):\r\n self.cs_overview.DistanceMatrices = [self.single_ele_dm,\r\n self.single_ele_dm]\r\n self.assertRaises(ValueError, self.cs_overview)","def test_rsp_invalid(self):\n\n def handle(event):\n ds = Dataset()\n ds.PatientName = \"Test^test\"\n return 0x0000, ds\n\n self.ae = ae = AE()\n ae.acse_timeout = 5\n ae.dimse_timeout = 0.4\n ae.network_timeout = 5\n ae.add_supported_context(ModalityPerformedProcedureStep)\n scp = ae.start_server(\n (\"localhost\", 11112), block=False, evt_handlers=[(evt.EVT_N_SET, handle)]\n )\n\n ae.add_requested_context(ModalityPerformedProcedureStep)\n assoc = ae.associate(\"localhost\", 11112)\n assert assoc.is_established\n\n class DummyResponse:\n is_valid_response = False\n\n class DummyDIMSE:\n msg_queue = queue.Queue()\n gotten = False\n\n def send_msg(*args, **kwargs):\n return\n\n def get_msg(self, *args, **kwargs):\n if not self.gotten:\n self.gotten = True\n return None, DummyResponse()\n return None, None\n\n assoc._reactor_checkpoint.clear()\n while not assoc._is_paused:\n time.sleep(0.01)\n assoc.dimse = DummyDIMSE()\n mod_list = Dataset()\n mod_list.PatientName = \"Test^test\"\n status, ds = assoc.send_n_set(\n mod_list, ModalityPerformedProcedureStep, \"1.2.840.10008.5.1.1.40.1\"\n )\n\n assert status == Dataset()\n assert ds is None\n assert assoc.is_aborted\n\n scp.shutdown()","def test_bad_data(self):\r\n # LB180210_3_corrupted.PD0 has three records in it, the 2nd record was corrupted\r\n with open(os.path.join(RESOURCE_PATH, 'LB180210_3_corrupted.PD0'), 'rb') as stream_handle:\r\n\r\n parser = AdcpPd0Parser(self.config_recov, stream_handle, self.exception_callback)\r\n\r\n # try to get 3 particles, should only get 2 back\r\n # the second one should correspond to ensemble 3\r\n parser.get_records(3)\r\n\r\n log.debug('Exceptions : %s', self.exception_callback_value[0])\r\n\r\n self.assertEqual(len(self.exception_callback_value), 1)\r\n self.assert_(isinstance(self.exception_callback_value[0], RecoverableSampleException))","def test_synchronize_splits_error(self, mocker):\n storage = mocker.Mock(spec=SplitStorage)\n api = mocker.Mock()\n\n def run(x, c):\n raise APIException(\"something broke\")\n run._calls = 0\n api.fetch_splits.side_effect = run\n storage.get_change_number.return_value = -1\n\n from splitio.sync.split import SplitSynchronizer\n split_synchronizer = SplitSynchronizer(api, storage)\n\n with pytest.raises(APIException):\n split_synchronizer.synchronize_splits(1)","def test_get_molecule_least_similar_to(self):\n csv_fpath = self.smiles_seq_to_xl_or_csv(ftype=\"csv\")\n for descriptor in SUPPORTED_FPRINTS:\n for similarity_measure in SUPPORTED_SIMILARITIES:\n molecule_set = MoleculeSet(\n molecule_database_src=csv_fpath,\n molecule_database_src_type=\"csv\",\n fingerprint_type=descriptor,\n similarity_measure=similarity_measure,\n is_verbose=False,\n )\n for mol_smile, mol in zip(TEST_SMILES,\n molecule_set.molecule_database):\n compare_task = CompareTargetMolecule(\n target_molecule_smiles=mol_smile)\n [furthest_mol], [similarity] = compare_task.\\\n get_hits_dissimilar_to(molecule_set)\n mol_similarities = molecule_set.compare_against_molecule(\n mol)\n self.assertEqual(\n np.min(mol_similarities),\n mol.get_similarity_to(\n molecule_set.molecule_database[furthest_mol],\n molecule_set.similarity_measure\n ),\n f\"Expected furthest mol to have minimum \"\n f\"similarity to target molecule \"\n f\"using similarity measure: {similarity_measure}, \"\n f\"descriptor: {descriptor}, \"\n f\"for molecule {mol.mol_text}\",\n )\n self.assertGreaterEqual(similarity, 0.,\n \"Expected similarity value to \"\n \"be >= 0.\"\n f\"using similarity measure: \"\n f\"{similarity_measure}, \"\n f\"descriptor: {descriptor}, \"\n f\"for molecule {mol.mol_text}\")\n self.assertLessEqual(similarity, 1.,\n \"Expected similarity value to \"\n \"be <= 1.\"\n f\"using similarity measure: \"\n f\"{similarity_measure}, \"\n f\"descriptor: {descriptor}, \"\n f\"for molecule {mol.mol_text}\"\n )","def test_no_outputs():\r\n # test module\r\n test_data = doc.MatObject.matlabify('test_data')\r\n test_submodule = test_data.getter('test_submodule')\r\n ok_(isinstance(test_submodule, doc.MatModule))\r\n eq_(test_submodule.__package__, 'test_data.test_submodule')\r\n f = test_submodule.getter('f_no_outputs')\r\n ok_(isinstance(f, doc.MatFunction))\r\n ok_(not f.retv)\r\n eq_(f.args, ['arg'])\r\n return f","def test_block_structure_matrices_on_elements_validity(n_rods):\n world_rods = [MockRod(np.random.randint(10, 30 + 1)) for _ in range(n_rods)]\n block_structure = MemoryBlockCosseratRod(\n world_rods, [i for i in range(len(world_rods))]\n )\n\n for i in range(n_rods):\n start_idx = block_structure.start_idx_in_rod_elems[i]\n end_idx = block_structure.end_idx_in_rod_elems[i]\n\n # director collection\n assert np.shares_memory(\n block_structure.director_collection, world_rods[i].director_collection\n )\n assert np.shares_memory(\n block_structure.matrix_dofs_in_rod_elems, world_rods[i].director_collection\n )\n assert_allclose(\n block_structure.director_collection[..., start_idx:end_idx],\n world_rods[i].director_collection,\n )\n\n # mass second moment of inertia\n assert np.shares_memory(\n block_structure.mass_second_moment_of_inertia,\n world_rods[i].mass_second_moment_of_inertia,\n )\n assert np.shares_memory(\n block_structure.matrix_dofs_in_rod_elems,\n world_rods[i].mass_second_moment_of_inertia,\n )\n assert_allclose(\n block_structure.mass_second_moment_of_inertia[..., start_idx:end_idx],\n world_rods[i].mass_second_moment_of_inertia,\n )\n\n # inv mass second moment of inertia\n assert np.shares_memory(\n block_structure.inv_mass_second_moment_of_inertia,\n world_rods[i].inv_mass_second_moment_of_inertia,\n )\n assert np.shares_memory(\n block_structure.matrix_dofs_in_rod_elems,\n world_rods[i].inv_mass_second_moment_of_inertia,\n )\n assert_allclose(\n block_structure.inv_mass_second_moment_of_inertia[..., start_idx:end_idx],\n world_rods[i].inv_mass_second_moment_of_inertia,\n )\n\n # shear matrix\n assert np.shares_memory(\n block_structure.shear_matrix, world_rods[i].shear_matrix\n )\n assert np.shares_memory(\n block_structure.matrix_dofs_in_rod_elems, world_rods[i].shear_matrix\n )\n assert_allclose(\n block_structure.shear_matrix[..., start_idx:end_idx],\n world_rods[i].shear_matrix,\n )","def test_givens_decomposition_exceptions(unitary_matrix, msg_match):\n\n with pytest.raises(ValueError, match=msg_match):\n givens_decomposition(unitary_matrix)","def meta_res(simulatedata_cbma, meta, random):\n _, (_, dataset) = simulatedata_cbma\n # CHECK IF META/KERNEL WORK TOGETHER\n ####################################\n meta_expectation = does_not_raise()\n\n with meta_expectation:\n res = meta.fit(dataset)\n # if creating the result failed (expected), do not continue\n if isinstance(meta_expectation, type(pytest.raises(ValueError))):\n pytest.xfail(\"this meta-analysis & kernel combo fails\")\n # instantiate meta-analysis estimator\n return res","def test_rr_bcibad(results):\n ci1 = results.effect_ci(citype=\"Some Unsupported Type\")\n assert np.all(np.isnan(ci1))","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def experiment3():\n raise FAKE_ERROR","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_main_exit_absent(self, mock_delete_volume, mock_module, mock_client):\n PARAMS = {\n 'storage_system_ip': '192.168.0.1',\n 'storage_system_name': '3PAR',\n 'storage_system_username': 'USER',\n 'storage_system_password': 'PASS',\n 'volume_name': 'test_volume',\n 'cpg': None,\n 'size': None,\n 'size_unit': None,\n 'snap_cpg': None,\n 'wait_for_task_to_end': None,\n 'new_name': None,\n 'expiration_hours': None,\n 'retention_hours': None,\n 'ss_spc_alloc_warning_pct': None,\n 'ss_spc_alloc_limit_pct': None,\n 'usr_spc_alloc_warning_pct': None,\n 'usr_spc_alloc_limit_pct': None,\n 'rm_ss_spc_alloc_warning': None,\n 'rm_usr_spc_alloc_warning': None,\n 'rm_exp_time': None,\n 'rm_usr_spc_alloc_limit': None,\n 'rm_ss_spc_alloc_limit': None,\n 'compression': False,\n 'type': 'thin',\n 'keep_vv': None,\n 'state': 'absent'\n }\n # This creates a instance of the AnsibleModule mock.\n mock_module.params = PARAMS\n mock_module.return_value = mock_module\n instance = mock_module.return_value\n mock_delete_volume.return_value = (True, True, \"Deleted volume successfully.\", {})\n hpe3par_volume.main()\n # AnsibleModule.exit_json should be called\n instance.exit_json.assert_called_with(\n changed=True, msg=\"Deleted volume successfully.\")\n # AnsibleModule.fail_json should not be called\n self.assertEqual(instance.fail_json.call_count, 0)","def test_call_vmec(self):\n self.set_up()\n inputObject = self.vmecOptimization.vmecInputObject\n inputObject_new = VmecInput(self.input_filename_intersecting)\n error_code = self.vmecOptimization.call_vmec(inputObject_new)\n self.assertEqual(error_code,16)\n \n # To do : add test for ill-conditioned Jacobian\n# rbc = np.copy(inputObject.rbc)\n# zbs = np.copy(inputObject.zbs)\n# inputObject.rbc[1::] = 1e-4*inputObject.rbc[1::]\n# inputObject.zbs = inputObject.zbs\n# error_code = self.vmecOptimization.call_vmec(inputObject)\n# self.assertEqual(error_code,16)\n # Reset boundary\n# inputObject.rbc = rbc\n# inputObject.zbs = zbs\n \n inputObject = VmecInput(self.input_filename)\n error_code = self.vmecOptimization.call_vmec(inputObject)\n self.assertEqual(error_code,0)\n self.tear_down()","def test_call(self):\r\n args = [\"-d \" + self.dm_fp + \" -m \" + self.map_fp +\r\n \" -c DOB -o \" + self.output_dir]\r\n\r\n rex = RExecutor(TmpDir=self.tmp_dir)\r\n results = rex(args, \"permdisp.r\", self.output_dir)\r\n\r\n self.files_to_remove.append(join(self.tmp_dir, 'R.stdout'))\r\n self.files_to_remove.append(join(self.tmp_dir, 'R.stderr'))\r\n\r\n # Make sure an output file was created with something in it.\r\n results_fp = join(self.output_dir, 'permdisp_results.txt')\r\n results_f = open(results_fp, 'U')\r\n results = results_f.read()\r\n results_f.close()\r\n self.files_to_remove.append(results_fp)\r\n self.assertTrue(len(results) > 0)","def test_bad_statistics():\n dev = _aws_device(wires=1, foo=\"bar\")\n observable = qml.Identity(wires=0, do_queue=False)\n observable.return_type = None\n\n with pytest.raises(QuantumFunctionError, match=\"Unsupported return type specified\"):\n dev.statistics(None, [observable])","def test_re_split_cell_raises_error(mock_amg):\n\n # splitting once should work as normal\n mock_amg.cells[4].split()\n\n with pytest.raises(ValueError):\n mock_amg.cells[4].split()","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_part_1(arguments, output):\n # assert part_1.solution(arguments) == output\n assert part_1.solution(arguments) == output","def testError(self):\n cmds = \"\"\"chown 0 missingFile\npwd\nexit\n\"\"\"\n\n def _cbCheckResult(res):\n self.assertNotIn(self.testDir.asBytesMode().path, res)\n\n d = self._getBatchOutput(cmds)\n d.addCallback(_cbCheckResult)\n return d","def test_partial_channel_invalid_map():\n with np.testing.assert_raises(ValueError):\n rho = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [12, 11, 10, 9]])\n partial_channel(rho, 5)","def test_init_ClusterNotFoundByName(self):\n self.mock_search.return_value = []\n self.assertRaises(npvmex.ClusterNotFoundByName, self._get_ssp_stor)","def testCCHalt(self):\n cdl_convert.config.HALT_ON_ERROR = True\n\n def getCC():\n self.ccr_bad.cc\n\n self.assertRaises(\n ValueError,\n getCC\n )","def test_discover_array_fail(self):\n self._set_args({\"password\": \"password\", \"subnet_mask\": \"192.168.1.0/24\", \"add_discovered_systems\": True})\n systems = NetAppESeriesProxySystems()\n with self.assertRaisesRegex(AnsibleFailJson, \"Failed to initiate array discovery.\"):\n with mock.patch(self.TIME_FUNC, return_value=None):\n with mock.patch(self.REQUEST_FUNC, return_value=Exception()):\n systems.discover_array()\n\n self._set_args({\"password\": \"password\", \"subnet_mask\": \"192.168.1.0/24\", \"add_discovered_systems\": True})\n systems = NetAppESeriesProxySystems()\n with self.assertRaisesRegex(AnsibleFailJson, \"Failed to get the discovery results.\"):\n with mock.patch(self.TIME_FUNC, return_value=None):\n with mock.patch(self.REQUEST_FUNC, side_effect=[(200, {\"requestId\": \"1\"}), Exception()]):\n systems.discover_array()\n\n self._set_args({\"password\": \"password\", \"subnet_mask\": \"192.168.1.0/24\", \"add_discovered_systems\": True})\n systems = NetAppESeriesProxySystems()\n with self.assertRaisesRegex(AnsibleFailJson, \"Timeout waiting for array discovery process.\"):\n with mock.patch(self.TIME_FUNC, return_value=None):\n with mock.patch(self.REQUEST_FUNC, side_effect=[(200, {\"requestId\": \"1\"})] + [(200, {\"discoverProcessRunning\": True})] * 1000):\n systems.discover_array()","def test_init(self):\n nt.assert_raises(Exception, CisInterface.CisOutput, 'error')","def test_compute_partial_charges(self):\n # TODO: Test only one molecule for speed?\n # TODO: Do we need to deepcopy each molecule, or is setUp called separately for each test method?\n import numpy as np\n from simtk import unit\n\n # Do not modify original molecules.\n molecules = copy.deepcopy(mini_drug_bank())\n\n # Test a single toolkit at a time\n # Removed ['amber', 'amberff94'] from OE list, as those won't find the residue types they're expecting\n toolkit_to_charge_method = {\n OpenEyeToolkitWrapper: [\n \"mmff\",\n \"mmff94\",\n \"am1bcc\",\n \"am1bccnosymspt\",\n \"am1bccelf10\",\n ],\n AmberToolsToolkitWrapper: [\"bcc\", \"gas\", \"mul\"],\n }\n\n manual_skips = []\n\n manual_skips.append(\n \"ZINC1564378\"\n ) # Warning: OEMMFF94Charges: assigning OEMMFFAtomTypes failed on mol .\n manual_skips.append(\n \"ZINC00265517\"\n ) # Warning: OEMMFF94Charges: assigning OEMMFFAtomTypes failed on mol .\n\n for toolkit in list(toolkit_to_charge_method.keys()):\n toolkit_registry = ToolkitRegistry(toolkit_precedence=[toolkit])\n for charge_model in toolkit_to_charge_method[toolkit]:\n c = 0\n for molecule in molecules[:1]: # Just test first molecule to save time\n c += 1\n if molecule.name in manual_skips: # Manual skips, hopefully rare\n continue\n molecule.compute_partial_charges(\n charge_model=charge_model, toolkit_registry=toolkit_registry\n )\n charges1 = molecule._partial_charges\n # Make sure everything isn't 0s\n assert (abs(charges1 / unit.elementary_charge) > 0.01).any()\n # Check total charge\n charges_sum_unitless = charges1.sum() / unit.elementary_charge\n # if abs(charges_sum_unitless - float(molecule.total_charge)) > 0.0001:\n # print('c {} molecule {} charge_sum {} molecule.total_charge {}'.format(c, molecule.name,\n # charges_sum_unitless,\n # molecule.total_charge))\n # assert_almost_equal(charges_sum_unitless, molecule.total_charge, decimal=4)\n\n # Call should be faster second time due to caching\n # TODO: Implement caching\n molecule.compute_partial_charges(\n charge_model=charge_model, toolkit_registry=toolkit_registry\n )\n charges2 = molecule._partial_charges\n assert np.allclose(charges1, charges2, atol=0.002)","def test_run_read(self):\n\n self.ictrl[0] = 1 + 2 + 4 + 8\n vmec_f90wrap.runvmec(self.ictrl, self.filename, self.verbose, \\\n self.fcomm, reset_file)\n\n self.assertTrue(self.ictrl[1] in success_codes)\n\n self.assertEqual(vmec_f90wrap.vmec_input.nfp, 3)\n self.assertEqual(vmec_f90wrap.vmec_input.mpol, 4)\n self.assertEqual(vmec_f90wrap.vmec_input.ntor, 3)\n print('rbc.shape:', vmec_f90wrap.vmec_input.rbc.shape)\n print('rbc:',vmec_f90wrap.vmec_input.rbc[101:103, 0:4])\n\n # n = 0, m = 0:\n self.assertAlmostEqual(vmec_f90wrap.vmec_input.rbc[101,0], 1.3782)\n\n # n = 0, m = 1:\n self.assertAlmostEqual(vmec_f90wrap.vmec_input.zbs[101,1], 4.6465E-01)\n\n # n = 1, m = 1:\n self.assertAlmostEqual(vmec_f90wrap.vmec_input.zbs[102,1], 1.6516E-01)\n\n # Now try reading in the output\n wout_file = os.path.join(os.path.dirname(__file__), 'wout_li383_low_res.nc')\n ierr = 0\n vmec_f90wrap.read_wout_mod.read_wout_file(wout_file, ierr)\n self.assertEqual(ierr, 0)\n self.assertAlmostEqual(vmec_f90wrap.read_wout_mod.betatot, \\\n 0.0426215030653306, places=4)\n\n print('iotaf.shape:',vmec_f90wrap.read_wout_mod.iotaf.shape)\n print('rmnc.shape:',vmec_f90wrap.read_wout_mod.rmnc.shape)\n\n self.assertAlmostEqual(vmec_f90wrap.read_wout_mod.iotaf[-1], \\\n 0.654868168783638, places=4)\n\n self.assertAlmostEqual(vmec_f90wrap.read_wout_mod.rmnc[0, 0], \\\n 1.4773028173065, places=4)","def test_cputemp_get_data_error(self):\n test_sensor_error_data = {\n \"sensorid\": int(self.test_sens_data['sensorid']),\n \"error\": \"Exception\",\n \"code\": 1,\n \"message\": \"CPUTemp sensor failed. See log for details\"\n }\n self.test_cputemp.get_data(self.test_sens_data, self.test_out_queue)\n assert_equal(self.test_out_queue.get(), test_sensor_error_data)","def test_returns_block() -> None:\n gr = BlobGoal(REAL_RED)\n gp = PerimeterGoal(MELON_MAMBO)\n board = one_block_four_children_(1)\n rp = RandomPlayer(0, gr)\n sp = SmartPlayer(1, gp, 10)\n rp._proceed = True\n sp._proceed = True\n move_block_rp = rp.generate_move(board)[2]\n move_block_sp = sp.generate_move(board)[2]\n assert move_block_rp == board or move_block_rp in board.children\n assert move_block_sp == board or move_block_sp in board.children","def testOutputReturned(self):\n\n def SideEffect(ci_builder):\n b = [\n ci_builder.replace('ci', 'try'),\n ci_builder.replace('ci', 'try2'),\n ]\n return set(b), True\n\n self._get_mock.side_effect = SideEffect\n mirrored_builders = builders.GetTryBuilders(['foo_ci', 'bar_ci'])\n self.assertEqual(mirrored_builders,\n set(['foo_try', 'foo_try2', 'bar_try', 'bar_try2']))","def test_molecule_from_pdb_error_crystal_waters(self):\n with pytest.raises(\n UnassignedChemistryInPDBError,\n match=(\n r\"Note: 'HOH' is a residue code for water. You may have \"\n + r\"crystallographic waters in your PDB file. Please remove \"\n + r\"these before proceeding, or use Topology.from_pdb\\.\"\n ),\n ):\n Molecule.from_polymer_pdb(\n get_data_file_path(\"proteins/T4_protein_waters.pdb\")\n )","def test_invalid_input_data(self):\n self.data.diffusion_data = self.data.diffusion_data[0]\n self.assertRaises(ValueError, module_05.run_module,\n self.data)"],"string":"[\n \"def test_return_molecule(self):\\n\\n # Ask for a few molecules.\\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\\n\\n # Test the data of molecule 1.\\n self.assertEqual(mol1.name, 'Ap4Aase')\\n\\n # Test the data of molecule 2.\\n self.assertEqual(mol2.name, 'RNA')\",\n \"def test_molecule_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the molecules.\\n i = 0\\n for molecule in mol_res_spin.molecule_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_return_single_residue_info_fail(self):\\n\\n # Ask for a few residues.\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')\",\n \"def test_return_residue_pipe_fail(self):\\n\\n # Try to get a residue from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_return_residue(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_residue(':1')\\n res2 = mol_res_spin.return_residue(selection=':2')\\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1.num, 1)\\n self.assertEqual(res1.name, None)\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2.num, 2)\\n self.assertEqual(res2.name, 'Glu')\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4.num, 4)\\n self.assertEqual(res4.name, 'Pro')\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5.num, -5)\\n self.assertEqual(res5.name, None)\\n self.assertEqual(res5.spin[1].name, 'N5')\",\n \"def test_return_spin_pipe_fail(self):\\n\\n # Try to get a spin from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')\",\n \"def test_molecule_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for molecule in mol_res_spin.molecule_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_molecule_loop_no_selection(self):\\n\\n # Molecule data.\\n name = ['Ap4Aase', 'RNA']\\n\\n # Loop over the molecules.\\n i = 0\\n for mol in mol_res_spin.molecule_loop():\\n # Test the molecule names.\\n self.assertEqual(mol.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def test_validation_wrong_molecules():\\n paths = examples_paths()\\n paths['wrongformat'] = utils.get_data_filename(os.path.join('tests', 'data', 'README.md'))\\n molecules = [\\n {'antechamber': {'charge_method': 'bcc'}},\\n {'filepath': paths['wrongformat']},\\n {'name': 'p-xylene', 'antechamber': {'charge_method': 'bcc'}, 'unknown': 4},\\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'}},\\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'invalid'},\\n 'antechamber': {'charge_method': None}},\\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'},\\n 'antechamber': {'charge_method': 'bcc'}},\\n {'filepath': 'nonexistentfile.pdb', 'leap': {'parameters': 'leaprc.ff14SB'}},\\n {'filepath': paths['toluene'], 'smiles': 'Cc1ccccc1'},\\n {'filepath': paths['toluene'], 'strip_protons': True},\\n {'filepath': paths['abl'], 'leap': {'parameters': 'oldff/leaprc.ff14SB'}, 'epik': {'select': 0}},\\n {'name': 'toluene', 'epik': 0},\\n {'name': 'toluene', 'epik': {'tautomerize': 6}},\\n {'name': 'toluene', 'epik': {'extract_range': 1}},\\n {'name': 'toluene', 'smiles': 'Cc1ccccc1'},\\n {'name': 3},\\n {'smiles': 'Cc1ccccc1', 'select': 1},\\n {'name': 'Cc1ccccc1', 'select': 1},\\n {'filepath': paths['abl'], 'leap': {'parameters': 'oldff/leaprc.ff14SB'}, 'select': 'notanoption'},\\n {'filepath': paths['abl'], 'regions': 5},\\n {'filepath': paths['abl'], 'regions': {'a_region': [-56, 5.23]}},\\n {'filepath': paths['toluene'], 'leap': {'parameters': 'leaprc.gaff'}, 'strip_protons': True},\\n ]\\n for molecule in molecules:\\n yield assert_raises, YamlParseError, ExperimentBuilder._validate_molecules, {'mol': molecule}\",\n \"def test_set_molecule_error(self):\\n mol = Molecule.from_smiles(\\\"CCO\\\")\\n atom = Atom(6, 0, False)\\n atom.molecule = mol\\n with pytest.raises(AssertionError, match=\\\"already has an associated molecule\\\"):\\n atom.molecule = mol\",\n \"def test_molecule_loop(self):\\n\\n # Loop over the molecules.\\n for mol in mol_res_spin.molecule_loop('#RNA'):\\n # Test the molecule name.\\n self.assertEqual(mol.name, 'RNA')\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_get_thermo_data(self):\\n output_directory = os.path.join(self.mop4.settings.fileStore, '..', '..')\\n self.mop4.set_default_output_directory(output_directory)\\n self.gauss3.set_default_output_directory(output_directory)\\n self.molpro1.set_default_output_directory(output_directory)\\n\\n mol = Molecule().from_smiles('C1=CC=C2C=CC=CC2=C1')\\n\\n with self.assertRaises(Exception):\\n self.mop4.get_thermo_data(mol)\\n self.gauss3.get_thermo_data(mol)\\n self.molpro1.get_thermo_data(mol)\",\n \"def test_read_fail1(self):\\n mod_fn = os.path.join(tests.TEST_DATA_PATH, 'segmentations', 'test_bad_data1.mod')\\n with self.assertRaises(ValueError):\\n modreader.get_data(mod_fn) # missing 'IMOD' start\",\n \"def test_run_molecule(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def test_return_single_residue_info(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_single_residue_info('1')\\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\\n res5 = mol_res_spin.return_single_residue_info('-5')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1, (1, None))\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2, (2, 'Glu'))\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4, (4, 'Pro'))\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5, (-5, None))\",\n \"def test_read_mol_input():\\n # good input\\n read_mol_input(os.path.join(TEST_DIR, \\\"example_mol_input_file.txt\\\"))\\n # good input with extra spaces\\n read_mol_input(os.path.join(TEST_DIR, \\\"example2_mol_input_file.txt\\\"))\\n # no such file error\\n assert_raises(FileNotFoundError, read_mol_input, 'no-such-file')\\n # qcm appears twice\\n assert_raises(ValueError, read_mol_input, os.path.join(TEST_DIR, \\\"bad1_mol_input_file.txt\\\"))\\n # missing struct type\\n assert_raises(ValueError, read_mol_input, os.path.join(TEST_DIR, \\\"bad2_mol_input_file.txt\\\"))\",\n \"def test_get_data_fail(self):\\n self.assertIsNone(get_data('this_must_fail', 5, 0))\",\n \"def test_shared_wires(self):\\n wires = range(2)\\n estimation_wires = range(1, 3)\\n\\n with pytest.raises(ValueError, match=\\\"No wires can be shared between the wires\\\"):\\n quantum_monte_carlo(\\n lambda: None, wires=wires, target_wire=0, estimation_wires=estimation_wires\\n )\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_input_sanity():\\n energy = MagicMock()\\n\\n with raises(NotImplementedError) as exception:\\n MonteCarlo(sum, [1, 1, 1], 0e0)\\n with raises(ValueError) as exception:\\n MonteCarlo(energy, [1, 1, 1], temperature=-1e0)\\n\\n with raises(TypeError) as exception:\\n MonteCarlo(energy, [1.0, 2, 3])\\n with raises(ValueError) as exception:\\n MonteCarlo(energy, [-1, 2, 3])\\n with raises(ValueError) as exception:\\n MonteCarlo(energy, [[1, 2, 3], [3, 4, 5]])\\n with raises(ValueError) as exception:\\n MonteCarlo(energy, [3])\\n with raises(ValueError) as exception:\\n MonteCarlo(energy, [0, 0])\",\n \"def test_residue_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for residue in mol_res_spin.residue_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_validation_correct_molecules():\\n paths = examples_paths()\\n molecules = [\\n {'name': 'toluene', 'leap': {'parameters': 'leaprc.gaff'}},\\n {'name': 'toluene', 'leap': {'parameters': ['leaprc.gaff', 'toluene.frcmod']}},\\n {'name': 'p-xylene', 'antechamber': {'charge_method': 'bcc'}},\\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'},\\n 'antechamber': {'charge_method': None}},\\n {'name': 'p-xylene', 'antechamber': {'charge_method': 'bcc'},\\n 'epik': {'ph': 7.6, 'ph_tolerance': 0.7, 'tautomerize': False, 'select': 0}},\\n {'smiles': 'Cc1ccccc1', 'openeye': {'quacpac': 'am1-bcc'},\\n 'antechamber': {'charge_method': None}, 'epik': {'select': 1}},\\n\\n {'filepath': paths['abl']},\\n {'filepath': paths['abl'], 'leap': {'parameters': 'leaprc.ff99SBildn'}},\\n {'filepath': paths['abl'], 'leap': {'parameters': 'leaprc.ff99SBildn'}, 'select': 1},\\n {'filepath': paths['abl'], 'select': 'all'},\\n {'filepath': paths['abl'], 'select': 'all', 'strip_protons': True},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {}},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'add_missing_residues': True}},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'add_missing_atoms': 'all', 'ph': '8.0'}},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'remove_heterogens': 'all'}},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'replace_nonstandard_residues': True}},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'apply_mutations': {'chain_id': 'A', 'mutations': 'T85I'}}},\\n {'filepath': paths['abl'], 'select': 'all', 'modeller': {'apply_mutations': {'chain_id': 'A', 'mutations': 'T85I'}}},\\n {'filepath': paths['abl'], 'select': 'all', 'modeller': {'apply_mutations': {'chain_id': 'A', 'mutations': 'WT'}}},\\n {'filepath': paths['abl'], 'select': 'all', 'pdbfixer': {'apply_mutations': {'chain_id': 'A', 'mutations': 'I8A/T9A'}}},\\n {'filepath': paths['toluene'], 'leap': {'parameters': 'leaprc.gaff'}},\\n {'filepath': paths['benzene'], 'epik': {'select': 1, 'tautomerize': False}},\\n # Regions tests, make sure all other combos still work\\n {'name': 'toluene', 'regions': {'a_region': 4}},\\n {'name': 'toluene', 'regions': {'a_region': 'dsl string'}},\\n {'name': 'toluene', 'regions': {'a_region': [0, 2, 3]}},\\n {'name': 'toluene', 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}},\\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': 4}},\\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': 'dsl string'}},\\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': [0, 2, 3]}},\\n {'smiles': 'Cc1ccccc1', 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}},\\n {'filepath': paths['abl'], 'regions': {'a_region': 4}},\\n {'filepath': paths['abl'], 'regions': {'a_region': 'dsl string'}},\\n {'filepath': paths['abl'], 'regions': {'a_region': [0, 2, 3]}},\\n {'filepath': paths['abl'], 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}},\\n {'filepath': paths['toluene'], 'regions': {'a_region': 4}},\\n {'filepath': paths['toluene'], 'regions': {'a_region': 'dsl string'}},\\n {'filepath': paths['toluene'], 'regions': {'a_region': [0, 2, 3]}},\\n {'filepath': paths['toluene'], 'regions': {'a_region': [0, 2, 3], 'another_region': [5, 4, 3]}}\\n ]\\n for molecule in molecules:\\n yield ExperimentBuilder._validate_molecules, {'mol': molecule}\",\n \"def test_to_from_rdkit(self, molecule):\\n # import pickle\\n from openforcefield.utils.toolkits import UndefinedStereochemistryError\\n\\n undefined_stereo = molecule.name in rdkit_drugbank_undefined_stereo_mols\\n\\n toolkit_wrapper = RDKitToolkitWrapper()\\n\\n rdmol = molecule.to_rdkit()\\n molecule_smiles = molecule.to_smiles(toolkit_registry=toolkit_wrapper)\\n\\n # First test making a molecule using the Molecule(oemol) method\\n\\n # If this is a known failure, check that it raises UndefinedStereochemistryError\\n # and proceed with the test ignoring it.\\n test_mol = None\\n if undefined_stereo:\\n with pytest.raises(UndefinedStereochemistryError):\\n Molecule(rdmol)\\n test_mol = Molecule(rdmol, allow_undefined_stereo=True)\\n else:\\n test_mol = Molecule(rdmol)\\n\\n test_mol_smiles = test_mol.to_smiles(toolkit_registry=toolkit_wrapper)\\n assert molecule_smiles == test_mol_smiles\\n\\n # Check that the two topologies are isomorphic.\\n assert_molecule_is_equal(\\n molecule, test_mol, \\\"Molecule.to_rdkit()/Molecule(rdmol) round trip failed\\\"\\n )\\n\\n # Second, test making a molecule using the Molecule.from_openeye(oemol) method\\n\\n # If this is a known failure, check that it raises UndefinedStereochemistryError\\n # and proceed with the test.\\n if undefined_stereo:\\n with pytest.raises(UndefinedStereochemistryError):\\n Molecule.from_rdkit(rdmol)\\n test_mol = Molecule.from_rdkit(rdmol, allow_undefined_stereo=True)\\n else:\\n test_mol = Molecule.from_rdkit(rdmol)\\n\\n test_mol_smiles = test_mol.to_smiles(toolkit_registry=toolkit_wrapper)\\n assert molecule_smiles == test_mol_smiles\\n\\n # Check that the two topologies are isomorphic.\\n assert_molecule_is_equal(\\n molecule, test_mol, \\\"Molecule.to_rdkit()/from_rdkit() round trip failed\\\"\\n )\",\n \"def test_run_molecule_not_selected(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n processor = dssp.AnnotateResidues(\\n \\\"test\\\", sequence, molecule_selector=lambda mol: False\\n )\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert vermouth.utils.are_all_equal(found)\\n assert found[0] is None\",\n \"def validate_molecules(molecules):\\n # The input should be a Design Group, a Molecule, or a list of Molecules. If\\n # it is a Design Group, get the group number. Make sure the final result is\\n # iterable and each entry is a Molecule\\n error = False\\n gn = None\\n # molecules can be one of three things: a DesignGroup\\n if isinstance(molecules, MOLECULES.DesignGroup):\\n gn = molecules.number\\n # A Molecule\\n elif isinstance(molecules, MOLECULES.Molecule):\\n molecules = [molecules]\\n # Or a list of Molecules\\n elif isinstance(molecules, list) and len(molecules) > 0:\\n for obj in molecules:\\n if not isinstance(obj, MOLECULES.Molecule):\\n error = True\\n break\\n else:\\n error = True\\n # If molecules is not one of those three things\\n if error:\\n text = \\\"The functions in the CHARMM module will work with either a \\\"\\n text +=\\\"Design Group, Molecule, or list of Molecules as input, but not:\\\"\\n text += \\\"\\\\n\\\" + str(molecules)\\n raise CHARMM_Error(text)\\n # Make sure that all Molecules use the CHARMM force field and the identified\\n # file format, and that each Molecule has a unique name\\n names = []\\n for molecule in molecules:\\n # Check that it uses CHARMM\\n if molecule.forceField != \\\"CHARMM\\\":\\n text = \\\"All Molecules used by a function in the CHARMM module must \\\"\\n text += \\\"use the CHARMM force field.\\\"\\n raise CHARMM_Error(text)\\n # And they have a consistent file format\\n elif molecule.fileFormat != molecules[0].fileFormat:\\n text = \\\"All Molecules used by a function in the CHARMM module must \\\"\\n text += \\\"use the same file format.\\\"\\n raise CHARMM_Error(text)\\n # And that it has a unique name\\n elif molecule.name in names:\\n text = \\\"All Molecules used by a function in the CHARMM module must \\\"\\n text += \\\"have a unique name.\\\"\\n raise CHARMM_Error(text)\\n # Otherwise store the Molecule's name\\n else:\\n names.append(molecule.name)\\n # Return the pointer to the molecules, the identified group number, and the\\n # file format\\n return molecules, gn\",\n \"def test_to_from_rdkit(self, molecule):\\n # import pickle\\n from openff.toolkit.utils.toolkits import UndefinedStereochemistryError\\n\\n undefined_stereo = molecule.name in rdkit_drugbank_undefined_stereo_mols\\n\\n toolkit_wrapper = RDKitToolkitWrapper()\\n\\n rdmol = molecule.to_rdkit()\\n molecule_smiles = molecule.to_smiles(toolkit_registry=toolkit_wrapper)\\n\\n # First test making a molecule using the Molecule(oemol) method\\n\\n # If this is a known failure, check that it raises UndefinedStereochemistryError\\n # and proceed with the test ignoring it.\\n test_mol = None\\n if undefined_stereo:\\n with pytest.raises(UndefinedStereochemistryError):\\n Molecule(rdmol)\\n test_mol = Molecule(rdmol, allow_undefined_stereo=True)\\n else:\\n test_mol = Molecule(rdmol)\\n\\n test_mol_smiles = test_mol.to_smiles(toolkit_registry=toolkit_wrapper)\\n assert molecule_smiles == test_mol_smiles\\n\\n # Check that the two topologies are isomorphic.\\n assert_molecule_is_equal(\\n molecule, test_mol, \\\"Molecule.to_rdkit()/Molecule(rdmol) round trip failed\\\"\\n )\\n\\n # Second, test making a molecule using the Molecule.from_openeye(oemol) method\\n\\n # If this is a known failure, check that it raises UndefinedStereochemistryError\\n # and proceed with the test.\\n if undefined_stereo:\\n with pytest.raises(UndefinedStereochemistryError):\\n Molecule.from_rdkit(rdmol)\\n test_mol = Molecule.from_rdkit(rdmol, allow_undefined_stereo=True)\\n else:\\n test_mol = Molecule.from_rdkit(rdmol)\\n\\n test_mol_smiles = test_mol.to_smiles(toolkit_registry=toolkit_wrapper)\\n assert molecule_smiles == test_mol_smiles\\n\\n # Check that the two topologies are isomorphic.\\n assert_molecule_is_equal(\\n molecule, test_mol, \\\"Molecule.to_rdkit()/from_rdkit() round trip failed\\\"\\n )\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_single_molecule(self, single_mol_system, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def test_read_fail2(self):\\n mod_fn = os.path.join(tests.TEST_DATA_PATH, 'segmentations', 'test_bad_data2.mod')\\n with self.assertRaises(ValueError):\\n modreader.get_data(mod_fn) # missing 'IEOF' end\",\n \"def test_qcschema_round_trip_raise_error(self):\\n\\n # get a molecule qcschema\\n import qcportal as ptl\\n\\n client = ptl.FractalClient()\\n ds = client.get_collection(\\n \\\"TorsionDriveDataset\\\", \\\"OpenFF-benchmark-ligand-fragments-v1.0\\\"\\n )\\n # grab an entry from the torsiondrive data set\\n entry = ds.get_entry(\\n \\\"[H]c1[c:1]([c:2](c(c(c1[H])N([H])C(=O)[H])[H])[C:3]2=C(C(=C([S:4]2)[H])OC([H])([H])[H])Br)[H]\\\"\\n )\\n del entry.attributes[\\\"canonical_isomeric_explicit_hydrogen_mapped_smiles\\\"]\\n # now make the molecule from the record instance with the geometry\\n with pytest.raises(KeyError):\\n Molecule.from_qcschema(entry, client)\",\n \"def test_get_placement_w_exception(self, mock__get_nslcmop,\\n mock__get_nsd,\\n mock__get_vim_accounts,\\n mock_create_ns_placement_data,\\n mock_do_placement_computation):\\n server = self.serverSetup()\\n\\n server.msgBus.aiowrite = _async_mock()\\n mock__get_nsd.return_value = nsd_from_db\\n mock__get_nsd.side_effect = RuntimeError('kaboom!')\\n mock__get_vim_accounts.return_value = list_of_vims\\n mock_do_placement_computation.return_value = \\\\\\n [{'vimAccountId': 'bbbbbbbb-38f5-438d-b8ee-3f93b3531f87', 'member-vnf-index': '1'},\\n {'vimAccountId': 'aaaaaaaa-38f5-438d-b8ee-3f93b3531f87', 'member-vnf-index': '2'},\\n {'vimAccountId': 'aaaaaaaa-38f5-438d-b8ee-3f93b3531f87', 'member-vnf-index': '3'}]\\n\\n _run(server.get_placement(nslcmop_record_w_pinning['id']))\\n self.assertTrue(server.msgBus.aiowrite.mock.called)\\n args, kwargs = server.msgBus.aiowrite.mock.call_args\\n rsp_payload = args[2]\\n expected_keys = {'placement'}\\n self.assertEqual(expected_keys, set(rsp_payload.keys()), \\\"placement response missing keys\\\")\\n self.assertIs(type(rsp_payload['placement']['vnf']), list, 'vnf not a list')\\n self.assertEqual([], rsp_payload['placement']['vnf'], 'vnf list not empty')\\n self.assertEqual(nslcmop_record_w_pinning['id'], rsp_payload['placement']['nslcmopId'], \\\"nslcmopId invalid\\\")\",\n \"def test_exception_list_empty(self):\\n complex_id_list = range(1,4) #1~3\\n dataloader = lambda d: d\\n calc_func = lambda d1,d2: d1 + d2\\n \\n _, actual = complex_pairwise_calc(complex_id_list, dataloader, calc_func, symmetry=False)\\n expected = []\\n\\n self.assertEqual(actual, expected)\",\n \"def test_check_cluster1():\\n with pytest.raises(AssertionError) as err_info:\\n Check_BuoyDC.check_cluster(cluster_fail_1)\\n assert str(err_info.value) == 'cluster type input not within range of index'\",\n \"def setUp(self):\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Name the first molecule.\\n cdp.mol[0].name = 'Ap4Aase'\\n\\n # Add a second molecule to the system.\\n cdp.mol.add_item(mol_name='RNA')\\n\\n # Add two more residues to the first molecule (and set the residue number of the first).\\n cdp.mol[0].res[0].num = 1\\n cdp.mol[0].res.add_item(res_num=2, res_name='Glu')\\n cdp.mol[0].res.add_item(res_num=4, res_name='Pro')\\n\\n # Add some spin info to this molecule.\\n cdp.mol[0].res[0].spin[0].name = 'NH'\\n cdp.mol[0].res[0].spin[0].num = 60\\n cdp.mol[0].res[1].spin[0].name = 'NH'\\n cdp.mol[0].res[1].spin[0].num = 63\\n\\n # Add one more residue to the second molecule (and set the residue number of the first).\\n cdp.mol[1].res[0].num = -5\\n cdp.mol[1].res.add_item(res_num=-4)\\n\\n # Add a second set of spins to the second molecule (naming the first set first).\\n cdp.mol[1].res[0].spin[0].name = 'C8'\\n cdp.mol[1].res[1].spin[0].name = 'C8'\\n cdp.mol[1].res[0].spin.add_item(spin_name='N5')\\n cdp.mol[1].res[1].spin.add_item(spin_name='N5')\\n cdp.mol[1].res[1].spin.add_item(spin_name='2H', spin_num=132)\\n\\n # Deselect a number of spins.\\n cdp.mol[0].res[0].spin[0].select = 0\\n cdp.mol[0].res[2].spin[0].select = 0\\n cdp.mol[1].res[0].spin[0].select = 0\\n cdp.mol[1].res[1].spin[1].select = 0\\n\\n # Update the metadata.\\n mol_res_spin.metadata_update()\",\n \"def test_xyzp_qm_7b():\\n subject = subject7\\n\\n with pytest.raises(qcelemental.MoleculeFormatError):\\n final, intermed = qcelemental.molparse.from_string(subject, return_processed=True, dtype='xyz')\",\n \"def test_wrong_len(mocker: MockFixture, tmp_path: Path):\\n df = read_molecules(PATH_TEST / \\\"smiles_carboxylic.csv\\\")\\n opts = create_options(tmp_path)\\n\\n mocked_df = pd.DataFrame.from_dict({'ligand': ['CO', 'CC'], 'V_bulk': [1, 2]})\\n mocker.patch(\\n \\\"flamingo.cat_interface.compute_property_using_cat\\\", return_value=mocked_df)\\n\\n data = compute_batch_bulkiness(df.smiles, opts, pd.Index(list(range(4))))\\n\\n assert np.all(np.isnan(data))\",\n \"def test_molecule_from_pdb_error_non_canonical_aa(self):\\n with pytest.raises(\\n UnassignedChemistryInPDBError,\\n match=(\\n r\\\"The following residue names with unassigned atoms were \\\"\\n + r\\\"not found in the substructure library. While the OpenFF \\\"\\n + r\\\"Toolkit identifies residues by matching chemical \\\"\\n + r\\\"substructures rather than by residue name, it currently \\\"\\n + r\\\"only supports the 20 'canonical' amino acids\\\\.\\\\n\\\\s*DYE\\\"\\n ),\\n ):\\n Molecule.from_polymer_pdb(\\n get_data_file_path(\\\"proteins/fluoresceine_dyed_helix_capped.pdb\\\")\\n )\",\n \"def test_exception_result(self):\\n raiser = self.make_wrapped_function()\\n self.assertRaises(ZeroDivisionError, raiser, ZeroDivisionError())\",\n \"def test_set_molecule(self):\\n mol = Molecule.from_smiles(\\\"CCO\\\")\\n atom = Atom(6, 0, False)\\n atom.molecule = mol\",\n \"def test_spin_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the spins.\\n i = 0\\n for spin in mol_res_spin.spin_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_exception_list_nonempty(self):\\n complex_id_list = map(float, range(0,3)) #0.0 ~ 2.0\\n dataloader = lambda d: d\\n calc_func = lambda d1,d2: d1 / d2 #DivisionByZeroError\\n \\n actual_result, actual_exception = complex_pairwise_calc(complex_id_list, dataloader, calc_func, symmetry=False)\\n expected_exception = [(1,0),(2,0),(0,0)]\\n expected_result = [(0.0, 1.0, 0.0), (0.0, 2.0, 0.0), (1.0, 2.0, 0.5), (2.0, 1.0, 2.0), (1.0, 1.0, 1.0), (2.0, 2.0, 1.0)]\\n \\n self.assertEqual(actual_result, expected_result)\\n self.assertEqual(actual_exception, expected_exception)\",\n \"def test_get_center_invalid_errors(syn):\\n with patch.object(\\n syn, \\\"tableQuery\\\", return_value=QueryResponse\\n ) as patch_query, patch.object(\\n write_invalid_reasons, \\\"_combine_center_file_errors\\\", return_value=\\\"errors\\\"\\n ) as patch_combine:\\n center_invalid = write_invalid_reasons.get_center_invalid_errors(syn, \\\"syn3333\\\")\\n assert center_invalid == {\\\"SAGE\\\": \\\"errors\\\", \\\"TEST\\\": \\\"errors\\\"}\\n patch_query.assert_called_once_with(\\\"SELECT * FROM syn3333\\\")\\n assert patch_combine.call_count == 2\",\n \"def test_nothing_perceived_dipeptide(self):\\n from openff.toolkit._tests.create_molecules import dipeptide as create_dipeptide\\n\\n dipeptide = create_dipeptide()\\n\\n with pytest.raises(KeyError):\\n assert dipeptide.atoms[0].metadata[\\\"residue_name\\\"] is None\\n with pytest.raises(KeyError):\\n assert \\\"ALA\\\" == dipeptide.atoms[10].metadata[\\\"residue_name\\\"]\\n with pytest.raises(KeyError):\\n assert 1 == dipeptide.atoms[10].metadata[\\\"residue_number\\\"]\\n with pytest.raises(KeyError):\\n assert \\\" \\\" == dipeptide.atoms[10].metadata[\\\"insertion_code\\\"]\\n with pytest.raises(AttributeError):\\n dipeptide.residues[0]\",\n \"def test_exceptions_optimal_sector(symbols, geometry, generators, num_electrons, msg_match):\\n mol = qml.qchem.Molecule(symbols, geometry)\\n hamiltonian = qml.qchem.diff_hamiltonian(mol)()\\n\\n with pytest.raises(ValueError, match=msg_match):\\n optimal_sector(hamiltonian, generators, num_electrons)\",\n \"def test_verify_mol_input():\\n # good input with extra spaces\\n mol_input_dict = read_mol_input(os.path.join(TEST_DIR, \\\"example2_mol_input_file.txt\\\"))\\n verify_mol_input(mol_input_dict)\\n\\n # check the good file\\n # {'qcm': 'hf', 'basis': 'sto-3g', 'struct_input': 'C=CC=C',\\n # 'struct_type': 'smiles', 'prog': 'psi4', 'charge': '0', 'multip': '1'}\\n mol_input_dict = read_mol_input(os.path.join(TEST_DIR, \\\"example_mol_input_file.txt\\\"))\\n verify_mol_input(mol_input_dict)\\n # reset all params that are modified by verification\\n mol_input_dict[\\\"charge\\\"] = '0'\\n mol_input_dict[\\\"multip\\\"] = '1'\\n\\n # struct input is spelt wrong\\n mol_input_dict2 = read_mol_input(os.path.join(TEST_DIR, \\\"bad3_mol_input_file.txt\\\"))\\n assert_raises(ValueError, verify_mol_input, mol_input_dict2)\\n\\n mol_input_dict[\\\"qcm\\\"] = \\\"not-a-method\\\"\\n assert_raises(ValueError, verify_mol_input, mol_input_dict)\\n mol_input_dict[\\\"qcm\\\"] = \\\"hf\\\"\\n # reset all params that are modified by verification\\n mol_input_dict[\\\"charge\\\"] = '0'\\n mol_input_dict[\\\"multip\\\"] = '1'\\n\\n mol_input_dict[\\\"basis\\\"] = \\\"not-a-basis\\\"\\n assert_raises(ValueError, verify_mol_input, mol_input_dict)\\n mol_input_dict[\\\"basis\\\"] = \\\"sto-3g\\\"\\n # reset all params that are modified by verification\\n mol_input_dict[\\\"charge\\\"] = '0'\\n mol_input_dict[\\\"multip\\\"] = '1'\\n\\n mol_input_dict[\\\"struct_input\\\"] = \\\"very-bad-smiles-string\\\"\\n assert_raises(ValueError, verify_mol_input, mol_input_dict)\\n mol_input_dict[\\\"struct_input\\\"] = \\\"C=CC=C\\\"\\n # reset all params that are modified by verification\\n mol_input_dict[\\\"charge\\\"] = '0'\\n mol_input_dict[\\\"multip\\\"] = '1'\\n\\n mol_input_dict[\\\"struct_type\\\"] = \\\"not-an-option\\\"\\n assert_raises(AssertionError, verify_mol_input, mol_input_dict)\\n mol_input_dict[\\\"struct_type\\\"] = \\\"smiles\\\"\\n # reset all params that are modified by verification\\n mol_input_dict[\\\"charge\\\"] = '0'\\n mol_input_dict[\\\"multip\\\"] = '1'\\n\\n mol_input_dict[\\\"prog\\\"] = \\\"unavailable-prog\\\"\\n assert_raises(AssertionError, verify_mol_input, mol_input_dict)\\n mol_input_dict[\\\"prog\\\"] = \\\"psi4\\\"\\n # reset all params that are modified by verification\\n mol_input_dict[\\\"charge\\\"] = '0'\\n mol_input_dict[\\\"multip\\\"] = '1'\\n\\n mol_input_dict[\\\"charge\\\"] = \\\"0.34\\\"\\n assert_raises(ValueError, verify_mol_input, mol_input_dict)\\n mol_input_dict[\\\"charge\\\"] = \\\"0\\\"\\n # reset all params that are modified by verification\\n mol_input_dict[\\\"multip\\\"] = '1'\\n\\n mol_input_dict[\\\"multip\\\"] = \\\"-2\\\"\\n assert_raises(AssertionError, verify_mol_input, mol_input_dict)\",\n \"def test_result(self):\\n result = compute()\\n self.assertEqual(result, '4782')\\n print(\\\"eulpy25Test passed\\\")\",\n \"def exception_catcher(func):\\n\\n @wraps(func)\\n def wrapper(*args, **kwargs):\\n\\n try:\\n return func(*args, **kwargs)\\n\\n except Exception as exc:\\n if len(args) >= 1 and hasattr(args[0], 'molecule'):\\n if hasattr(args[0].molecule, 'bulk_run'):\\n if not args[0].molecule.bulk_run:\\n raise\\n else:\\n raise\\n\\n print(exc)\\n\\n return wrapper\",\n \"def test_get_thermo_data_mopac(self):\\n output_directory = os.path.join(self.mop1.settings.fileStore, '..', '..')\\n self.mop1.set_default_output_directory(output_directory)\\n self.mop2.set_default_output_directory(output_directory)\\n self.mop3.set_default_output_directory(output_directory)\\n\\n mol = Molecule().from_smiles('C1=CC=C2C=CC=CC2=C1')\\n\\n for directory in (self.mop1.settings.fileStore, self.mop1.settings.scratchDirectory):\\n shutil.rmtree(directory, ignore_errors=True)\\n\\n for directory in (self.mop2.settings.fileStore, self.mop2.settings.scratchDirectory):\\n shutil.rmtree(directory, ignore_errors=True)\\n\\n for directory in (self.mop3.settings.fileStore, self.mop3.settings.scratchDirectory):\\n shutil.rmtree(directory, ignore_errors=True)\\n\\n thermo1 = self.mop1.get_thermo_data(mol)\\n thermo2 = self.mop2.get_thermo_data(mol)\\n thermo3 = self.mop3.get_thermo_data(mol)\\n\\n self.assertTrue(thermo1.comment.startswith('QM MopacMolPM3'))\\n self.assertTrue(thermo2.comment.startswith('QM MopacMolPM6'))\\n self.assertTrue(thermo3.comment.startswith('QM MopacMolPM7'))\\n\\n self.assertAlmostEqual(thermo1.H298.value_si, 169708.0608, 1) # to 1 decimal place\\n self.assertAlmostEqual(thermo1.S298.value_si, 334.5007584, 1) # to 1 decimal place\\n self.assertAlmostEqual(thermo2.H298.value_si, 167704.4270, 1) # to 1 decimal place\\n self.assertAlmostEqual(thermo2.S298.value_si, 338.0999241, 1) # to 1 decimal place\\n self.assertAlmostEqual(thermo3.H298.value_si, 166168.8571, 1) # to 1 decimal place\\n self.assertAlmostEqual(thermo3.S298.value_si, 336.3330406, 1) # to 1 decimal place\",\n \"def _get_components(\\n design_unit: oechem.OEDesignUnit\\n ) -> Tuple[oechem.OEGraphMol(), oechem.OEGraphMol(), oechem.OEGraphMol()]:\\n from openeye import oechem\\n\\n protein, solvent, ligand = oechem.OEGraphMol(), oechem.OEGraphMol(), oechem.OEGraphMol()\\n\\n logging.debug(\\\"Extracting molecular components ...\\\")\\n design_unit.GetProtein(protein)\\n design_unit.GetSolvent(solvent)\\n design_unit.GetLigand(ligand)\\n\\n # delete protein atoms with no name (found in prepared protein of 4ll0)\\n for atom in protein.GetAtoms():\\n if not atom.GetName().strip():\\n logging.debug(\\\"Deleting unknown atom ...\\\")\\n protein.DeleteAtom(atom)\\n\\n # perceive residues to remove artifacts of other design units in the sequence of the protein\\n # preserve certain properties to assure correct behavior of the pipeline,\\n # e.g. deletion of chains in OEKLIFSKinaseApoFeaturizer._process_kinase_domain method\\n preserved_info = (\\n oechem.OEPreserveResInfo_ResidueNumber\\n | oechem.OEPreserveResInfo_ResidueName\\n | oechem.OEPreserveResInfo_AtomName\\n | oechem.OEPreserveResInfo_ChainID\\n | oechem.OEPreserveResInfo_HetAtom\\n | oechem.OEPreserveResInfo_InsertCode\\n | oechem.OEPreserveResInfo_AlternateLocation\\n )\\n oechem.OEPerceiveResidues(protein, preserved_info)\\n oechem.OEPerceiveResidues(solvent, preserved_info)\\n oechem.OEPerceiveResidues(ligand)\\n\\n logging.debug(\\n \\\"Number of component atoms: \\\" +\\n f\\\"Protein - {protein.NumAtoms()}, \\\" +\\n f\\\"Solvent - {solvent.NumAtoms()}, \\\" +\\n f\\\"Ligand - {ligand.NumAtoms()}.\\\"\\n )\\n return protein, solvent, ligand\",\n \"def failure(self, result):\\r\\n raise NotImplementedError\",\n \"def test():\\r\\n\\tassert calcolatrice.__author__ == \\\"help@castellanidavide.it\\\", \\\"sanity test failed\\\"\\r\\n\\t#assert calcolatrice.<function>(<values>) == <the result(s) you would like to have>, \\\"<the fail message>\\\"\\r\",\n \"def test_spin_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for spin in mol_res_spin.spin_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def test_deferred_failure_result(self):\\n passthrough = self.make_wrapped_function()\\n self.assertRaises(\\n ZeroDivisionError, passthrough, fail(ZeroDivisionError()))\",\n \"def testNoOutputCausesFailure(self):\\n self._get_mock.return_value = (set(['foo_ci']), False)\\n with self.assertRaises(RuntimeError):\\n builders.GetTryBuilders(['foo_ci'])\",\n \"def test_from_qcschema_no_client(self):\\n\\n import json\\n\\n # As the method can take a record instance or a dict with JSON encoding test both\\n # test incomplete dict\\n example_dict = {\\\"name\\\": \\\"CH4\\\"}\\n with pytest.raises(KeyError):\\n mol = Molecule.from_qcschema(example_dict)\\n\\n # test an object that is not a record\\n wrong_object = \\\"CH4\\\"\\n with pytest.raises(AttributeError):\\n mol = Molecule.from_qcschema(wrong_object)\\n\\n with open(get_data_file_path(\\\"molecules/qcportal_molecules.json\\\")) as json_file:\\n # test loading the dict representation from a json file\\n json_mol = json.load(json_file)\\n mol = Molecule.from_qcschema(json_mol)\\n # now make a molecule from the canonical smiles and make sure they are isomorphic\\n can_mol = Molecule.from_smiles(\\n json_mol[\\\"attributes\\\"][\\\"canonical_isomeric_smiles\\\"]\\n )\\n assert mol.is_isomorphic_with(can_mol) is True\",\n \"def test_from_qcschema_no_client(self):\\n\\n import json\\n\\n # As the method can take a record instance or a dict with JSON encoding test both\\n # test incomplete dict\\n example_dict = {\\\"name\\\": \\\"CH4\\\"}\\n with pytest.raises(KeyError):\\n mol = Molecule.from_qcschema(example_dict)\\n\\n # test an object that is not a record\\n wrong_object = \\\"CH4\\\"\\n with pytest.raises(AttributeError):\\n mol = Molecule.from_qcschema(wrong_object)\\n\\n with open(get_data_file_path(\\\"molecules/qcportal_molecules.json\\\")) as json_file:\\n # test loading the dict representation from a json file\\n json_mol = json.load(json_file)\\n mol = Molecule.from_qcschema(json_mol)\\n # now make a molecule from the canonical smiles and make sure they are isomorphic\\n can_mol = Molecule.from_smiles(\\n json_mol[\\\"attributes\\\"][\\\"canonical_isomeric_smiles\\\"]\\n )\\n assert mol.is_isomorphic_with(can_mol) is True\",\n \"def test_operator_with_invalid_wire(self, monkeypatch, test_batch_result):\\n dev = QeQiskitDevice(\\n wires=[\\\"a\\\", \\\"b\\\", \\\"c\\\"], shots=1000, backend=\\\"qasm_simulator\\\", analytic=False\\n )\\n\\n with monkeypatch.context() as m:\\n m.setattr(pennylane_orquestra.cli_actions, \\\"user_data_dir\\\", lambda *args: tmpdir)\\n\\n # Disable submitting to the Orquestra platform by mocking Popen\\n m.setattr(subprocess, \\\"Popen\\\", lambda *args, **kwargs: MockPopen())\\n m.setattr(\\n pennylane_orquestra.orquestra_device,\\n \\\"loop_until_finished\\\",\\n lambda *args, **kwargs: test_batch_result,\\n )\\n\\n @qml.qnode(dev)\\n def circuit():\\n return qml.expval(qml.PauliZ(0))\\n\\n with pytest.raises(\\n qml.qnodes.base.QuantumFunctionError,\\n match=\\\"Operation PauliZ applied to invalid wire\\\",\\n ):\\n circuit()\",\n \"def test_library_charges_dont_parameterize_molecule_because_of_incomplete_coverage(\\n self,\\n ):\\n molecules = [Molecule.from_file(get_data_file_path(\\\"molecules/toluene.sdf\\\"))]\\n top = Topology.from_molecules(molecules)\\n\\n # The library charges in the FF should not be able to fully cover toluene\\n ff = ForceField(\\n get_data_file_path(\\\"test_forcefields/test_forcefield.offxml\\\"),\\n xml_ethanol_library_charges_by_atom_ff,\\n )\\n # Delete the ToolkitAM1BCCHandler so the molecule won't get charges from anywhere\\n del ff._parameter_handlers[\\\"ToolkitAM1BCC\\\"]\\n with pytest.raises(\\n RuntimeError, match=\\\"Cc1ccccc1 could not be fully assigned charges\\\"\\n ):\\n omm_system = ff.create_openmm_system(top)\\n\\n # If we do NOT delete the ToolkiAM1BCCHandler, then toluene should be assigned some nonzero partial charges.\\n # The exact value will vary by toolkit, so we don't test that here.\\n ff = ForceField(\\n get_data_file_path(\\\"test_forcefields/test_forcefield.offxml\\\"),\\n xml_ethanol_library_charges_by_atom_ff,\\n )\\n omm_system = ff.create_openmm_system(top)\\n nonbondedForce = [\\n f for f in omm_system.getForces() if type(f) == NonbondedForce\\n ][0]\\n for particle_index in range(top.n_atoms):\\n q, _, _ = nonbondedForce.getParticleParameters(particle_index)\\n assert q != 0 * unit.elementary_charge\",\n \"def test_errors_on_metadata(self):\\n mb = self.maria_backup\\n\\n # correct run\\n sample_xtrabackup_info = \\\"\\\"\\\"\\n uuid = a6336c86-1b33-11e8-8de6-080027f3a5d8\\n tool_name = xtrabackup\\n tool_command = –backup –target-dir=/Backups/base –datadir=/var/lib/mysql –user=root –password=… –galera-info\\n tool_version = 2.4.9\\n ibbackup_version = 2.4.9\\n server_version = 5.7.19-17-57-log\\n start_time = 2022-02-26 15:28:22\\n end_time = 2022-02-26 15:28:48\\n \\\"\\\"\\\"\\n mock = mock_open(read_data=sample_xtrabackup_info)\\n with patch('builtins.open', mock):\\n self.assertFalse(mb.errors_on_metadata(''))\\n\\n # missing end_time\\n sample_xtrabackup_info = \\\"\\\"\\\"\\n uuid = a6336c86-1b33-11e8-8de6-080027f3a5d8\\n tool_name = xtrabackup\\n tool_command = –backup –target-dir=/Backups/base –datadir=/var/lib/mysql –user=root –password=… –galera-info\\n tool_version = 2.4.9\\n ibbackup_version = 2.4.9\\n server_version = 5.7.19-17-57-log\\n start_time = 2022-02-26 15:28:22\\n \\\"\\\"\\\"\\n mock = mock_open(read_data=sample_xtrabackup_info)\\n with patch('builtins.open', mock):\\n self.assertTrue(mb.errors_on_metadata(''))\\n\\n # simulate open error\\n mock = mock_open(read_data=\\\"\\\")\\n with patch('builtins.open', mock) as mocked_open:\\n mocked_open.side_effect = OSError\\n self.assertTrue(mb.errors_on_metadata(''))\\n\\n # simulate read error\\n mock = mock_open(read_data=\\\"\\\")\\n with patch('builtins.open', mock) as mocked_open:\\n mocked_file = mocked_open.return_value\\n mocked_file.read.side_effect = IOError\\n self.assertTrue(mb.errors_on_metadata(''))\",\n \"def test_wrong_output_provided(self):\\n with self.assertRaises(VisualizationError):\\n circuit_drawer(None, output='wrong_output')\",\n \"def setup_molecule_output_check(exp_builder_db, mol_id, output_path):\\n exp_builder_db._setup_molecules(mol_id)\\n assert os.path.exists(output_path)\\n assert os.path.getsize(output_path) > 0\",\n \"def test_call_incompatible_data(self):\\r\\n self.cs_overview.DistanceMatrices = [self.single_ele_dm,\\r\\n self.single_ele_dm]\\r\\n self.assertRaises(ValueError, self.cs_overview)\",\n \"def test_rsp_invalid(self):\\n\\n def handle(event):\\n ds = Dataset()\\n ds.PatientName = \\\"Test^test\\\"\\n return 0x0000, ds\\n\\n self.ae = ae = AE()\\n ae.acse_timeout = 5\\n ae.dimse_timeout = 0.4\\n ae.network_timeout = 5\\n ae.add_supported_context(ModalityPerformedProcedureStep)\\n scp = ae.start_server(\\n (\\\"localhost\\\", 11112), block=False, evt_handlers=[(evt.EVT_N_SET, handle)]\\n )\\n\\n ae.add_requested_context(ModalityPerformedProcedureStep)\\n assoc = ae.associate(\\\"localhost\\\", 11112)\\n assert assoc.is_established\\n\\n class DummyResponse:\\n is_valid_response = False\\n\\n class DummyDIMSE:\\n msg_queue = queue.Queue()\\n gotten = False\\n\\n def send_msg(*args, **kwargs):\\n return\\n\\n def get_msg(self, *args, **kwargs):\\n if not self.gotten:\\n self.gotten = True\\n return None, DummyResponse()\\n return None, None\\n\\n assoc._reactor_checkpoint.clear()\\n while not assoc._is_paused:\\n time.sleep(0.01)\\n assoc.dimse = DummyDIMSE()\\n mod_list = Dataset()\\n mod_list.PatientName = \\\"Test^test\\\"\\n status, ds = assoc.send_n_set(\\n mod_list, ModalityPerformedProcedureStep, \\\"1.2.840.10008.5.1.1.40.1\\\"\\n )\\n\\n assert status == Dataset()\\n assert ds is None\\n assert assoc.is_aborted\\n\\n scp.shutdown()\",\n \"def test_bad_data(self):\\r\\n # LB180210_3_corrupted.PD0 has three records in it, the 2nd record was corrupted\\r\\n with open(os.path.join(RESOURCE_PATH, 'LB180210_3_corrupted.PD0'), 'rb') as stream_handle:\\r\\n\\r\\n parser = AdcpPd0Parser(self.config_recov, stream_handle, self.exception_callback)\\r\\n\\r\\n # try to get 3 particles, should only get 2 back\\r\\n # the second one should correspond to ensemble 3\\r\\n parser.get_records(3)\\r\\n\\r\\n log.debug('Exceptions : %s', self.exception_callback_value[0])\\r\\n\\r\\n self.assertEqual(len(self.exception_callback_value), 1)\\r\\n self.assert_(isinstance(self.exception_callback_value[0], RecoverableSampleException))\",\n \"def test_synchronize_splits_error(self, mocker):\\n storage = mocker.Mock(spec=SplitStorage)\\n api = mocker.Mock()\\n\\n def run(x, c):\\n raise APIException(\\\"something broke\\\")\\n run._calls = 0\\n api.fetch_splits.side_effect = run\\n storage.get_change_number.return_value = -1\\n\\n from splitio.sync.split import SplitSynchronizer\\n split_synchronizer = SplitSynchronizer(api, storage)\\n\\n with pytest.raises(APIException):\\n split_synchronizer.synchronize_splits(1)\",\n \"def test_get_molecule_least_similar_to(self):\\n csv_fpath = self.smiles_seq_to_xl_or_csv(ftype=\\\"csv\\\")\\n for descriptor in SUPPORTED_FPRINTS:\\n for similarity_measure in SUPPORTED_SIMILARITIES:\\n molecule_set = MoleculeSet(\\n molecule_database_src=csv_fpath,\\n molecule_database_src_type=\\\"csv\\\",\\n fingerprint_type=descriptor,\\n similarity_measure=similarity_measure,\\n is_verbose=False,\\n )\\n for mol_smile, mol in zip(TEST_SMILES,\\n molecule_set.molecule_database):\\n compare_task = CompareTargetMolecule(\\n target_molecule_smiles=mol_smile)\\n [furthest_mol], [similarity] = compare_task.\\\\\\n get_hits_dissimilar_to(molecule_set)\\n mol_similarities = molecule_set.compare_against_molecule(\\n mol)\\n self.assertEqual(\\n np.min(mol_similarities),\\n mol.get_similarity_to(\\n molecule_set.molecule_database[furthest_mol],\\n molecule_set.similarity_measure\\n ),\\n f\\\"Expected furthest mol to have minimum \\\"\\n f\\\"similarity to target molecule \\\"\\n f\\\"using similarity measure: {similarity_measure}, \\\"\\n f\\\"descriptor: {descriptor}, \\\"\\n f\\\"for molecule {mol.mol_text}\\\",\\n )\\n self.assertGreaterEqual(similarity, 0.,\\n \\\"Expected similarity value to \\\"\\n \\\"be >= 0.\\\"\\n f\\\"using similarity measure: \\\"\\n f\\\"{similarity_measure}, \\\"\\n f\\\"descriptor: {descriptor}, \\\"\\n f\\\"for molecule {mol.mol_text}\\\")\\n self.assertLessEqual(similarity, 1.,\\n \\\"Expected similarity value to \\\"\\n \\\"be <= 1.\\\"\\n f\\\"using similarity measure: \\\"\\n f\\\"{similarity_measure}, \\\"\\n f\\\"descriptor: {descriptor}, \\\"\\n f\\\"for molecule {mol.mol_text}\\\"\\n )\",\n \"def test_no_outputs():\\r\\n # test module\\r\\n test_data = doc.MatObject.matlabify('test_data')\\r\\n test_submodule = test_data.getter('test_submodule')\\r\\n ok_(isinstance(test_submodule, doc.MatModule))\\r\\n eq_(test_submodule.__package__, 'test_data.test_submodule')\\r\\n f = test_submodule.getter('f_no_outputs')\\r\\n ok_(isinstance(f, doc.MatFunction))\\r\\n ok_(not f.retv)\\r\\n eq_(f.args, ['arg'])\\r\\n return f\",\n \"def test_block_structure_matrices_on_elements_validity(n_rods):\\n world_rods = [MockRod(np.random.randint(10, 30 + 1)) for _ in range(n_rods)]\\n block_structure = MemoryBlockCosseratRod(\\n world_rods, [i for i in range(len(world_rods))]\\n )\\n\\n for i in range(n_rods):\\n start_idx = block_structure.start_idx_in_rod_elems[i]\\n end_idx = block_structure.end_idx_in_rod_elems[i]\\n\\n # director collection\\n assert np.shares_memory(\\n block_structure.director_collection, world_rods[i].director_collection\\n )\\n assert np.shares_memory(\\n block_structure.matrix_dofs_in_rod_elems, world_rods[i].director_collection\\n )\\n assert_allclose(\\n block_structure.director_collection[..., start_idx:end_idx],\\n world_rods[i].director_collection,\\n )\\n\\n # mass second moment of inertia\\n assert np.shares_memory(\\n block_structure.mass_second_moment_of_inertia,\\n world_rods[i].mass_second_moment_of_inertia,\\n )\\n assert np.shares_memory(\\n block_structure.matrix_dofs_in_rod_elems,\\n world_rods[i].mass_second_moment_of_inertia,\\n )\\n assert_allclose(\\n block_structure.mass_second_moment_of_inertia[..., start_idx:end_idx],\\n world_rods[i].mass_second_moment_of_inertia,\\n )\\n\\n # inv mass second moment of inertia\\n assert np.shares_memory(\\n block_structure.inv_mass_second_moment_of_inertia,\\n world_rods[i].inv_mass_second_moment_of_inertia,\\n )\\n assert np.shares_memory(\\n block_structure.matrix_dofs_in_rod_elems,\\n world_rods[i].inv_mass_second_moment_of_inertia,\\n )\\n assert_allclose(\\n block_structure.inv_mass_second_moment_of_inertia[..., start_idx:end_idx],\\n world_rods[i].inv_mass_second_moment_of_inertia,\\n )\\n\\n # shear matrix\\n assert np.shares_memory(\\n block_structure.shear_matrix, world_rods[i].shear_matrix\\n )\\n assert np.shares_memory(\\n block_structure.matrix_dofs_in_rod_elems, world_rods[i].shear_matrix\\n )\\n assert_allclose(\\n block_structure.shear_matrix[..., start_idx:end_idx],\\n world_rods[i].shear_matrix,\\n )\",\n \"def test_givens_decomposition_exceptions(unitary_matrix, msg_match):\\n\\n with pytest.raises(ValueError, match=msg_match):\\n givens_decomposition(unitary_matrix)\",\n \"def meta_res(simulatedata_cbma, meta, random):\\n _, (_, dataset) = simulatedata_cbma\\n # CHECK IF META/KERNEL WORK TOGETHER\\n ####################################\\n meta_expectation = does_not_raise()\\n\\n with meta_expectation:\\n res = meta.fit(dataset)\\n # if creating the result failed (expected), do not continue\\n if isinstance(meta_expectation, type(pytest.raises(ValueError))):\\n pytest.xfail(\\\"this meta-analysis & kernel combo fails\\\")\\n # instantiate meta-analysis estimator\\n return res\",\n \"def test_rr_bcibad(results):\\n ci1 = results.effect_ci(citype=\\\"Some Unsupported Type\\\")\\n assert np.all(np.isnan(ci1))\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def experiment3():\\n raise FAKE_ERROR\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_main_exit_absent(self, mock_delete_volume, mock_module, mock_client):\\n PARAMS = {\\n 'storage_system_ip': '192.168.0.1',\\n 'storage_system_name': '3PAR',\\n 'storage_system_username': 'USER',\\n 'storage_system_password': 'PASS',\\n 'volume_name': 'test_volume',\\n 'cpg': None,\\n 'size': None,\\n 'size_unit': None,\\n 'snap_cpg': None,\\n 'wait_for_task_to_end': None,\\n 'new_name': None,\\n 'expiration_hours': None,\\n 'retention_hours': None,\\n 'ss_spc_alloc_warning_pct': None,\\n 'ss_spc_alloc_limit_pct': None,\\n 'usr_spc_alloc_warning_pct': None,\\n 'usr_spc_alloc_limit_pct': None,\\n 'rm_ss_spc_alloc_warning': None,\\n 'rm_usr_spc_alloc_warning': None,\\n 'rm_exp_time': None,\\n 'rm_usr_spc_alloc_limit': None,\\n 'rm_ss_spc_alloc_limit': None,\\n 'compression': False,\\n 'type': 'thin',\\n 'keep_vv': None,\\n 'state': 'absent'\\n }\\n # This creates a instance of the AnsibleModule mock.\\n mock_module.params = PARAMS\\n mock_module.return_value = mock_module\\n instance = mock_module.return_value\\n mock_delete_volume.return_value = (True, True, \\\"Deleted volume successfully.\\\", {})\\n hpe3par_volume.main()\\n # AnsibleModule.exit_json should be called\\n instance.exit_json.assert_called_with(\\n changed=True, msg=\\\"Deleted volume successfully.\\\")\\n # AnsibleModule.fail_json should not be called\\n self.assertEqual(instance.fail_json.call_count, 0)\",\n \"def test_call_vmec(self):\\n self.set_up()\\n inputObject = self.vmecOptimization.vmecInputObject\\n inputObject_new = VmecInput(self.input_filename_intersecting)\\n error_code = self.vmecOptimization.call_vmec(inputObject_new)\\n self.assertEqual(error_code,16)\\n \\n # To do : add test for ill-conditioned Jacobian\\n# rbc = np.copy(inputObject.rbc)\\n# zbs = np.copy(inputObject.zbs)\\n# inputObject.rbc[1::] = 1e-4*inputObject.rbc[1::]\\n# inputObject.zbs = inputObject.zbs\\n# error_code = self.vmecOptimization.call_vmec(inputObject)\\n# self.assertEqual(error_code,16)\\n # Reset boundary\\n# inputObject.rbc = rbc\\n# inputObject.zbs = zbs\\n \\n inputObject = VmecInput(self.input_filename)\\n error_code = self.vmecOptimization.call_vmec(inputObject)\\n self.assertEqual(error_code,0)\\n self.tear_down()\",\n \"def test_call(self):\\r\\n args = [\\\"-d \\\" + self.dm_fp + \\\" -m \\\" + self.map_fp +\\r\\n \\\" -c DOB -o \\\" + self.output_dir]\\r\\n\\r\\n rex = RExecutor(TmpDir=self.tmp_dir)\\r\\n results = rex(args, \\\"permdisp.r\\\", self.output_dir)\\r\\n\\r\\n self.files_to_remove.append(join(self.tmp_dir, 'R.stdout'))\\r\\n self.files_to_remove.append(join(self.tmp_dir, 'R.stderr'))\\r\\n\\r\\n # Make sure an output file was created with something in it.\\r\\n results_fp = join(self.output_dir, 'permdisp_results.txt')\\r\\n results_f = open(results_fp, 'U')\\r\\n results = results_f.read()\\r\\n results_f.close()\\r\\n self.files_to_remove.append(results_fp)\\r\\n self.assertTrue(len(results) > 0)\",\n \"def test_bad_statistics():\\n dev = _aws_device(wires=1, foo=\\\"bar\\\")\\n observable = qml.Identity(wires=0, do_queue=False)\\n observable.return_type = None\\n\\n with pytest.raises(QuantumFunctionError, match=\\\"Unsupported return type specified\\\"):\\n dev.statistics(None, [observable])\",\n \"def test_re_split_cell_raises_error(mock_amg):\\n\\n # splitting once should work as normal\\n mock_amg.cells[4].split()\\n\\n with pytest.raises(ValueError):\\n mock_amg.cells[4].split()\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_part_1(arguments, output):\\n # assert part_1.solution(arguments) == output\\n assert part_1.solution(arguments) == output\",\n \"def testError(self):\\n cmds = \\\"\\\"\\\"chown 0 missingFile\\npwd\\nexit\\n\\\"\\\"\\\"\\n\\n def _cbCheckResult(res):\\n self.assertNotIn(self.testDir.asBytesMode().path, res)\\n\\n d = self._getBatchOutput(cmds)\\n d.addCallback(_cbCheckResult)\\n return d\",\n \"def test_partial_channel_invalid_map():\\n with np.testing.assert_raises(ValueError):\\n rho = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [12, 11, 10, 9]])\\n partial_channel(rho, 5)\",\n \"def test_init_ClusterNotFoundByName(self):\\n self.mock_search.return_value = []\\n self.assertRaises(npvmex.ClusterNotFoundByName, self._get_ssp_stor)\",\n \"def testCCHalt(self):\\n cdl_convert.config.HALT_ON_ERROR = True\\n\\n def getCC():\\n self.ccr_bad.cc\\n\\n self.assertRaises(\\n ValueError,\\n getCC\\n )\",\n \"def test_discover_array_fail(self):\\n self._set_args({\\\"password\\\": \\\"password\\\", \\\"subnet_mask\\\": \\\"192.168.1.0/24\\\", \\\"add_discovered_systems\\\": True})\\n systems = NetAppESeriesProxySystems()\\n with self.assertRaisesRegex(AnsibleFailJson, \\\"Failed to initiate array discovery.\\\"):\\n with mock.patch(self.TIME_FUNC, return_value=None):\\n with mock.patch(self.REQUEST_FUNC, return_value=Exception()):\\n systems.discover_array()\\n\\n self._set_args({\\\"password\\\": \\\"password\\\", \\\"subnet_mask\\\": \\\"192.168.1.0/24\\\", \\\"add_discovered_systems\\\": True})\\n systems = NetAppESeriesProxySystems()\\n with self.assertRaisesRegex(AnsibleFailJson, \\\"Failed to get the discovery results.\\\"):\\n with mock.patch(self.TIME_FUNC, return_value=None):\\n with mock.patch(self.REQUEST_FUNC, side_effect=[(200, {\\\"requestId\\\": \\\"1\\\"}), Exception()]):\\n systems.discover_array()\\n\\n self._set_args({\\\"password\\\": \\\"password\\\", \\\"subnet_mask\\\": \\\"192.168.1.0/24\\\", \\\"add_discovered_systems\\\": True})\\n systems = NetAppESeriesProxySystems()\\n with self.assertRaisesRegex(AnsibleFailJson, \\\"Timeout waiting for array discovery process.\\\"):\\n with mock.patch(self.TIME_FUNC, return_value=None):\\n with mock.patch(self.REQUEST_FUNC, side_effect=[(200, {\\\"requestId\\\": \\\"1\\\"})] + [(200, {\\\"discoverProcessRunning\\\": True})] * 1000):\\n systems.discover_array()\",\n \"def test_init(self):\\n nt.assert_raises(Exception, CisInterface.CisOutput, 'error')\",\n \"def test_compute_partial_charges(self):\\n # TODO: Test only one molecule for speed?\\n # TODO: Do we need to deepcopy each molecule, or is setUp called separately for each test method?\\n import numpy as np\\n from simtk import unit\\n\\n # Do not modify original molecules.\\n molecules = copy.deepcopy(mini_drug_bank())\\n\\n # Test a single toolkit at a time\\n # Removed ['amber', 'amberff94'] from OE list, as those won't find the residue types they're expecting\\n toolkit_to_charge_method = {\\n OpenEyeToolkitWrapper: [\\n \\\"mmff\\\",\\n \\\"mmff94\\\",\\n \\\"am1bcc\\\",\\n \\\"am1bccnosymspt\\\",\\n \\\"am1bccelf10\\\",\\n ],\\n AmberToolsToolkitWrapper: [\\\"bcc\\\", \\\"gas\\\", \\\"mul\\\"],\\n }\\n\\n manual_skips = []\\n\\n manual_skips.append(\\n \\\"ZINC1564378\\\"\\n ) # Warning: OEMMFF94Charges: assigning OEMMFFAtomTypes failed on mol .\\n manual_skips.append(\\n \\\"ZINC00265517\\\"\\n ) # Warning: OEMMFF94Charges: assigning OEMMFFAtomTypes failed on mol .\\n\\n for toolkit in list(toolkit_to_charge_method.keys()):\\n toolkit_registry = ToolkitRegistry(toolkit_precedence=[toolkit])\\n for charge_model in toolkit_to_charge_method[toolkit]:\\n c = 0\\n for molecule in molecules[:1]: # Just test first molecule to save time\\n c += 1\\n if molecule.name in manual_skips: # Manual skips, hopefully rare\\n continue\\n molecule.compute_partial_charges(\\n charge_model=charge_model, toolkit_registry=toolkit_registry\\n )\\n charges1 = molecule._partial_charges\\n # Make sure everything isn't 0s\\n assert (abs(charges1 / unit.elementary_charge) > 0.01).any()\\n # Check total charge\\n charges_sum_unitless = charges1.sum() / unit.elementary_charge\\n # if abs(charges_sum_unitless - float(molecule.total_charge)) > 0.0001:\\n # print('c {} molecule {} charge_sum {} molecule.total_charge {}'.format(c, molecule.name,\\n # charges_sum_unitless,\\n # molecule.total_charge))\\n # assert_almost_equal(charges_sum_unitless, molecule.total_charge, decimal=4)\\n\\n # Call should be faster second time due to caching\\n # TODO: Implement caching\\n molecule.compute_partial_charges(\\n charge_model=charge_model, toolkit_registry=toolkit_registry\\n )\\n charges2 = molecule._partial_charges\\n assert np.allclose(charges1, charges2, atol=0.002)\",\n \"def test_run_read(self):\\n\\n self.ictrl[0] = 1 + 2 + 4 + 8\\n vmec_f90wrap.runvmec(self.ictrl, self.filename, self.verbose, \\\\\\n self.fcomm, reset_file)\\n\\n self.assertTrue(self.ictrl[1] in success_codes)\\n\\n self.assertEqual(vmec_f90wrap.vmec_input.nfp, 3)\\n self.assertEqual(vmec_f90wrap.vmec_input.mpol, 4)\\n self.assertEqual(vmec_f90wrap.vmec_input.ntor, 3)\\n print('rbc.shape:', vmec_f90wrap.vmec_input.rbc.shape)\\n print('rbc:',vmec_f90wrap.vmec_input.rbc[101:103, 0:4])\\n\\n # n = 0, m = 0:\\n self.assertAlmostEqual(vmec_f90wrap.vmec_input.rbc[101,0], 1.3782)\\n\\n # n = 0, m = 1:\\n self.assertAlmostEqual(vmec_f90wrap.vmec_input.zbs[101,1], 4.6465E-01)\\n\\n # n = 1, m = 1:\\n self.assertAlmostEqual(vmec_f90wrap.vmec_input.zbs[102,1], 1.6516E-01)\\n\\n # Now try reading in the output\\n wout_file = os.path.join(os.path.dirname(__file__), 'wout_li383_low_res.nc')\\n ierr = 0\\n vmec_f90wrap.read_wout_mod.read_wout_file(wout_file, ierr)\\n self.assertEqual(ierr, 0)\\n self.assertAlmostEqual(vmec_f90wrap.read_wout_mod.betatot, \\\\\\n 0.0426215030653306, places=4)\\n\\n print('iotaf.shape:',vmec_f90wrap.read_wout_mod.iotaf.shape)\\n print('rmnc.shape:',vmec_f90wrap.read_wout_mod.rmnc.shape)\\n\\n self.assertAlmostEqual(vmec_f90wrap.read_wout_mod.iotaf[-1], \\\\\\n 0.654868168783638, places=4)\\n\\n self.assertAlmostEqual(vmec_f90wrap.read_wout_mod.rmnc[0, 0], \\\\\\n 1.4773028173065, places=4)\",\n \"def test_cputemp_get_data_error(self):\\n test_sensor_error_data = {\\n \\\"sensorid\\\": int(self.test_sens_data['sensorid']),\\n \\\"error\\\": \\\"Exception\\\",\\n \\\"code\\\": 1,\\n \\\"message\\\": \\\"CPUTemp sensor failed. See log for details\\\"\\n }\\n self.test_cputemp.get_data(self.test_sens_data, self.test_out_queue)\\n assert_equal(self.test_out_queue.get(), test_sensor_error_data)\",\n \"def test_returns_block() -> None:\\n gr = BlobGoal(REAL_RED)\\n gp = PerimeterGoal(MELON_MAMBO)\\n board = one_block_four_children_(1)\\n rp = RandomPlayer(0, gr)\\n sp = SmartPlayer(1, gp, 10)\\n rp._proceed = True\\n sp._proceed = True\\n move_block_rp = rp.generate_move(board)[2]\\n move_block_sp = sp.generate_move(board)[2]\\n assert move_block_rp == board or move_block_rp in board.children\\n assert move_block_sp == board or move_block_sp in board.children\",\n \"def testOutputReturned(self):\\n\\n def SideEffect(ci_builder):\\n b = [\\n ci_builder.replace('ci', 'try'),\\n ci_builder.replace('ci', 'try2'),\\n ]\\n return set(b), True\\n\\n self._get_mock.side_effect = SideEffect\\n mirrored_builders = builders.GetTryBuilders(['foo_ci', 'bar_ci'])\\n self.assertEqual(mirrored_builders,\\n set(['foo_try', 'foo_try2', 'bar_try', 'bar_try2']))\",\n \"def test_molecule_from_pdb_error_crystal_waters(self):\\n with pytest.raises(\\n UnassignedChemistryInPDBError,\\n match=(\\n r\\\"Note: 'HOH' is a residue code for water. You may have \\\"\\n + r\\\"crystallographic waters in your PDB file. Please remove \\\"\\n + r\\\"these before proceeding, or use Topology.from_pdb\\\\.\\\"\\n ),\\n ):\\n Molecule.from_polymer_pdb(\\n get_data_file_path(\\\"proteins/T4_protein_waters.pdb\\\")\\n )\",\n \"def test_invalid_input_data(self):\\n self.data.diffusion_data = self.data.diffusion_data[0]\\n self.assertRaises(ValueError, module_05.run_module,\\n self.data)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7752265","0.6388569","0.6297495","0.6286569","0.62686867","0.6196573","0.6173113","0.617114","0.6123175","0.60926574","0.59676576","0.5883313","0.587805","0.5837631","0.58120954","0.577729","0.5614546","0.56138414","0.56082726","0.55601","0.55297875","0.5484098","0.54734397","0.54571813","0.5454904","0.54448116","0.5432812","0.54089737","0.53627783","0.5347771","0.5339521","0.5329358","0.529693","0.5264967","0.52484494","0.5229008","0.5225007","0.5221719","0.51970947","0.5168955","0.5114539","0.51052845","0.50920933","0.50911117","0.5082645","0.50819427","0.50745535","0.5071777","0.5069019","0.5068735","0.50668603","0.5061705","0.5051576","0.50512147","0.5031148","0.5028217","0.50208455","0.50008124","0.4996766","0.499511","0.49759132","0.49759132","0.49728224","0.4972336","0.49671277","0.49521267","0.49494222","0.4947551","0.4940391","0.49336654","0.49306723","0.49206436","0.49151886","0.4913015","0.4906564","0.48973697","0.48932734","0.48899207","0.48878962","0.48847803","0.4884159","0.48838776","0.4883347","0.4880082","0.487654","0.48761213","0.48677945","0.48658758","0.48549864","0.48537472","0.48517114","0.485009","0.48464265","0.48437592","0.4842177","0.483144","0.48294255","0.48246717","0.482268","0.4822189"],"string":"[\n \"0.7752265\",\n \"0.6388569\",\n \"0.6297495\",\n \"0.6286569\",\n \"0.62686867\",\n \"0.6196573\",\n \"0.6173113\",\n \"0.617114\",\n \"0.6123175\",\n \"0.60926574\",\n \"0.59676576\",\n \"0.5883313\",\n \"0.587805\",\n \"0.5837631\",\n \"0.58120954\",\n \"0.577729\",\n \"0.5614546\",\n \"0.56138414\",\n \"0.56082726\",\n \"0.55601\",\n \"0.55297875\",\n \"0.5484098\",\n \"0.54734397\",\n \"0.54571813\",\n \"0.5454904\",\n \"0.54448116\",\n \"0.5432812\",\n \"0.54089737\",\n \"0.53627783\",\n \"0.5347771\",\n \"0.5339521\",\n \"0.5329358\",\n \"0.529693\",\n \"0.5264967\",\n \"0.52484494\",\n \"0.5229008\",\n \"0.5225007\",\n \"0.5221719\",\n \"0.51970947\",\n \"0.5168955\",\n \"0.5114539\",\n \"0.51052845\",\n \"0.50920933\",\n \"0.50911117\",\n \"0.5082645\",\n \"0.50819427\",\n \"0.50745535\",\n \"0.5071777\",\n \"0.5069019\",\n \"0.5068735\",\n \"0.50668603\",\n \"0.5061705\",\n \"0.5051576\",\n \"0.50512147\",\n \"0.5031148\",\n \"0.5028217\",\n \"0.50208455\",\n \"0.50008124\",\n \"0.4996766\",\n \"0.499511\",\n \"0.49759132\",\n \"0.49759132\",\n \"0.49728224\",\n \"0.4972336\",\n \"0.49671277\",\n \"0.49521267\",\n \"0.49494222\",\n \"0.4947551\",\n \"0.4940391\",\n \"0.49336654\",\n \"0.49306723\",\n \"0.49206436\",\n \"0.49151886\",\n \"0.4913015\",\n \"0.4906564\",\n \"0.48973697\",\n \"0.48932734\",\n \"0.48899207\",\n \"0.48878962\",\n \"0.48847803\",\n \"0.4884159\",\n \"0.48838776\",\n \"0.4883347\",\n \"0.4880082\",\n \"0.487654\",\n \"0.48761213\",\n \"0.48677945\",\n \"0.48658758\",\n \"0.48549864\",\n \"0.48537472\",\n \"0.48517114\",\n \"0.485009\",\n \"0.48464265\",\n \"0.48437592\",\n \"0.4842177\",\n \"0.483144\",\n \"0.48294255\",\n \"0.48246717\",\n \"0.482268\",\n \"0.4822189\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.75012517"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":81499,"cells":{"query":{"kind":"string","value":"Test the function for returning the desired residue data container. The function tested is pipe_control.mol_res_spin.return_residue()."},"document":{"kind":"string","value":"def test_return_residue(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_residue(':1')\n res2 = mol_res_spin.return_residue(selection=':2')\n res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')\n res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig')\n\n # Test the data of residue 1.\n self.assertEqual(res1.num, 1)\n self.assertEqual(res1.name, None)\n\n # Test the data of residue 2.\n self.assertEqual(res2.num, 2)\n self.assertEqual(res2.name, 'Glu')\n\n # Test the data of residue 4.\n self.assertEqual(res4.num, 4)\n self.assertEqual(res4.name, 'Pro')\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5.num, -5)\n self.assertEqual(res5.name, None)\n self.assertEqual(res5.spin[1].name, 'N5')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_return_single_residue_info(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_single_residue_info('1')\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\n res5 = mol_res_spin.return_single_residue_info('-5')\n\n # Test the data of residue 1.\n self.assertEqual(res1, (1, None))\n\n # Test the data of residue 2.\n self.assertEqual(res2, (2, 'Glu'))\n\n # Test the data of residue 4.\n self.assertEqual(res4, (4, 'Pro'))\n\n # Test the data of the RNA residue -5.\n self.assertEqual(res5, (-5, None))","def test_return_molecule(self):\n\n # Ask for a few molecules.\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\n\n # Test the data of molecule 1.\n self.assertEqual(mol1.name, 'Ap4Aase')\n\n # Test the data of molecule 2.\n self.assertEqual(mol2.name, 'RNA')","def test_return_single_residue_info_fail(self):\n\n # Ask for a few residues.\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')","def test_return_residue_pipe_fail(self):\n\n # Try to get a residue from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')","def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 0)","def test_return_spin(self):\n\n # Ask for a few spins.\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\n\n # Test the data of spin 1.\n self.assertNotEqual(spin1, None)\n self.assertEqual(spin1.num, 60)\n self.assertEqual(spin1.name, 'NH')\n\n # Test the data of spin 2.\n self.assertNotEqual(spin2, None)\n self.assertEqual(spin2.num, 63)\n self.assertEqual(spin2.name, 'NH')\n\n # Test the data of spin 3.\n self.assertNotEqual(spin3, None)\n self.assertEqual(spin3.num, None)\n self.assertEqual(spin3.name, None)\n\n # Test the data of the RNA res -5, spin N5.\n self.assertNotEqual(spin4, None)\n self.assertEqual(spin4.num, None)\n self.assertEqual(spin4.name, 'N5')\n\n # Test the data of the RNA res -4, spin 2H.\n self.assertNotEqual(spin5, None)\n self.assertEqual(spin5.num, 132)\n self.assertEqual(spin5.name, '2H')","def test_residue_loop(self):\n\n # Loop over the residues.\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\n # Test the selection.\n self.assertEqual(res.num, 2)\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)","def test_exists_mol_res_spin_data_single_res_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first residue.\n dp.mol[0].res[0].num = 1\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertEqual(res.num, num[i])\n\n # Test the residue names.\n self.assertEqual(res.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(i, 5)","def residue(res_name):\n _init_dataset()\n array_dict = _residues[res_name]\n\n array = AtomArray(len(array_dict[\"res_name\"]))\n\n array.res_name = array_dict[\"res_name\"]\n array.atom_name = array_dict[\"atom_name\"]\n array.element = array_dict[\"element\"]\n array.charge = array_dict[\"charge\"]\n array.hetero = array_dict[\"hetero\"]\n\n array.coord[:,0] = array_dict[\"coord_x\"]\n array.coord[:,1] = array_dict[\"coord_y\"]\n array.coord[:,2] = array_dict[\"coord_z\"]\n\n array.bonds = BondList(\n array.array_length(),\n bonds = np.stack([\n array_dict[\"bond_i\"],\n array_dict[\"bond_j\"],\n array_dict[\"bond_type\"]\n ]).T\n )\n\n return array","def test_exists_mol_res_spin_data_single_res_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first residue.\n dp.mol[0].res[0].name = 'Lys'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def residue(self, resnum, chain_id, icode=' ', alt=' ', model_num = 0):\n res = self.struct[model_num][chain_id][(alt, resnum, icode)]\n res.chain_id = chain_id\n return res","def get_residue(self, chainid, resid) :\n if not self._res_dict :\n d = {}\n for r in self.residues :\n d[ (r.chainid, r.resid)] = r\n self._res_dict =d\n \n return self._res_dict[(chainid, resid)]","def check_residue(self, chain_id, resid, resname):\n if resname in PTM_lookup.keys():\n return\n else:\n try:\n ref_resname = PTM_reverse_lookup[resname]\n except KeyError:\n # print \"skipping unrecognized residue\", resname\n return\n ptm_dict = PTM_lookup[ref_resname][resname]\n return (chain_id, resid, ref_resname, ptm_dict[\"goto_atom\"], ptm_dict[\"name\"])","def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def check_residue_callback(self):\n\n if not self.check_for_residue_existance():\n return\n\n self.listbox_current_designs.delete(0, END)\n self.current_residueFull = self.current_residue.get().split(\":\")\n\n if len(self.current_residueFull) > 1:\n self.listbox_restypes.delete(9)\n self.listbox_restypes.insert(9, \"Conserved\")\n else:\n res = self.current_residueFull[0] +\":\"+self.current_chain.get()\n #print res\n if not self.pose.total_residue():\n return\n\n resType = self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get()))\n try:\n resName = self.pose.residue(resType).name()\n except PyRosettaException:\n print \"Residue does not exist in PDB...\"\n return\n\n\n self.current_residue_name_full.set(resName)\n three_letter_name = resName.split(\"_\")[0]; #Fix for Rosetta designated chain endings, His_d\n self.current_residue_name.set(resName)\n\n #Fix for not having data for certain residue types:\n try:\n self.design_accessible_sa.set(self.residue_definitions.resinfo[three_letter_name][0])\n self.design_relative_mutability.set(self.residue_definitions.resinfo[three_letter_name][1])\n self.design_surface_probability.set(self.residue_definitions.resinfo[three_letter_name][2])\n except KeyError:\n print \"No Data for restype\"\n self.design_accessible_sa.set(\"\")\n self.design_relative_mutability.set(\"\")\n self.design_surface_probability.set(\"\")\n\n con = \"Conserved:\" +three_letter_name\n self.listbox_restypes.delete(9)\n self.listbox_restypes.insert(9, con)\n if self.DesignDic.has_key(res):\n for residues in self.DesignDic[res]:\n self.listbox_current_designs.insert(END, residues)","def test_residue_loop_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # Function for the problem of catching an error in a generator function.\n def fail_test():\n for residue in mol_res_spin.residue_loop():\n pass\n\n # Test for the no pipe error.\n self.assertRaises(RelaxNoPipeError, fail_test)","def get_residue(self, resid, chainLocal=False):\n \n try:\n resid = int(resid)\n except ValueError, e:\n print \"ERROR: get_resid() requires a numeric value\"\n raise e\n \n\n if type(resid) == int: \n \n if chainLocal:\n for res in self.residues:\n if res.chain_local_id == resid: \n return res\n else: \n for res in self.residues:\n if res.res_id == resid:\n return res","def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def getResAromaticVectors(residues):\n for res in residues.keys():\n rtype = res.split(\":\")[1][0:3] # A:GLY48 => GLY\n try:\n if rtype == \"PHE\" or rtype == \"TYR\":\n if len(residues[res]) == 6:\n pass\n else:\n if DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n elif rtype == \"TRP\":\n if len(residues[res]) >= 9:\n residues[res] = purgeTrp(residues[res])\n else:\n if DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n elif rtype == \"HIS\":\n if len(residues[res]) >= 5:\n residues[res] = purgeHis(residues[res])\n else:\n if DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n elif rtype == \"ARG\":\n residues[res] = purgeArg(residues[res])\n if not residues[res] and DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n elif rtype == \"DA\" or rtype == \"A\":\n if len(residues[res]) >= 10:\n residues[res] = purgeAdenine(residues[res])\n else:\n if DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n elif rtype == \"DC\" or rtype == \"C\":\n if len(residues[res]) >= 6:\n residues[res] = purgeAdenine(residues[res])\n else:\n if DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n elif rtype == \"DG\" or rtype == \"G\":\n if len(residues[res]) >= 10:\n residues[res] = purgeAdenine(residues[res])\n else:\n if DEBUG: print \"Warning! Ignoring residue [ %s ] (missing atoms)\" % res\n if residues[res]:\n residues[res] = atomsToVec(residues[res])\n else:\n del residues[res]\n except:\n if DEBUG: print \"Fatal error in processing residue [ %s ]\"% res\n del residues[res]\n return residues","def test_exists_mol_res_spin_data_single_spin_name(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first spin.\n dp.mol[0].res[0].spin[0].name = 'NH'\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())","def get_residue_info(self):\n return","def __getitem__(self, residue_number):\n return self.residues_by_number[residue_number]","def test_return_molecule_pipe_fail(self):\n\n # Try to get a molecule from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')","def test_RUMI():\r\n\r\n start = 11051\r\n end = 11902\r\n read_poems(start, end)","def getAmberParams(residue, name):\n atomname = name\n type = residue.get(\"type\")\n if type == 4:\n resname = residue.get(\"naname\")\n else:\n resname = residue.get(\"name\")\n\n # Residue Substitutions\n\n if residue.get(\"name\") == \"CYS\" and \"HG\" not in residue.get(\"map\"):\n resname = \"CYX\"\n elif residue.get(\"name\") == \"HIS\":\n if \"HD1\" in residue.get(\"map\") and \"HE2\" in residue.get(\"map\"):\n resname = \"HIP\"\n elif \"HD1\" in residue.get(\"map\"):\n resname = \"HID\"\n elif \"HE2\" in residue.get(\"map\"):\n resname = \"HIE\"\n else:\n resname = \"HID\" # Default for no hydrogens\n elif residue.get(\"name\") == \"HSP\":\n resname = \"HIP\"\n elif residue.get(\"name\") == \"HSE\":\n resname = \"HIE\"\n elif residue.get(\"name\") == \"HSD\":\n resname = \"HID\"\n elif residue.get(\"name\") == \"GLU\" or residue.get(\"name\") == \"GLH\":\n if \"HE1\" in residue.get(\"map\"):\n resname = \"GLH\"\n if atomname == \"HE1\":\n atomname = \"HE2\"\n elif atomname == \"OE1\":\n atomname = \"OE2\"\n elif atomname == \"OE2\":\n atomname = \"OE1\"\n elif \"HE2\" in residue.get(\"map\"):\n resname = \"GLH\"\n elif residue.get(\"name\") == \"ASP\" or residue.get(\"name\") == \"ASH\":\n if \"HD1\" in residue.get(\"map\"):\n resname = \"ASH\"\n if atomname == \"HD1\":\n atomname = \"HD2\"\n elif atomname == \"OD1\":\n atomname = \"OD2\"\n elif atomname == \"OD2\":\n atomname = \"OD1\"\n elif \"HD2\" in residue.get(\"map\"):\n resname = \"ASH\"\n\n if residue.get(\"isCterm\"):\n resname = \"C\" + resname\n elif residue.get(\"isNterm\"):\n resname = \"N\" + resname\n\n # Atom Substitutions\n\n if resname == \"WAT\":\n if atomname == \"O\":\n atomname = \"OW\"\n elif atomname == \"H1\":\n atomname = \"HW\"\n elif atomname == \"H2\":\n atomname = \"HW\"\n elif resname == \"ILE\":\n if atomname == \"CD\": atomname = \"CD1\"\n if resname[0] == \"N\" and resname != \"NME\": # N-terminal\n if atomname == \"H\": atomname = \"H1\"\n if (resname == \"CCYS\" or resname == \"NCYS\") and atomname == \"HG\": atomname = \"HSG\"\n if resname == \"CYM\" and atomname == \"H\": atomname = \"HN\"\n if residue.get(\"isNterm\") and resname == \"NPRO\" and atomname == \"HN2\":\n atomname = \"H2\"\n if residue.get(\"isNterm\") and resname == \"NPRO\" and atomname == \"HN1\":\n atomname = \"H3\"\n return resname, atomname","def _residue_from_residue_id(self, residue_id):\n\n residues = list(self._data_complex.get_residues())\n # Select residue of interest\n # residue.get_id()[2] == \" \" makes sure that only the first residue is selected in case\n # there are residues with insertion codes for the residue of interest\n residue = [\n residue\n for residue in residues\n if (residue.get_id()[1] == residue_id) and (residue.get_id()[2] == \" \")\n ]\n\n if len(residue) == 1:\n return residue[0]\n elif len(residue) == 0:\n return None\n else:\n residue_ids = [residue.get_id()[1] for residue in residues]\n residue_ids_duplicated = [\n item for item, count in collections.Counter(residue_ids).items() if count > 1\n ]\n raise KeyError(\n f\"{len(residue)} residues were found, but must be 1 or 0. \"\n f\"Duplicated residue serial number(s): {residue_ids_duplicated}\"\n )","def data(self, pdb, **kwargs):\n\n structure = self.structure(pdb)\n\n # running infer_hydrogens, but now that is done automatically\n# structure.infer_hydrogens()\n\n for residue in structure.residues():\n\n if hasattr(residue, 'rotation_matrix'):\n matrix = residue.rotation_matrix\n # if there are not enough atoms for the rotation matrix, it will be None\n if matrix is not None:\n yield mod.UnitRotations(unit_id=residue.unit_id(),\n pdb_id=pdb,\n cell_0_0=float(matrix[0, 0]),\n cell_0_1=float(matrix[0, 1]),\n cell_0_2=float(matrix[0, 2]),\n cell_1_0=float(matrix[1, 0]),\n cell_1_1=float(matrix[1, 1]),\n cell_1_2=float(matrix[1, 2]),\n cell_2_0=float(matrix[2, 0]),\n cell_2_1=float(matrix[2, 1]),\n cell_2_2=float(matrix[2, 2]))","def test_exists_mol_res_spin_data_no_pipe(self):\n\n # Reset relax.\n reset()\n\n # This should fail.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)","def mutate_residue(pose, mutant_position, mutant_aa,\n pack_radius = 0.0, pack_scorefxn = '' ):\n #### a MutateResidue Mover exists similar to this except it does not pack\n #### the area around the mutant residue (no pack_radius feature)\n #mutator = MutateResidue(mutant_position, mutant_aa)\n #mutator.apply(test_pose)\n\n if pose.is_fullatom() == False:\n IOError( 'mutate_residue only works with fullatom poses' )\n\n\n # create a standard scorefxn by default\n if not pack_scorefxn:\n pack_scorefxn = rosetta.core.scoring.get_score_function()\n\n task = pyrosetta.standard_packer_task(pose)\n\n # the Vector1 of booleans (a specific object) is needed for specifying the\n # mutation, this demonstrates another more direct method of setting\n # PackerTask options for design\n aa_bool = rosetta.utility.vector1_bool()\n # PyRosetta uses several ways of tracking amino acids (ResidueTypes)\n # the numbers 1-20 correspond individually to the 20 proteogenic amino acids\n # aa_from_oneletter returns the integer representation of an amino acid\n # from its one letter code\n # convert mutant_aa to its integer representation\n mutant_aa = rosetta.core.chemical.aa_from_oneletter_code(mutant_aa)\n\n # mutation is performed by using a PackerTask with only the mutant\n # amino acid available during design\n # to do this, construct a Vector1 of booleans indicating which amino acid\n # (by its numerical designation, see above) to allow\n for i in range(1, 21):\n # in Python, logical expression are evaluated with priority, thus the\n # line below appends to aa_bool the truth (True or False) of the\n # statement i == mutant_aa\n aa_bool.append( i == int(mutant_aa) )\n\n # modify the mutating residue's assignment in the PackerTask using the\n # Vector1 of booleans across the proteogenic amino acids\n task.nonconst_residue_task(mutant_position\n ).restrict_absent_canonical_aas(aa_bool)\n\n # prevent residues from packing by setting the per-residue \"options\" of\n # the PackerTask\n restrict_non_nbrs_from_repacking(pose, mutant_position, task, pack_radius)\n\n # apply the mutation and pack nearby residues\n #print task\n packer = rosetta.protocols.simple_moves.PackRotamersMover(pack_scorefxn, task)\n packer.apply(pose)","def residue(b, a, tol=1e-3, rtype='avg'):\n if (cupy.issubdtype(b.dtype, cupy.complexfloating)\n or cupy.issubdtype(a.dtype, cupy.complexfloating)):\n b = b.astype(complex)\n a = a.astype(complex)\n else:\n b = b.astype(float)\n a = a.astype(float)\n\n b = cupy.trim_zeros(cupy.atleast_1d(b), 'f')\n a = cupy.trim_zeros(cupy.atleast_1d(a), 'f')\n\n if a.size == 0:\n raise ValueError(\"Denominator `a` is zero.\")\n\n poles = roots(a)\n if b.size == 0:\n return cupy.zeros(poles.shape), _cmplx_sort(poles)[0], cupy.array([])\n\n if len(b) < len(a):\n k = cupy.empty(0)\n else:\n k, b = _polydiv(b, a)\n\n unique_poles, multiplicity = unique_roots(poles, tol=tol, rtype=rtype)\n unique_poles, order = _cmplx_sort(unique_poles)\n multiplicity = multiplicity[order]\n\n residues = _compute_residues(unique_poles, multiplicity, b)\n\n index = 0\n for pole, mult in zip(unique_poles, multiplicity):\n poles[index:index + mult] = pole\n index += mult\n\n return residues / a[0], poles, k","def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())","def test_residues(parse_mmtf):\n parse_mmtf.assertEqual(len(parse_mmtf.mmcif_res), len(parse_mmtf.mmtf_res))\n for i, e in enumerate(parse_mmtf.mmcif_res):\n mmcif_r = parse_mmtf.mmcif_res[i]\n mmtf_r = parse_mmtf.mmtf_res[i]\n parse_mmtf.assertEqual(mmtf_r.level, mmcif_r.level)\n parse_mmtf.assertEqual(mmtf_r.disordered, mmcif_r.disordered)\n parse_mmtf.assertEqual(mmtf_r.resname, mmcif_r.resname)\n parse_mmtf.assertEqual(mmtf_r.segid, mmcif_r.segid)\n parse_mmtf.mmcif_atoms = [x for x in mmcif_r.get_atom()]\n parse_mmtf.mmtf_atoms = [x for x in mmtf_r.get_atom()]\n test_atoms(parse_mmtf=parse_mmtf)","def getResidue(self, resnum, icode=None):\n\n return self._hv.getResidue(self.getChid(), resnum, icode,\n self.getSegname())","def get_residues_sequence (structure):\n list_fastas=[]\n residues_dict = {'CYS': 'C', 'ASP': 'D', 'SER': 'S', 'GLN': 'Q', 'LYS': 'K',\n 'ILE': 'I', 'PRO': 'P', 'THR': 'T', 'PHE': 'F', 'ASN': 'N',\n 'GLY': 'G', 'HIS': 'H', 'LEU': 'L', 'ARG': 'R', 'TRP': 'W',\n 'ALA': 'A', 'VAL': 'V', 'GLU': 'E', 'TYR': 'Y', 'MET': 'M'}\n\n rna_dict={ ' G': 'G', ' C': 'C', ' A': 'A', ' T': 'T', ' U': 'U'}\n dna_dict={ ' DG': 'G', ' DC': 'C', ' DA': 'A', ' DT': 'T', ' DU': 'U'}\n\n for model in structure:\n for chain in model:\n string=\"\"\n for residue in chain:\n for atom in residue:\n if atom.id == \"CA\":\n if residue.resname == 'UNK':\n continue \n else:\n if residue.resname not in residues_dict:\n raise NoExistsResidue(residue.resname) \n residue_name = residues_dict[residue.resname] \n string = string + residue_name\n elif atom.id == \"P\":\n if residue.resname.startswith(\" D\"):\n residue_name= dna_dict[residue.resname]\n if residue.resname not in dna_dict:\n raise NoExistsDesoxiribonucleotide(residue.resname)\n else:\n residue_name= rna_dict[residue.resname]\n if residue.resname not in rna_dict:\n raise NoExistsRibonucleotide(residue.resname)\n string= string + residue_name\n if string != \"\":\n list_fastas.append(string)\n return list_fastas","def get_contact_residue(self,cutoff=8.5,chain1='A',chain2='B',excludeH=False,\n only_backbone_atoms=False,return_contact_pairs=False):\n # get the contact atoms\n if return_contact_pairs:\n\n # declare the dict\n residue_contact_pairs = {}\n\n # get the contact atom pairs\n atom_pairs = self.get_contact_atoms(cutoff=cutoff,chain1=chain1,chain2=chain2,\n only_backbone_atoms=only_backbone_atoms,\n excludeH=excludeH,\n return_contact_pairs=True)\n\n # loop over the atom pair dict\n for iat1,atoms2 in atom_pairs.items():\n\n # get the res info of the current atom\n data1 = tuple(self.get('chainID,resSeq,resName',rowID=[iat1])[0])\n\n # create a new entry in the dict if necessary\n if data1 not in residue_contact_pairs:\n residue_contact_pairs[data1] = set()\n\n # get the res info of the atom in the other chain\n data2 = self.get('chainID,resSeq,resName',rowID=atoms2)\n\n # store that in the dict without double\n for resData in data2:\n residue_contact_pairs[data1].add(tuple(resData))\n\n for resData in residue_contact_pairs.keys():\n residue_contact_pairs[resData] = sorted(residue_contact_pairs[resData])\n\n return residue_contact_pairs\n\n else:\n\n # get the contact atoms\n contact_atoms = self.get_contact_atoms(cutoff=cutoff,chain1=chain1,chain2=chain2,return_contact_pairs=False)\n\n # get the residue info\n data1 = self.get('chainID,resSeq,resName',rowID=contact_atoms[0])\n data2 = self.get('chainID,resSeq,resName',rowID=contact_atoms[1])\n\n # take only unique\n residue_contact_A = sorted(set([tuple(resData) for resData in data1]))\n residue_contact_B = sorted(set([tuple(resData) for resData in data2]))\n\n return residue_contact_A,residue_contact_B","def getResonanceResidue(resonance):\n\n residue = None\n if resonance.resonanceSet:\n residue = resonance.resonanceSet.findFirstAtomSet().findFirstAtom().residue\n \n return residue","def test_from_pdb_t4_n_residues(self):\n expected_n_residues = 164 # noqa\n raise NotImplementedError","def assignResonanceResidue(resonance, residue):\n\n\n #print 'assignResonanceResidue', makeResonanceGuiName(resonance), residue.seqId\n if residue:\n # we could be setting the residue to None\n if not setAssignmentMolSystem(residue, resonance=resonance):\n return\n \n resonanceSet = resonance.resonanceSet\n if resonanceSet:\n assignNames = set()\n \n for atomSet in resonanceSet.atomSets:\n assignNames.add(atomSet.name)\n \n else:\n assignNames = set(resonance.assignNames)\n \n assignedResidue = getResonanceResidue(resonance)\n \n if assignNames and (assignedResidue is not residue):\n resonance.setAssignNames(assignNames)\n \n if residue:\n atomSets = []\n isotopeCode = resonance.isotopeCode\n if ('HA' in assignNames) and (residue.ccpCode == 'Gly'):\n assignNames.add('HA2')\n assignNames.add('HA3')\n \n for atom in residue.atoms:\n element = atom.chemAtom.elementSymbol\n \n if isotopeCode[-len(element):] != element:\n continue\n \n atomSet = atom.atomSet\n if atomSet:\n if atomSet.name in assignNames:\n if atomSet not in atomSets:\n atomSets.append(atomSet)\n \n if resonanceSet:\n resonanceSet.delete()\n \n if atomSets:\n # might not always find atom sets\n # e.g. if changing residue types\n assignAtomsToRes(atomSets,resonance,None)\n else:\n if resonanceSet:\n resonanceSet.delete()\n #updateResonanceAnnotation(resonance)\n\n if not resonance.resonanceGroup:\n nmrProject = resonance.nmrProject\n spinSystem = None\n molResidue = residue.molResidue\n ccpCode = molResidue.ccpCode\n molType = molResidue.molType\n spinSystems = nmrProject.findAllResonanceGroups(ccpCode=ccpCode,\n molType=molType)\n \n for extantSpinSystem in spinSystems:\n if extantSpinSystem.residue is residue:\n spinSystem = extantSpinSystem\n break\n \n if not spinSystem:\n spinSystem = nmrProject.newResonanceGroup()\n assignSpinSystemResidue(spinSystem,residue)\n \n if resonance not in spinSystem.resonances:\n spinSystem.addResonance(resonance)\n updateResonanceAnnotation(resonance)\n \n else:\n updateResonanceAnnotation(resonance)","def test_perceive_residues_sorting(self, strict_chirality):\n molecule = Molecule.from_file(get_data_file_path(\"proteins/ace-a10-nme.sdf\"))\n\n molecule.perceive_residues(strict_chirality=strict_chirality)\n\n for index, residue in enumerate(molecule.residues):\n found = residue.residue_number\n expected = str(index + 1)\n\n assert isinstance(found, str)\n assert found == expected","def test_boolean_complex_selection(self):\n\n # The residue selection loop.\n sel = list(mol_res_spin.residue_loop(\"#Ap4Aase:4 & :Pro | #RNA\"))\n\n # Residue names and numbers.\n names = ['Pro', None, None]\n numbers = [4, -5, -4]\n\n # The residues.\n self.assertEqual(len(sel), 3)\n for i in range(3):\n self.assertEqual(sel[i].name, names[i])\n self.assertEqual(sel[i].num, numbers[i])","def test_run_molecule(self, single_mol_system):\n sequence = \"ABCDE\"\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_molecule(single_mol_system.molecules[0])\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def read_resfile(filename):\n def place_constraints(constraint, init_seq):\n \"\"\"\n places the constraints in the appropriate dicts \n -initial_seq for building the initial sequence with TPIKAA and TNOTAA\n -constraints for restricting the conditional model with PIKAA, NOTAA, ALLAA, POLAR, etc.\n \"\"\"\n if not init_seq:\n constraints[res_id] = constraint\n else:\n initial_seq[res_id] = constraint\n\n constraints = dict() # amino acids to restrict in the design\n header, start_id = check_for_header(filename) # amino acids to use as default for those not specified in constraints\n initial_seq = dict() # amino acids to use when initializing the sequence\n\n with open(filename, \"r\") as f:\n # iterate over the lines and extract arguments (residue id, command)\n lines = f.readlines()\n for line in lines[start_id + 1:]:\n args = [arg.strip() for arg in line.split(\" \")]\n is_integer(args[0]) # the res id needs to be an integer\n assert isinstance(args[1], str), \"the resfile command needs to be a string\"\n \n res_id = int(args[0]) - 1\n if args[1] == \"-\": # if given a range of residue ids (ex. 31 - 33 NOTAA)\n is_integer(args[2]) # the res id needs to be an integer\n for res_id in range(res_id, int(args[2])):\n constraint, init_seq = check_for_commands(args, 3, 4)\n place_constraints(constraint, init_seq)\n else: # if not given a range (ex. 31 NOTAA CA)\n constraint, init_seq = check_for_commands(args, 1, 2)\n place_constraints(constraint, init_seq)\n \n # update the initial seq dictionary to only have one element per residue id (at random)\n initial_seq = {res_id : (common.atoms.resfile_commands[\"ALLAAwc\"] - restricted_aa).pop() for res_id, restricted_aa in initial_seq.items()}\n\n return constraints, header, initial_seq","def getResidue(self, resname):\n if self.hasResidue(resname):\n return self.map[resname]\n else:\n return None","def test_single_molecule(self, single_mol_system, sequence):\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\n processor = dssp.AnnotateResidues(\"test\", sequence)\n processor.run_system(single_mol_system)\n found = self.sequence_from_system(single_mol_system, \"test\")\n assert found == expected","def getResidue(self, resi):\n\n\t\tif self.numChains == 0:\n\t\t\tprint \"WARNING: Molecule has no chains\"\n\t\t\treturn None\n\n\t\tresi = int(resi)\n\t\tfor chn in self.chain:\n\t\t\tfor res in chn.residue:\n\t\t\t\tif int(res.file_id) == resi:\n\t\t\t\t\treturn res\n\n\t\treturn None","def test_ipam_rirs_list(self):\n pass","def test_perceive_residues_natoms_mainchain_arginine(self, strict_chirality):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/MainChain_ARG.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def returnData(self):\r\n return self.returnRes","def get_residue(self, resnum, chain):\n res_chain = self.get_chain(chain)\n residue = []\n for line in res_chain.split(\"\\n\"):\n if str(resnum) == str(line[22:26].strip()):\n residue.append(line)\n return \"\\n\".join(residue)","def test_residues_perceived_dipeptide(self):\n from openff.toolkit._tests.create_molecules import (\n dipeptide_residues_perceived as create_dipeptide,\n )\n\n dipeptide_residues_perceived = create_dipeptide()\n\n assert \"ACE\" == dipeptide_residues_perceived.atoms[0].metadata[\"residue_name\"]\n assert \"1\" == dipeptide_residues_perceived.atoms[0].metadata[\"residue_number\"]\n assert \" \" == dipeptide_residues_perceived.atoms[0].metadata[\"insertion_code\"]\n\n assert \"ALA\" == dipeptide_residues_perceived.atoms[10].metadata[\"residue_name\"]\n assert \"2\" == dipeptide_residues_perceived.atoms[10].metadata[\"residue_number\"]\n assert \" \" == dipeptide_residues_perceived.atoms[10].metadata[\"insertion_code\"]\n\n assert isinstance(dipeptide_residues_perceived.residues[0], HierarchyElement)\n with pytest.raises(AttributeError):\n type(dipeptide_residues_perceived.chains[0])","def test_find_surface_residues():\n atom_dict_0 = find_surface_residues(protein, max_dist=0, scaling=1)\n atom_dict_1 = find_surface_residues(protein, max_dist=2, scaling=1)\n atom_dict_2 = find_surface_residues(protein, max_dist=3, scaling=1)\n atom_dict_3 = find_surface_residues(protein, max_dist=None, scaling=1)\n atom_dict_4 = find_surface_residues(protein, max_dist=None, scaling=2)\n\n assert atom_dict_0.size == 0\n assert len(atom_dict_1) > len(atom_dict_0), ('Increasing max_dist should '\n 'result in more/equal number '\n 'of atoms found')\n\n assert len(atom_dict_2) >= len(atom_dict_1), ('Increasing max_dist should '\n 'result in more/equal number '\n 'of atoms found')\n assert_array_equal(np.intersect1d(atom_dict_1['id'], atom_dict_2['id']), atom_dict_1['id'])\n\n if oddt.toolkit.backend == 'ob':\n ref_len_1 = 762\n ref_len_2 = 968\n ref_len_3 = 654\n ref_len_4 = 379\n elif oddt.toolkit.backend == 'rdk' and oddt.toolkits.rdk.__version__ >= '2019.09':\n ref_len_1 = 762\n ref_len_2 = 968\n ref_len_3 = 664\n ref_len_4 = 393\n else:\n ref_len_1 = 759\n ref_len_2 = 966\n ref_len_3 = 735\n ref_len_4 = 489\n\n assert len(atom_dict_1) == ref_len_1\n assert len(atom_dict_2) == ref_len_2\n assert len(atom_dict_3) == ref_len_3\n assert len(atom_dict_4) == ref_len_4\n\n # Adding hydrogen atoms should have no effect on the result\n protein.addh()\n atom_dict_addh = find_surface_residues(protein, max_dist=2, scaling=1)\n assert_array_equal(atom_dict_addh['id'], atom_dict_1['id'])\n\n with pytest.raises(TypeError):\n find_surface_residues(molecule=1)\n with pytest.raises(ValueError):\n find_surface_residues(molecule=protein, max_dist='a')\n with pytest.raises(ValueError):\n find_surface_residues(molecule=protein, max_dist=[1, 1, 1])","def test_return_spin_pipe_fail(self):\n\n # Try to get a spin from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')","def getResonanceAtomTuple(resonance):\n from ccpnmr.analysis.core.MoleculeBasic import getResidueCode\n \n molSystemCode = ''\n chainCode = ''\n res = ''\n name = getResonanceName(resonance)\n\n if resonance.resonanceSet:\n residue = getResonanceResidue(resonance)\n chain = residue.chain\n chainCode = chain.code\n molSystemCode = chain.molSystem.code\n res = str(residue.seqCode) + getResidueCode(residue)\n \n elif hasattr(resonance, 'resonanceGroup'): # Not FixedResonance\n spinSystem = resonance.resonanceGroup\n \n if spinSystem:\n residue = spinSystem.residue\n ccpCode = spinSystem.ccpCode\n residueProbs = [rp for rp in spinSystem.residueProbs if rp.weight > 0.0]\n \n if residue:\n sysChain = residue.chain\n chainCode = sysChain.code\n molSystemCode = sysChain.molSystem.code\n res = str(residue.seqCode) + getResidueCode(residue)\n\n elif residueProbs:\n resTexts = []\n resSeqs = []\n resCodes = set()\n \n for residueProb in residueProbs:\n residue = residueProb.possibility\n seq = residue.seqCode\n code = getResidueCode(residue)\n \n resTexts.append('%d?%s' % (seq,code))\n resSeqs.append('%d?' % seq)\n resCodes.add(code)\n \n if len(resCodes) == 1:\n res = '/'.join(resSeqs) + resCodes.pop()\n else:\n res = '/'.join(resTexts)\n \n elif ccpCode:\n res = '{%d}%s' % (spinSystem.serial,ccpCode)\n\n elif spinSystem.name:\n res = '{%d:%s}' % (spinSystem.serial,spinSystem.name)\n \n else:\n res = '{%d}' % (spinSystem.serial)\n \n return (molSystemCode, chainCode, res, name)","def test_molecule_loop(self):\n\n # Loop over the molecules.\n for mol in mol_res_spin.molecule_loop('#RNA'):\n # Test the molecule name.\n self.assertEqual(mol.name, 'RNA')\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)","def get_next_residue(self):\n rawline = self.f.readline()\n while rawline:\n rematch = self.reslinere.match(rawline)\n if rematch:\n return (rematch.groups()[0], int(rematch.groups()[1]),\n float(rematch.groups()[2]), float(rematch.groups()[3]),\n float(rematch.groups()[4]), int(rematch.groups()[5]))\n # If we make it to a blank line, keep skipping forward until we hit\n # another CUMULATIVE record\n elif not rawline.strip():\n rematch2 = self.my_re.match(rawline)\n while not rematch2:\n rawline = self.f.readline()\n # Check if we hit EOF\n if not rawline: return None\n rematch2 = self.my_re.match(rawline)\n # end while not rematch2\n rawline = self.f.readline()\n # If we hit here, we are out of lines, or something\n return None","def test_call_wrapped_function(self):\r\n\r\n # adapted from test_app.test_cd_hit.test_cdhit_clusters_from_seqs\r\n\r\n exp = {'0': 'R27DLI_4812',\r\n '1': 'U1PLI_7889',\r\n '2': 'W3Cecum_4858',\r\n '3': 'R27DLI_3243',\r\n }\r\n app = GenericRepSetPicker(params={'Algorithm': 'most_abundant',\r\n 'ChoiceF': make_most_abundant, 'ChoiceFRequiresSeqs': True})\r\n obs = app(self.tmp_seq_filepath, self.tmp_otu_filepath)\r\n self.assertEqual(obs, exp)","def test_resids(self):\n cr = CaseReader(self.filename)\n last_case = cr.get_case(-1)\n self.assertIsNone(last_case.resids,\n \"Case erroneously contains resids.\")","def select_perturbation_residues(molecule):\n # Validte the length of the molecule\n validate_molecule_length(molecule)\n # Set the maximum allowed perturbation numbers\n maxNum = 3\n # Select a random number between 1 and maxNum\n ranNum = random.randint(1, maxNum)\n # Define the perturbed list to hold the perturbed residue name\n perturbed = []\n count = 0\n while count < ranNum:\n # Random select a residue number in the molecule \n index = random.randint(1, len(molecule))\n perturbed.append([molecule.name, index, molecule[index].name])\n count += 1\n\n return perturbed","def getCharmmParams(residue, name):\n resname = residue.get(\"name\")\n atomname = name\n\n # Nucleic Acid Substitutions\n\n if residue.get(\"type\") == 4:\n resname = resname[0]\n if resname == \"A\":\n resname = \"ADE\"\n elif resname == \"C\":\n resname = \"CYT\"\n elif resname == \"G\":\n resname = \"GUA\"\n elif resname == \"T\":\n resname = \"THY\"\n if atomname == \"C7\":\n atomname = \"C5M\"\n elif atomname == \"H71\":\n atomname = \"H51\"\n elif atomname == \"H72\":\n atomname = \"H52\"\n elif atomname == \"H73\":\n atomname = \"H53\"\n elif resname == \"U\":\n resname = \"URA\"\n\n if atomname == \"H5'1\":\n atomname = \"H5'\"\n elif atomname == \"H5'2\":\n atomname = \"H5''\"\n elif atomname == \"H2'1\":\n atomname = \"H2'\"\n elif atomname in [\"H2'2\", \"HO'2\"]:\n atomname = \"H2''\"\n\n if residue.getAtom(\"O2'\") is None:\n if atomname in [\"C2'\", \"H2'\", \"H2''\"]: resname = \"DEO1\"\n\n if residue.getAtom(\"H5T\") is not None:\n if atomname in [\"H5T\", \"O5'\", \"C5'\"]: resname = \"5TER\"\n if residue.getAtom(\"H3T\") is not None:\n if atomname in [\"H3T\", \"O3'\", \"C3'\"]: resname = \"3TER\"\n\n # Terminal/Water Substitutions\n\n if residue.get(\"isNterm\"):\n if resname == \"GLY\" and atomname in [\"N\", \"H\", \"H2\", \"H3\", \"CA\", \"HA2\", \"HA3\"]:\n resname = \"GLYP\"\n if atomname == \"H\":\n atomname = \"HT1\"\n elif atomname == \"H2\":\n atomname = \"HT2\"\n elif atomname == \"H3\":\n atomname = \"HT3\"\n elif resname == \"PRO\" and atomname in [\"N\", \"HN1\", \"HN2\", \"CD\", \"CA\", \"HD1\", \"HD2\", \"HA\", \"H2\", \"H3\"]:\n resname = \"PROP\"\n if atomname == \"H2\":\n atomname = \"HN1\"\n elif atomname == \"H3\":\n atomname = \"HN2\"\n elif resname == \"ACE\":\n if atomname == \"CH3\":\n atomname = \"CAY\"\n elif atomname == \"HH31\":\n atomname = \"HY1\"\n elif atomname == \"HH32\":\n atomname = \"HY2\"\n elif atomname == \"HH33\":\n atomname = \"HY3\"\n elif atomname == \"C\":\n atomname = \"CY\"\n elif atomname == \"O\":\n atomname = \"OY\"\n else:\n if atomname in [\"N\", \"H\", \"H2\", \"H3\", \"CA\", \"HA\"]:\n resname = \"NTER\"\n if atomname == \"H\":\n atomname = \"HT1\"\n elif atomname == \"H2\":\n atomname = \"HT2\"\n elif atomname == \"H3\":\n atomname = \"HT3\"\n elif residue.get(\"isCterm\"):\n if atomname in [\"O\", \"OXT\", \"C\"]:\n resname = \"CTER\"\n if atomname == \"O\":\n atomname = \"OT1\"\n elif atomname == \"OXT\":\n atomname = \"OT2\"\n elif residue.get(\"type\") == 3:\n resname = \"TP3M\"\n if atomname == \"O\": atomname = \"OH2\"\n\n # Residue substitutions\n\n if resname == \"ILE\":\n if atomname == \"CD1\":\n atomname = \"CD\"\n elif atomname == \"HD11\":\n atomname = \"HD1\"\n elif atomname == \"HD12\":\n atomname = \"HD2\"\n elif atomname == \"HD13\":\n atomname = \"HD3\"\n elif atomname == \"HG12\":\n atomname = \"HG11\"\n elif atomname == \"HG13\":\n atomname = \"HG12\"\n elif resname == \"CYS\" and \"HG\" not in residue.get(\"map\"):\n resname = \"CYS\"\n if atomname == \"CB\":\n resname = \"DISU\"\n atomname = \"1CB\"\n elif atomname == \"SG\":\n resname = \"DISU\"\n atomname = \"1SG\"\n elif resname == \"HIS\":\n if \"HD1\" in residue.get(\"map\") and \"HE2\" in residue.get(\"map\"):\n resname = \"HSP\"\n elif \"HD1\" in residue.get(\"map\"):\n resname = \"HSD\"\n elif \"HE2\" in residue.get(\"map\"):\n resname = \"HSE\"\n elif resname == \"GLU\" or resname == \"GLH\":\n if \"HE1\" in residue.get(\"map\"):\n if atomname == \"HE1\":\n atomname = \"HE2\"\n elif atomname == \"OE1\":\n atomname = \"OE2\"\n elif atomname == \"OE2\":\n atomname = \"OE1\"\n if atomname in [\"CG\", \"HG3\", \"HG1\", \"HG2\", \"CD\", \"OE1\", \"OE2\", \"HE2\"]:\n resname = \"GLUP\"\n else:\n resname = \"GLU\"\n elif \"HE2\" in residue.get(\"map\"):\n if atomname in [\"CG\", \"HG3\", \"HG1\", \"HG2\", \"CD\", \"OE1\", \"OE2\", \"HE2\"]:\n resname = \"GLUP\"\n else:\n resname = \"GLU\"\n elif resname == \"ASP\" or resname == \"ASH\":\n if \"HD1\" in residue.get(\"map\"):\n if atomname == \"HD1\":\n atomname = \"HD2\"\n elif atomname == \"OD1\":\n atomname = \"OD2\"\n elif atomname == \"OD2\":\n atomname = \"OD1\"\n if atomname in [\"CB\", \"HB3\", \"HB1\", \"HB2\", \"CG\", \"OD1\", \"OD2\", \"HD2\"]:\n resname = \"ASPP\"\n else:\n resname = \"ASP\"\n elif \"HD2\" in residue.get(\"map\"):\n if atomname in [\"CB\", \"HB3\", \"HB1\", \"HB2\", \"CG\", \"OD1\", \"OD2\", \"HD2\"]:\n resname = \"ASPP\"\n else:\n resname = \"ASP\"\n\n # HETATM Substitutions\n\n if resname == \"ACE\":\n if atomname == \"CH3\":\n atomname = \"CAY\"\n elif atomname == \"HH31\":\n atomname = \"HY1\"\n elif atomname == \"HH32\":\n atomname = \"HY2\"\n elif atomname == \"HH33\":\n atomname = \"HY3\"\n elif atomname == \"C\":\n atomname = \"CY\"\n elif atomname == \"O\":\n atomname = \"OY\"\n elif resname == \"ADP\":\n atomname = atomname.replace(\"*\", \"\\'\")\n elif resname == \"NME\":\n resname = \"CT3\"\n if atomname == \"HH31\":\n atomname = \"HT1\"\n elif atomname == \"HH32\":\n atomname = \"HT2\"\n elif atomname == \"HH33\":\n atomname = \"HT3\"\n elif atomname == \"CH3\":\n atomname = \"CAT\"\n elif atomname == \"N\":\n atomname = \"NT\"\n elif atomname == \"H\":\n atomname = \"HNT\"\n\n # Hydrogen Substitutions\n\n if atomname == \"H\":\n atomname = \"HN\"\n elif atomname == \"HA2\":\n atomname = \"HA1\"\n elif atomname == \"HA3\":\n atomname = \"HA2\"\n elif atomname == \"HB2\" and resname not in [\"ALA\"]:\n atomname = \"HB1\"\n elif atomname == \"HB3\" and resname not in [\"ALA\"]:\n atomname = \"HB2\"\n elif atomname == \"HD2\" and resname not in [\"HSP\", \"HSE\", \"HSD\", \"ASPP\"]:\n atomname = \"HD1\"\n elif atomname == \"HD3\" and resname not in [\"HIS\", \"HSE\", \"HSD\"]:\n atomname = \"HD2\"\n elif atomname == \"HE2\" and resname not in [\"TRP\", \"HSP\", \"HSE\", \"HSD\", \"GLUP\"]:\n atomname = \"HE1\"\n elif atomname == \"HE3\" and resname not in [\"TRP\", \"HSP\", \"HSE\", \"HSD\"]:\n atomname = \"HE2\"\n elif atomname == \"HG2\":\n atomname = \"HG1\"\n elif atomname == \"HG3\":\n atomname = \"HG2\"\n elif atomname == \"HG\" and resname in [\"SER\", \"CYS\"]:\n atomname = \"HG1\"\n\n return resname, atomname","def calculate_returns(data):\n pass","def test_generate_spin_id_data_array1(self):\n\n # The data.\n data = ['1', 'GLY']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')","def coords_to_residue(self, rnext: bool = ...) -> None:\n ...","def getResidueInformation(self, resIDs=None, atomIDs=None):\n if resIDs is None:\n resIDs = set ()\n else:\n resIDs = set (resIDs)\n\n if atomIDs is not None:\n for i in atomIDs:\n resIDs.add (self._atomInfo[i][\"residue\"])\n return self.getResidueInformation (resIDs=resIDs)\n\n resIDs = list (resIDs)\n resIDs.sort ()\n str=''\n for res in resIDs:\n str=str+self._residueInfo[res][\"name\"]\n print self._shortenResidue (str)\n str = ''\n return dict ((resID, self._residueInfo[resID]) for resID in resIDs)","def is_standard_residue(self):\n return True","def is_standard_residue(self):\n return True","def residuez(b, a, tol=1e-3, rtype='avg'):\n\n if (cupy.issubdtype(b.dtype, cupy.complexfloating)\n or cupy.issubdtype(a.dtype, cupy.complexfloating)):\n b = b.astype(complex)\n a = a.astype(complex)\n else:\n b = b.astype(float)\n a = a.astype(float)\n\n b = cupy.trim_zeros(cupy.atleast_1d(b), 'b')\n a = cupy.trim_zeros(cupy.atleast_1d(a), 'b')\n\n if a.size == 0:\n raise ValueError(\"Denominator `a` is zero.\")\n elif a[0] == 0:\n raise ValueError(\"First coefficient of determinant `a` must be \"\n \"non-zero.\")\n\n poles = roots(a)\n if b.size == 0:\n return cupy.zeros(poles.shape), _cmplx_sort(poles)[0], cupy.array([])\n\n b_rev = b[::-1]\n a_rev = a[::-1]\n\n if len(b_rev) < len(a_rev):\n k_rev = cupy.empty(0)\n else:\n k_rev, b_rev = _polydiv(b_rev, a_rev)\n\n unique_poles, multiplicity = unique_roots(poles, tol=tol, rtype=rtype)\n unique_poles, order = _cmplx_sort(unique_poles)\n multiplicity = multiplicity[order]\n\n residues = _compute_residues(1 / unique_poles, multiplicity, b_rev)\n\n index = 0\n powers = cupy.empty(len(residues), dtype=int)\n for pole, mult in zip(unique_poles, multiplicity):\n poles[index:index + mult] = pole\n powers[index:index + mult] = 1 + cupy.arange(int(mult))\n index += mult\n\n residues *= (-poles) ** powers / a_rev[0]\n\n return residues, poles, k_rev[::-1]","def _result_wrapper(self, result, _pymatgen) -> List[ase.atoms.Atoms]:\n if _pymatgen:\n _, fname = tempfile.mkstemp(text=True)\n with open(fname, \"w\") as f:\n f.write(result.to(\"poscar\"))\n return ase.io.read(fname, index=':', format=\"vasp\")\n else:\n import json\n result = json.load(result)\n if result[\"valid_response\"]:\n _, fname = tempfile.mkstemp(text=True)\n with open(fname, \"w\") as f:\n f.write(result[\"response\"][0][\"cif\"])\n return ase.io.read(fname, index=':', format=\"cif\")\n elif not result[\"api_key_valid\"]:\n raise ValueError(f\"Invalid API_KEY: {self.API_KEY}. Check your API_KEY at https://www.materialsproject.org/open!\")","def test_perceive_residues_natoms_t4(self, strict_chirality):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/T4-protein.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def get_residue_coords(self, resnum):\n return","def endElement(self, name):\n if name == \"residue\":\n if self.oldresname is not None: # Make a new residue hook\n\n newreslist = self.findMatchingNames(self.newresname, self.reference)\n if self.oldresname.find(\"$group\") >= 0: # Multiple new residues\n for resitem in newreslist:\n resname = resitem.string\n group = resitem.group(1)\n fromname = self.oldresname.replace(\"$group\", group)\n if fromname in self.map:\n self.updateMap(resname, fromname, self.map)\n\n else: # Work with a single new residue name\n oldreslist = self.findMatchingNames(self.oldresname, self.map)\n for resitem in newreslist:\n resname = resitem.string\n self.updateMap(resname, self.oldresname, self.map)\n\n # If this was only a residue conversion, exit\n\n if self.atommap == {}:\n self.oldresname = None\n self.newresname = None\n return\n\n # Apply atom conversions for all appropriate residues\n\n resmatchlist = self.findMatchingNames(self.newresname, self.map)\n for resitem in resmatchlist:\n residue = self.map[resitem.string]\n for newname in self.atommap:\n oldname = self.atommap[newname]\n if oldname not in residue.atoms: continue\n self.updateMap(newname, oldname, residue.atoms)\n\n # Clean up\n\n self.oldresname = None\n self.newresname = None\n self.atommap = {}\n\n elif name == \"atom\":\n\n self.atommap[self.newatomname] = self.oldatomname\n self.oldatomname = None\n self.newatomname = None\n\n else: # Just free the current element namespace\n self.curelement = \"\"\n\n return self.map","def residueList(self):\n\n\t\trl = []\n\t\tfor chain in self.chain:\n\t\t\tfor res in chain.residue:\n\t\t\t\trl.append(res)\n\n\t\treturn rl","def test_return_all(self):\n self.data.return_all()","def test_rsun(eit_map):\n assert u.allclose(eit_map.rsun_obs, 979.0701*u.arcsec)","def test_futures_loan_collateral_repay_result():\n\n client = Client(key, secret)\n response = client.futures_loan_collateral_repay_result(**params)\n response.should.equal(mock_item)","def testrescorr():\n tau = np.zeros((2,50))\n tau[0,25] = 2\n tau[1,23] = 3\n tau2 = spec_utils.res_corr(tau, 2, 8)\n #Check flux conserved\n assert np.abs(np.sum(tau2[0,:])/ np.sum(tau[0,:]) -1) < 1e-6\n assert np.abs(np.sum(tau2[1,:])/ np.sum(tau[1,:]) -1) < 1e-6\n #Check expanded by expected amount\n for i in (0,1):\n assert np.size(np.where(tau2[i,:]> 0)) == 15","def test_vault_get_vault_item(self):\n pass","def test_assign_resources_to_tmc_subarray_in_mid():","def setUp(self):\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Name the first molecule.\n cdp.mol[0].name = 'Ap4Aase'\n\n # Add a second molecule to the system.\n cdp.mol.add_item(mol_name='RNA')\n\n # Add two more residues to the first molecule (and set the residue number of the first).\n cdp.mol[0].res[0].num = 1\n cdp.mol[0].res.add_item(res_num=2, res_name='Glu')\n cdp.mol[0].res.add_item(res_num=4, res_name='Pro')\n\n # Add some spin info to this molecule.\n cdp.mol[0].res[0].spin[0].name = 'NH'\n cdp.mol[0].res[0].spin[0].num = 60\n cdp.mol[0].res[1].spin[0].name = 'NH'\n cdp.mol[0].res[1].spin[0].num = 63\n\n # Add one more residue to the second molecule (and set the residue number of the first).\n cdp.mol[1].res[0].num = -5\n cdp.mol[1].res.add_item(res_num=-4)\n\n # Add a second set of spins to the second molecule (naming the first set first).\n cdp.mol[1].res[0].spin[0].name = 'C8'\n cdp.mol[1].res[1].spin[0].name = 'C8'\n cdp.mol[1].res[0].spin.add_item(spin_name='N5')\n cdp.mol[1].res[1].spin.add_item(spin_name='N5')\n cdp.mol[1].res[1].spin.add_item(spin_name='2H', spin_num=132)\n\n # Deselect a number of spins.\n cdp.mol[0].res[0].spin[0].select = 0\n cdp.mol[0].res[2].spin[0].select = 0\n cdp.mol[1].res[0].spin[0].select = 0\n cdp.mol[1].res[1].spin[1].select = 0\n\n # Update the metadata.\n mol_res_spin.metadata_update()","def is_standard_residue(self):\n return False","def test_xyzp_qm_7b():\n subject = subject7\n\n with pytest.raises(qcelemental.MoleculeFormatError):\n final, intermed = qcelemental.molparse.from_string(subject, return_processed=True, dtype='xyz')","def test_rescore_unmask(self):\r\n module = CapaFactory.create(xml=self.common_shuffle_xml)\r\n get_request_dict = {CapaFactory.input_key(): 'mask_0'}\r\n module.check_problem(get_request_dict)\r\n # On rescore, state/student_answers should use unmasked names\r\n with patch.object(module.runtime, 'track_function') as mock_track_function:\r\n module.rescore_problem()\r\n mock_call = mock_track_function.mock_calls[0]\r\n event_info = mock_call[1][1]\r\n self.assertEquals(mock_call[1][0], 'problem_rescore')\r\n self.assertEquals(event_info['state']['student_answers'][CapaFactory.answer_key()], 'choice_2')\r\n self.assertIsNotNone(event_info['permutation'][CapaFactory.answer_key()])","def test_get_solution(self):\n pass","async def test_get_chr_assembly(test_db):\n resp = await test_db.get_chr_assembly(\"NC_000007.13\")\n assert resp == (\"chr7\", \"GRCh37\")\n\n resp = await test_db.get_chr_assembly(\"NC_000007.14\")\n assert resp is None","def __call__(self, mol):\n return self.choose(mol)","def residLike(self):\n\n # --------------------------------------------------------------------------------------------- #\n # Compute the residuals\n if self.csys == 'GAL':\n # Redo some file computations with this coordinate system\n self.outbinexp = os.path.join(self.workpath, 'BinExpMapGAL'+self.suffix+'.fits')\n self.outbincub = os.path.join(self.workpath, 'BinCubeGAL'+self.suffix+'.fits')\n self.outsrcmap = os.path.join(self.workpath, 'SrcMapsGAL'+self.suffix+'.fits')\n self.outresid = os.path.join(self.workpath, 'ResidGAL'+self.suffix+'.fits')\n self.outresig = os.path.join(self.workpath, 'ResSigmaGAL'+self.suffix+'.fits')\n\n self._gtExpmap()\n self._gtBincube()\n self._gtSrcmap()\n else:\n # Nothing to add\n pass\n \n self._gtBinmap()\n self._gtModel()\n # Create the residual count map (count_map - model_map)\n if not os.path.isfile(self.outresid):\n os.popen(\"farith {} {} {} ops=SUB\".format(self.outbinmap, self.outgtmod,\n self.outresid))\n # Create the sigma-residual map (residual_map/sqrt(model_map))\n if not os.path.isfile(self.outresig):\n os.popen(\"ftpixcalc {} '(a-b)/sqrt(b)' a={} b={}\".format(self.outresig,\n self.outbinmap, self.outgtmod))\n\n # --------------------------------------------------------------------------------------------- #\n # Get the sources to overplot\n srcs = self.getSrc()\n srcs = srcs[(srcs['Separation'] <= 3.) & ([not i.endswith('c') for i in srcs['Name']])]\n # Plot the residuals\n resplt1 = FermiMap()\n resplt1.savepath = self.workpath\n resplt1.image = self.outresig\n resplt1.figname = 'ResSigma.pdf'\n dmin, dmax = np.abs(resplt1.datamin), resplt1.datamax\n resplt1.datamin = - min(dmin, dmax)\n resplt1.datamax = + min(dmin, dmax)\n resplt1.cbarlabel = r'Residual $\\sigma$/pixel'\n resplt1.mapSky()\n resplt1.srcSky(srcs['RA'], srcs['DEC'], srcs['Name'])\n resplt1.save()\n print(\"\\t=== Figure '{}' created ===\".format( os.path.join(resplt1.savepath, resplt1.figname) ))\n\n resplt2 = FermiMap()\n resplt2.savepath = self.workpath\n resplt2.image = self.outresid\n resplt2.figname = 'Residuals.pdf'\n dmin, dmax = np.abs(resplt2.datamin), resplt2.datamax\n resplt2.datamin = - min(dmin, dmax)\n resplt2.datamax = + min(dmin, dmax)\n resplt2.cbarlabel = r'Residual counts/pixel'\n resplt2.mapSky()\n resplt2.srcSky(srcs['RA'], srcs['DEC'], srcs['Name'])\n resplt2.save()\n print(\"\\t=== Figure '{}' created ===\".format( os.path.join(resplt2.savepath, resplt2.figname) ))\n return","def test_molecule_loop_no_selection(self):\n\n # Molecule data.\n name = ['Ap4Aase', 'RNA']\n\n # Loop over the molecules.\n i = 0\n for mol in mol_res_spin.molecule_loop():\n # Test the molecule names.\n self.assertEqual(mol.name, name[i])\n\n # Increment i.\n i = i + 1\n\n # Test loop length.\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)","def test_rotamer_library_builder(self):\n LIGAND_PATH = 'ligands/oleic_acid.pdb'\n\n ligand_path = get_data_file_path(LIGAND_PATH)\n molecule = Molecule(ligand_path, exclude_terminal_rotamers=False)\n\n # rotamer_library = RotamerLibrary(molecule)\n\n rotamers_per_branch = molecule.rotamers\n\n assert len(rotamers_per_branch) == 2, \"Found an invalid number \" + \\\n \"of branches: {}\".format(len(rotamers_per_branch))\n\n atom_list_1 = list()\n atom_list_2 = list()\n\n rotamers = rotamers_per_branch[0]\n for rotamer in rotamers:\n atom_list_1.append(set([rotamer.index1, rotamer.index2]))\n\n rotamers = rotamers_per_branch[1]\n for rotamer in rotamers:\n atom_list_2.append(set([rotamer.index1, rotamer.index2]))\n\n EXPECTED_INDICES_1 = [set([9, 10]), set([8, 9]), set([7, 8]),\n set([6, 7]), set([5, 6]), set([2, 5]),\n set([0, 2]), set([0, 1])]\n\n EXPECTED_INDICES_2 = [set([12, 11]), set([12, 13]), set([13, 14]),\n set([14, 15]), set([15, 16]), set([16, 17]),\n set([17, 18]), set([18, 19])]\n\n where_1 = list()\n for atom_pair in atom_list_1:\n if atom_pair in EXPECTED_INDICES_1:\n where_1.append(1)\n elif atom_pair in EXPECTED_INDICES_2:\n where_1.append(2)\n else:\n where_1.append(0)\n\n where_2 = list()\n for atom_pair in atom_list_2:\n if atom_pair in EXPECTED_INDICES_1:\n where_2.append(1)\n elif atom_pair in EXPECTED_INDICES_2:\n where_2.append(2)\n else:\n where_2.append(0)\n\n assert (all(i == 1 for i in where_1)\n and all(i == 2 for i in where_2)) or \\\n (all(i == 2 for i in where_1)\n and all(i == 1 for i in where_2)), \"Invalid rotamer library \" + \\\n \"{}, {}\".format(where_1, where_2)\n\n assert (all(i == 1 for i in where_1)\n and all(i == 2 for i in where_2)\n and len(where_1) == len(EXPECTED_INDICES_1)\n and len(where_2) == len(EXPECTED_INDICES_2)) or \\\n (all(i == 2 for i in where_1)\n and all(i == 1 for i in where_2)\n and len(where_1) == len(EXPECTED_INDICES_2)\n and len(where_2) == len(EXPECTED_INDICES_1)), \"Unexpected \" + \\\n \"number of rotamers\"","def test_perceive_residues_natoms_mainchain_charged_glutamic_acid(\n self, strict_chirality\n ):\n offmol = Molecule.from_file(get_data_file_path(\"proteins/MainChain_GLH.sdf\"))\n # Perceive residue substructures\n offmol.perceive_residues(strict_chirality=strict_chirality)\n counter = 0 # matched atom counter\n for atom in offmol.atoms:\n if atom.metadata:\n counter += 1\n assert counter == offmol.n_atoms","def test_xyzp_qm_7a():\n subject = subject7\n\n with pytest.raises(qcelemental.MoleculeFormatError):\n final, intermed = qcelemental.molparse.from_string(subject, return_processed=True, dtype='psi4')","def determine_matched_residue_positions(match_pdb_path):\n positions_block = os.path.basename(os.path.normpath(match_pdb_path)).split('_')[2]\n resnames = [a for a in re.split(\"[0-9]*\", positions_block) if a]\n resnums = [int(a) for a in re.split(\"[a-zA-Z]*\", positions_block) if a]\n\n return [(a, b) for a, b in zip(resnames, resnums)]","def test_check_map_primer_pool(self):\r\n s = \"\"\"#SampleID\\tBarcodeSequence\\tLinkerPrimerSequence\\tX\\tDescription\r\n#fake data\r\nx\\tAA\\tAC\\t3\\tsample_x\r\ny\\t\"AC\"\\tAT,DC\\t4\\t\"sample_y\"\r\nz\\tGG\\tGC\\t5\\tsample_z\"\"\"\r\n f = StringIO(s)\r\n f.name = 'test.xls'\r\n headers, id_map, barcode_to_sample_id, warnings, errors, \\\r\n primer_seqs_lens, all_primers = check_map(f,\r\n disable_primer_check=False)\r\n\r\n self.assertEqual(\r\n barcode_to_sample_id,\r\n {'AA': 'x',\r\n 'AC': 'y',\r\n 'GG': 'z'})\r\n self.assertEqual(errors, [])\r\n self.assertEqual(warnings, [])\r\n\r\n # Returns all possible primers with lengths associated.\r\n expected_all_primers = {'AC': 2, 'GC': 2, 'AT': 2, 'TC': 2}\r\n self.assertEqual(all_primers, expected_all_primers)\r\n\r\n # Returns all primers associated with each barcode.\r\n expected_primer_seqs_lens = {'AA': {'AC': 2}, 'GG': {'GC': 2},\r\n 'AC': {'AC': 2, 'GC': 2, 'AT': 2, 'TC': 2}}\r\n\r\n self.assertEqual(primer_seqs_lens, expected_primer_seqs_lens)","def test_2_return(self):\n plan = list(astar(self.mapp_1_s,\n lambda s : s == self.mapp_1_s,\n MAPPDistanceSum(self.mapp_1_s)))\n self.assertEqual(len(plan),0)","def torchani(ret_data):\n\n import numpy as np\n import torch\n import torchani\n\n device = torch.device('cpu')\n builtin = torchani.neurochem.Builtins()\n\n # Failure flag\n ret_data[\"success\"] = False\n\n # Build model\n model = get_model(ret_data[\"model\"][\"method\"])\n if model is False:\n ret_data[\"error_message\"] = \"run_torchani only accepts the ANI1 method.\"\n return ret_data\n\n # Build species\n species = \"\".join(ret_data[\"molecule\"][\"symbols\"])\n unknown_sym = set(species) - {\"H\", \"C\", \"N\", \"O\"}\n if unknown_sym:\n ret_data[\"error_message\"] = \"The '{}' model does not support symbols: {}.\".format(\n ret_data[\"model\"][\"method\"], unknown_sym)\n return ret_data\n\n species = builtin.consts.species_to_tensor(species).to(device).unsqueeze(0)\n\n # Build coord array\n geom_array = np.array(ret_data[\"molecule\"][\"geometry\"]).reshape(1, -1, 3) * units.bohr_to_angstrom\n coordinates = torch.tensor(geom_array.tolist(), requires_grad=True, device=device)\n\n _, energy = model((species, coordinates))\n ret_data[\"properties\"] = {\"return_energy\": energy.item()}\n\n if ret_data[\"driver\"] == \"energy\":\n ret_data[\"return_result\"] = ret_data[\"properties\"][\"return_energy\"]\n elif ret_data[\"driver\"] == \"gradient\":\n derivative = torch.autograd.grad(energy.sum(), coordinates)[0].squeeze()\n ret_data[\"return_result\"] = np.asarray(derivative / units.bohr_to_angstrom).ravel().tolist()\n else:\n ret_data[\"error_message\"] = \"run_torchani did not understand driver method '{}'.\".format(ret_data[\"driver\"])\n return ret_data\n\n ret_data[\"provenance\"] = {\"creator\": \"torchani\", \"version\": \"unknown\", \"routine\": \"torchani.builtin.aev_computer\"}\n\n ret_data[\"schema_name\"] = \"qc_schema_output\"\n ret_data[\"success\"] = True\n\n return ret_data","def _get_2D_by_pubchem(self, code, mol):\n try:\n template_path = self._get_pubchem_template_path(code)\n if template_path:\n template = self._load_template(template_path)\n\n if mol.HasSubstructMatch(template):\n AllChem.GenerateDepictionMatching2DStructure(mol, template)\n flaws = DepictionValidator(mol).depiction_score()\n return DepictionResult(\n source=DepictionSource.PubChem,\n template_name=code,\n mol=mol,\n score=flaws,\n )\n except Exception as e:\n print(str(e), file=sys.stderr)\n\n return DepictionResult(\n source=DepictionSource.Failed, template_name=None, mol=None, score=1000\n )","def test_ipam_rirs_read(self):\n pass","def test_get_primers(self):\r\n\r\n # Raise error if ReversePrimer not supplied\r\n header = ['SampleID', 'BarcodeSequence', 'LinkerPrimerSequence',\r\n 'Description']\r\n mapping_data = [['s1', 'ATCG', 'TTGGCC,TTGGWC', 'ATRCCTA']]\r\n self.assertRaises(IndexError, get_primers, header, mapping_data)\r\n\r\n header = ['SampleID', 'BarcodeSequence', 'LinkerPrimerSequence',\r\n 'ReversePrimer', 'Description']\r\n forward_primers, reverse_primers = get_primers(header, mapping_data)\r\n\r\n forward_primers = set([seq.pattern for seq in forward_primers])\r\n reverse_primers = set([seq.pattern for seq in reverse_primers])\r\n\r\n expected_forward_primers = set(['TTGGCC', 'TAGG[CT]AT', 'TTGG[AT]C'])\r\n expected_reverse_primers = set(['GGCCAA', 'AT[AG]CCTA', 'G[AT]CCAA'])\r\n\r\n self.assertEqual(forward_primers, expected_forward_primers)\r\n self.assertEqual(reverse_primers, expected_reverse_primers)","def __init__(self, atomlist):\n\n self.residues = []\n\n current_res = atomlist[0].res_id\n\n temp_res =[]\n\n for i in atomlist:\n if i.res_id == current_res:\n temp_res.append(i)\n else:\n self.residues.append(PDB_residue(temp_res))\n temp_res = []\n current_res = i.res_id\n temp_res.append(i)\n \n \n\n self.residues.append(PDB_residue(temp_res)) # get final residue\n\n if len(self.residues) > 0: \n self.chain_name = self.residues[0].chain\n else:\n self.chain_name = None\n \n chain_local_id = 1 \n\n ## CHAIN LOCAL ID variables in atom and residue\n ## objects are set here!\n ##\n for res in self.residues:\n for atom in res.atoms:\n atom.chain_local_id = chain_local_id\n res.chain_local_id = chain_local_id\n chain_local_id=chain_local_id+1","def residue_subsystem():\n net = residue_network()\n state = (0, 0, 0, 0, 0)\n return Subsystem(net, state)"],"string":"[\n \"def test_return_single_residue_info(self):\\n\\n # Ask for a few residues.\\n res1 = mol_res_spin.return_single_residue_info('1')\\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\\n res5 = mol_res_spin.return_single_residue_info('-5')\\n\\n # Test the data of residue 1.\\n self.assertEqual(res1, (1, None))\\n\\n # Test the data of residue 2.\\n self.assertEqual(res2, (2, 'Glu'))\\n\\n # Test the data of residue 4.\\n self.assertEqual(res4, (4, 'Pro'))\\n\\n # Test the data of the RNA residue -5.\\n self.assertEqual(res5, (-5, None))\",\n \"def test_return_molecule(self):\\n\\n # Ask for a few molecules.\\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\\n\\n # Test the data of molecule 1.\\n self.assertEqual(mol1.name, 'Ap4Aase')\\n\\n # Test the data of molecule 2.\\n self.assertEqual(mol2.name, 'RNA')\",\n \"def test_return_single_residue_info_fail(self):\\n\\n # Ask for a few residues.\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,Glu,Pro')\\n self.assertRaises(RelaxError, mol_res_spin.return_single_residue_info, '1,2,Glu,Pro')\",\n \"def test_return_residue_pipe_fail(self):\\n\\n # Try to get a residue from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_residue, selection=':2', pipe='new')\",\n \"def test_residue_loop_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Loop over the residues.\\n i = 0\\n for residue in mol_res_spin.residue_loop():\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 0)\",\n \"def test_return_spin(self):\\n\\n # Ask for a few spins.\\n spin1 = mol_res_spin.return_spin('#Ap4Aase:1')\\n spin2 = mol_res_spin.return_spin(spin_id='#Ap4Aase:2')\\n spin3 = mol_res_spin.return_spin(spin_id='#Ap4Aase:4', pipe='orig')\\n spin4 = mol_res_spin.return_spin(spin_id='#RNA:-5@N5', pipe='orig')\\n spin5 = mol_res_spin.return_spin(spin_id='#RNA:-4@2H', pipe='orig')\\n\\n # Test the data of spin 1.\\n self.assertNotEqual(spin1, None)\\n self.assertEqual(spin1.num, 60)\\n self.assertEqual(spin1.name, 'NH')\\n\\n # Test the data of spin 2.\\n self.assertNotEqual(spin2, None)\\n self.assertEqual(spin2.num, 63)\\n self.assertEqual(spin2.name, 'NH')\\n\\n # Test the data of spin 3.\\n self.assertNotEqual(spin3, None)\\n self.assertEqual(spin3.num, None)\\n self.assertEqual(spin3.name, None)\\n\\n # Test the data of the RNA res -5, spin N5.\\n self.assertNotEqual(spin4, None)\\n self.assertEqual(spin4.num, None)\\n self.assertEqual(spin4.name, 'N5')\\n\\n # Test the data of the RNA res -4, spin 2H.\\n self.assertNotEqual(spin5, None)\\n self.assertEqual(spin5.num, 132)\\n self.assertEqual(spin5.name, '2H')\",\n \"def test_residue_loop(self):\\n\\n # Loop over the residues.\\n for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):\\n # Test the selection.\\n self.assertEqual(res.num, 2)\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)\",\n \"def test_exists_mol_res_spin_data_single_res_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first residue.\\n dp.mol[0].res[0].num = 1\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_exists_mol_res_spin_data_single_mol(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first molecule.\\n dp.mol[0].name = 'TOM40'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_residue_loop_no_selection(self):\\n\\n # Spin data.\\n num = [1, 2, 4, -5, -4]\\n name = [None, 'Glu', 'Pro', None, None]\\n\\n # Loop over the residues.\\n i = 0\\n for res in mol_res_spin.residue_loop():\\n # Test the residue numbers.\\n self.assertEqual(res.num, num[i])\\n\\n # Test the residue names.\\n self.assertEqual(res.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(i, 5)\",\n \"def residue(res_name):\\n _init_dataset()\\n array_dict = _residues[res_name]\\n\\n array = AtomArray(len(array_dict[\\\"res_name\\\"]))\\n\\n array.res_name = array_dict[\\\"res_name\\\"]\\n array.atom_name = array_dict[\\\"atom_name\\\"]\\n array.element = array_dict[\\\"element\\\"]\\n array.charge = array_dict[\\\"charge\\\"]\\n array.hetero = array_dict[\\\"hetero\\\"]\\n\\n array.coord[:,0] = array_dict[\\\"coord_x\\\"]\\n array.coord[:,1] = array_dict[\\\"coord_y\\\"]\\n array.coord[:,2] = array_dict[\\\"coord_z\\\"]\\n\\n array.bonds = BondList(\\n array.array_length(),\\n bonds = np.stack([\\n array_dict[\\\"bond_i\\\"],\\n array_dict[\\\"bond_j\\\"],\\n array_dict[\\\"bond_type\\\"]\\n ]).T\\n )\\n\\n return array\",\n \"def test_exists_mol_res_spin_data_single_res_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first residue.\\n dp.mol[0].res[0].name = 'Lys'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def residue(self, resnum, chain_id, icode=' ', alt=' ', model_num = 0):\\n res = self.struct[model_num][chain_id][(alt, resnum, icode)]\\n res.chain_id = chain_id\\n return res\",\n \"def get_residue(self, chainid, resid) :\\n if not self._res_dict :\\n d = {}\\n for r in self.residues :\\n d[ (r.chainid, r.resid)] = r\\n self._res_dict =d\\n \\n return self._res_dict[(chainid, resid)]\",\n \"def check_residue(self, chain_id, resid, resname):\\n if resname in PTM_lookup.keys():\\n return\\n else:\\n try:\\n ref_resname = PTM_reverse_lookup[resname]\\n except KeyError:\\n # print \\\"skipping unrecognized residue\\\", resname\\n return\\n ptm_dict = PTM_lookup[ref_resname][resname]\\n return (chain_id, resid, ref_resname, ptm_dict[\\\"goto_atom\\\"], ptm_dict[\\\"name\\\"])\",\n \"def test_exists_mol_res_spin_data_single_spin_num(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Number the first spin.\\n dp.mol[0].res[0].spin[0].num = 234\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def check_residue_callback(self):\\n\\n if not self.check_for_residue_existance():\\n return\\n\\n self.listbox_current_designs.delete(0, END)\\n self.current_residueFull = self.current_residue.get().split(\\\":\\\")\\n\\n if len(self.current_residueFull) > 1:\\n self.listbox_restypes.delete(9)\\n self.listbox_restypes.insert(9, \\\"Conserved\\\")\\n else:\\n res = self.current_residueFull[0] +\\\":\\\"+self.current_chain.get()\\n #print res\\n if not self.pose.total_residue():\\n return\\n\\n resType = self.pose.pdb_info().pdb2pose(self.current_chain.get(), int(self.current_residue.get()))\\n try:\\n resName = self.pose.residue(resType).name()\\n except PyRosettaException:\\n print \\\"Residue does not exist in PDB...\\\"\\n return\\n\\n\\n self.current_residue_name_full.set(resName)\\n three_letter_name = resName.split(\\\"_\\\")[0]; #Fix for Rosetta designated chain endings, His_d\\n self.current_residue_name.set(resName)\\n\\n #Fix for not having data for certain residue types:\\n try:\\n self.design_accessible_sa.set(self.residue_definitions.resinfo[three_letter_name][0])\\n self.design_relative_mutability.set(self.residue_definitions.resinfo[three_letter_name][1])\\n self.design_surface_probability.set(self.residue_definitions.resinfo[three_letter_name][2])\\n except KeyError:\\n print \\\"No Data for restype\\\"\\n self.design_accessible_sa.set(\\\"\\\")\\n self.design_relative_mutability.set(\\\"\\\")\\n self.design_surface_probability.set(\\\"\\\")\\n\\n con = \\\"Conserved:\\\" +three_letter_name\\n self.listbox_restypes.delete(9)\\n self.listbox_restypes.insert(9, con)\\n if self.DesignDic.has_key(res):\\n for residues in self.DesignDic[res]:\\n self.listbox_current_designs.insert(END, residues)\",\n \"def test_residue_loop_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Function for the problem of catching an error in a generator function.\\n def fail_test():\\n for residue in mol_res_spin.residue_loop():\\n pass\\n\\n # Test for the no pipe error.\\n self.assertRaises(RelaxNoPipeError, fail_test)\",\n \"def get_residue(self, resid, chainLocal=False):\\n \\n try:\\n resid = int(resid)\\n except ValueError, e:\\n print \\\"ERROR: get_resid() requires a numeric value\\\"\\n raise e\\n \\n\\n if type(resid) == int: \\n \\n if chainLocal:\\n for res in self.residues:\\n if res.chain_local_id == resid: \\n return res\\n else: \\n for res in self.residues:\\n if res.res_id == resid:\\n return res\",\n \"def test_exists_mol_res_spin_data(self):\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def getResAromaticVectors(residues):\\n for res in residues.keys():\\n rtype = res.split(\\\":\\\")[1][0:3] # A:GLY48 => GLY\\n try:\\n if rtype == \\\"PHE\\\" or rtype == \\\"TYR\\\":\\n if len(residues[res]) == 6:\\n pass\\n else:\\n if DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n elif rtype == \\\"TRP\\\":\\n if len(residues[res]) >= 9:\\n residues[res] = purgeTrp(residues[res])\\n else:\\n if DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n elif rtype == \\\"HIS\\\":\\n if len(residues[res]) >= 5:\\n residues[res] = purgeHis(residues[res])\\n else:\\n if DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n elif rtype == \\\"ARG\\\":\\n residues[res] = purgeArg(residues[res])\\n if not residues[res] and DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n elif rtype == \\\"DA\\\" or rtype == \\\"A\\\":\\n if len(residues[res]) >= 10:\\n residues[res] = purgeAdenine(residues[res])\\n else:\\n if DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n elif rtype == \\\"DC\\\" or rtype == \\\"C\\\":\\n if len(residues[res]) >= 6:\\n residues[res] = purgeAdenine(residues[res])\\n else:\\n if DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n elif rtype == \\\"DG\\\" or rtype == \\\"G\\\":\\n if len(residues[res]) >= 10:\\n residues[res] = purgeAdenine(residues[res])\\n else:\\n if DEBUG: print \\\"Warning! Ignoring residue [ %s ] (missing atoms)\\\" % res\\n if residues[res]:\\n residues[res] = atomsToVec(residues[res])\\n else:\\n del residues[res]\\n except:\\n if DEBUG: print \\\"Fatal error in processing residue [ %s ]\\\"% res\\n del residues[res]\\n return residues\",\n \"def test_exists_mol_res_spin_data_single_spin_name(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n dp = pipes.get_pipe('orig')\\n\\n # Name the first spin.\\n dp.mol[0].res[0].spin[0].name = 'NH'\\n\\n # This should be True.\\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())\",\n \"def get_residue_info(self):\\n return\",\n \"def __getitem__(self, residue_number):\\n return self.residues_by_number[residue_number]\",\n \"def test_return_molecule_pipe_fail(self):\\n\\n # Try to get a molecule from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new')\",\n \"def test_RUMI():\\r\\n\\r\\n start = 11051\\r\\n end = 11902\\r\\n read_poems(start, end)\",\n \"def getAmberParams(residue, name):\\n atomname = name\\n type = residue.get(\\\"type\\\")\\n if type == 4:\\n resname = residue.get(\\\"naname\\\")\\n else:\\n resname = residue.get(\\\"name\\\")\\n\\n # Residue Substitutions\\n\\n if residue.get(\\\"name\\\") == \\\"CYS\\\" and \\\"HG\\\" not in residue.get(\\\"map\\\"):\\n resname = \\\"CYX\\\"\\n elif residue.get(\\\"name\\\") == \\\"HIS\\\":\\n if \\\"HD1\\\" in residue.get(\\\"map\\\") and \\\"HE2\\\" in residue.get(\\\"map\\\"):\\n resname = \\\"HIP\\\"\\n elif \\\"HD1\\\" in residue.get(\\\"map\\\"):\\n resname = \\\"HID\\\"\\n elif \\\"HE2\\\" in residue.get(\\\"map\\\"):\\n resname = \\\"HIE\\\"\\n else:\\n resname = \\\"HID\\\" # Default for no hydrogens\\n elif residue.get(\\\"name\\\") == \\\"HSP\\\":\\n resname = \\\"HIP\\\"\\n elif residue.get(\\\"name\\\") == \\\"HSE\\\":\\n resname = \\\"HIE\\\"\\n elif residue.get(\\\"name\\\") == \\\"HSD\\\":\\n resname = \\\"HID\\\"\\n elif residue.get(\\\"name\\\") == \\\"GLU\\\" or residue.get(\\\"name\\\") == \\\"GLH\\\":\\n if \\\"HE1\\\" in residue.get(\\\"map\\\"):\\n resname = \\\"GLH\\\"\\n if atomname == \\\"HE1\\\":\\n atomname = \\\"HE2\\\"\\n elif atomname == \\\"OE1\\\":\\n atomname = \\\"OE2\\\"\\n elif atomname == \\\"OE2\\\":\\n atomname = \\\"OE1\\\"\\n elif \\\"HE2\\\" in residue.get(\\\"map\\\"):\\n resname = \\\"GLH\\\"\\n elif residue.get(\\\"name\\\") == \\\"ASP\\\" or residue.get(\\\"name\\\") == \\\"ASH\\\":\\n if \\\"HD1\\\" in residue.get(\\\"map\\\"):\\n resname = \\\"ASH\\\"\\n if atomname == \\\"HD1\\\":\\n atomname = \\\"HD2\\\"\\n elif atomname == \\\"OD1\\\":\\n atomname = \\\"OD2\\\"\\n elif atomname == \\\"OD2\\\":\\n atomname = \\\"OD1\\\"\\n elif \\\"HD2\\\" in residue.get(\\\"map\\\"):\\n resname = \\\"ASH\\\"\\n\\n if residue.get(\\\"isCterm\\\"):\\n resname = \\\"C\\\" + resname\\n elif residue.get(\\\"isNterm\\\"):\\n resname = \\\"N\\\" + resname\\n\\n # Atom Substitutions\\n\\n if resname == \\\"WAT\\\":\\n if atomname == \\\"O\\\":\\n atomname = \\\"OW\\\"\\n elif atomname == \\\"H1\\\":\\n atomname = \\\"HW\\\"\\n elif atomname == \\\"H2\\\":\\n atomname = \\\"HW\\\"\\n elif resname == \\\"ILE\\\":\\n if atomname == \\\"CD\\\": atomname = \\\"CD1\\\"\\n if resname[0] == \\\"N\\\" and resname != \\\"NME\\\": # N-terminal\\n if atomname == \\\"H\\\": atomname = \\\"H1\\\"\\n if (resname == \\\"CCYS\\\" or resname == \\\"NCYS\\\") and atomname == \\\"HG\\\": atomname = \\\"HSG\\\"\\n if resname == \\\"CYM\\\" and atomname == \\\"H\\\": atomname = \\\"HN\\\"\\n if residue.get(\\\"isNterm\\\") and resname == \\\"NPRO\\\" and atomname == \\\"HN2\\\":\\n atomname = \\\"H2\\\"\\n if residue.get(\\\"isNterm\\\") and resname == \\\"NPRO\\\" and atomname == \\\"HN1\\\":\\n atomname = \\\"H3\\\"\\n return resname, atomname\",\n \"def _residue_from_residue_id(self, residue_id):\\n\\n residues = list(self._data_complex.get_residues())\\n # Select residue of interest\\n # residue.get_id()[2] == \\\" \\\" makes sure that only the first residue is selected in case\\n # there are residues with insertion codes for the residue of interest\\n residue = [\\n residue\\n for residue in residues\\n if (residue.get_id()[1] == residue_id) and (residue.get_id()[2] == \\\" \\\")\\n ]\\n\\n if len(residue) == 1:\\n return residue[0]\\n elif len(residue) == 0:\\n return None\\n else:\\n residue_ids = [residue.get_id()[1] for residue in residues]\\n residue_ids_duplicated = [\\n item for item, count in collections.Counter(residue_ids).items() if count > 1\\n ]\\n raise KeyError(\\n f\\\"{len(residue)} residues were found, but must be 1 or 0. \\\"\\n f\\\"Duplicated residue serial number(s): {residue_ids_duplicated}\\\"\\n )\",\n \"def data(self, pdb, **kwargs):\\n\\n structure = self.structure(pdb)\\n\\n # running infer_hydrogens, but now that is done automatically\\n# structure.infer_hydrogens()\\n\\n for residue in structure.residues():\\n\\n if hasattr(residue, 'rotation_matrix'):\\n matrix = residue.rotation_matrix\\n # if there are not enough atoms for the rotation matrix, it will be None\\n if matrix is not None:\\n yield mod.UnitRotations(unit_id=residue.unit_id(),\\n pdb_id=pdb,\\n cell_0_0=float(matrix[0, 0]),\\n cell_0_1=float(matrix[0, 1]),\\n cell_0_2=float(matrix[0, 2]),\\n cell_1_0=float(matrix[1, 0]),\\n cell_1_1=float(matrix[1, 1]),\\n cell_1_2=float(matrix[1, 2]),\\n cell_2_0=float(matrix[2, 0]),\\n cell_2_1=float(matrix[2, 1]),\\n cell_2_2=float(matrix[2, 2]))\",\n \"def test_exists_mol_res_spin_data_no_pipe(self):\\n\\n # Reset relax.\\n reset()\\n\\n # This should fail.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data)\",\n \"def mutate_residue(pose, mutant_position, mutant_aa,\\n pack_radius = 0.0, pack_scorefxn = '' ):\\n #### a MutateResidue Mover exists similar to this except it does not pack\\n #### the area around the mutant residue (no pack_radius feature)\\n #mutator = MutateResidue(mutant_position, mutant_aa)\\n #mutator.apply(test_pose)\\n\\n if pose.is_fullatom() == False:\\n IOError( 'mutate_residue only works with fullatom poses' )\\n\\n\\n # create a standard scorefxn by default\\n if not pack_scorefxn:\\n pack_scorefxn = rosetta.core.scoring.get_score_function()\\n\\n task = pyrosetta.standard_packer_task(pose)\\n\\n # the Vector1 of booleans (a specific object) is needed for specifying the\\n # mutation, this demonstrates another more direct method of setting\\n # PackerTask options for design\\n aa_bool = rosetta.utility.vector1_bool()\\n # PyRosetta uses several ways of tracking amino acids (ResidueTypes)\\n # the numbers 1-20 correspond individually to the 20 proteogenic amino acids\\n # aa_from_oneletter returns the integer representation of an amino acid\\n # from its one letter code\\n # convert mutant_aa to its integer representation\\n mutant_aa = rosetta.core.chemical.aa_from_oneletter_code(mutant_aa)\\n\\n # mutation is performed by using a PackerTask with only the mutant\\n # amino acid available during design\\n # to do this, construct a Vector1 of booleans indicating which amino acid\\n # (by its numerical designation, see above) to allow\\n for i in range(1, 21):\\n # in Python, logical expression are evaluated with priority, thus the\\n # line below appends to aa_bool the truth (True or False) of the\\n # statement i == mutant_aa\\n aa_bool.append( i == int(mutant_aa) )\\n\\n # modify the mutating residue's assignment in the PackerTask using the\\n # Vector1 of booleans across the proteogenic amino acids\\n task.nonconst_residue_task(mutant_position\\n ).restrict_absent_canonical_aas(aa_bool)\\n\\n # prevent residues from packing by setting the per-residue \\\"options\\\" of\\n # the PackerTask\\n restrict_non_nbrs_from_repacking(pose, mutant_position, task, pack_radius)\\n\\n # apply the mutation and pack nearby residues\\n #print task\\n packer = rosetta.protocols.simple_moves.PackRotamersMover(pack_scorefxn, task)\\n packer.apply(pose)\",\n \"def residue(b, a, tol=1e-3, rtype='avg'):\\n if (cupy.issubdtype(b.dtype, cupy.complexfloating)\\n or cupy.issubdtype(a.dtype, cupy.complexfloating)):\\n b = b.astype(complex)\\n a = a.astype(complex)\\n else:\\n b = b.astype(float)\\n a = a.astype(float)\\n\\n b = cupy.trim_zeros(cupy.atleast_1d(b), 'f')\\n a = cupy.trim_zeros(cupy.atleast_1d(a), 'f')\\n\\n if a.size == 0:\\n raise ValueError(\\\"Denominator `a` is zero.\\\")\\n\\n poles = roots(a)\\n if b.size == 0:\\n return cupy.zeros(poles.shape), _cmplx_sort(poles)[0], cupy.array([])\\n\\n if len(b) < len(a):\\n k = cupy.empty(0)\\n else:\\n k, b = _polydiv(b, a)\\n\\n unique_poles, multiplicity = unique_roots(poles, tol=tol, rtype=rtype)\\n unique_poles, order = _cmplx_sort(unique_poles)\\n multiplicity = multiplicity[order]\\n\\n residues = _compute_residues(unique_poles, multiplicity, b)\\n\\n index = 0\\n for pole, mult in zip(unique_poles, multiplicity):\\n poles[index:index + mult] = pole\\n index += mult\\n\\n return residues / a[0], poles, k\",\n \"def test_exists_mol_res_spin_data_no_data(self):\\n\\n # Reset relax.\\n reset()\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # This should be False.\\n self.failIf(mol_res_spin.exists_mol_res_spin_data())\",\n \"def test_residues(parse_mmtf):\\n parse_mmtf.assertEqual(len(parse_mmtf.mmcif_res), len(parse_mmtf.mmtf_res))\\n for i, e in enumerate(parse_mmtf.mmcif_res):\\n mmcif_r = parse_mmtf.mmcif_res[i]\\n mmtf_r = parse_mmtf.mmtf_res[i]\\n parse_mmtf.assertEqual(mmtf_r.level, mmcif_r.level)\\n parse_mmtf.assertEqual(mmtf_r.disordered, mmcif_r.disordered)\\n parse_mmtf.assertEqual(mmtf_r.resname, mmcif_r.resname)\\n parse_mmtf.assertEqual(mmtf_r.segid, mmcif_r.segid)\\n parse_mmtf.mmcif_atoms = [x for x in mmcif_r.get_atom()]\\n parse_mmtf.mmtf_atoms = [x for x in mmtf_r.get_atom()]\\n test_atoms(parse_mmtf=parse_mmtf)\",\n \"def getResidue(self, resnum, icode=None):\\n\\n return self._hv.getResidue(self.getChid(), resnum, icode,\\n self.getSegname())\",\n \"def get_residues_sequence (structure):\\n list_fastas=[]\\n residues_dict = {'CYS': 'C', 'ASP': 'D', 'SER': 'S', 'GLN': 'Q', 'LYS': 'K',\\n 'ILE': 'I', 'PRO': 'P', 'THR': 'T', 'PHE': 'F', 'ASN': 'N',\\n 'GLY': 'G', 'HIS': 'H', 'LEU': 'L', 'ARG': 'R', 'TRP': 'W',\\n 'ALA': 'A', 'VAL': 'V', 'GLU': 'E', 'TYR': 'Y', 'MET': 'M'}\\n\\n rna_dict={ ' G': 'G', ' C': 'C', ' A': 'A', ' T': 'T', ' U': 'U'}\\n dna_dict={ ' DG': 'G', ' DC': 'C', ' DA': 'A', ' DT': 'T', ' DU': 'U'}\\n\\n for model in structure:\\n for chain in model:\\n string=\\\"\\\"\\n for residue in chain:\\n for atom in residue:\\n if atom.id == \\\"CA\\\":\\n if residue.resname == 'UNK':\\n continue \\n else:\\n if residue.resname not in residues_dict:\\n raise NoExistsResidue(residue.resname) \\n residue_name = residues_dict[residue.resname] \\n string = string + residue_name\\n elif atom.id == \\\"P\\\":\\n if residue.resname.startswith(\\\" D\\\"):\\n residue_name= dna_dict[residue.resname]\\n if residue.resname not in dna_dict:\\n raise NoExistsDesoxiribonucleotide(residue.resname)\\n else:\\n residue_name= rna_dict[residue.resname]\\n if residue.resname not in rna_dict:\\n raise NoExistsRibonucleotide(residue.resname)\\n string= string + residue_name\\n if string != \\\"\\\":\\n list_fastas.append(string)\\n return list_fastas\",\n \"def get_contact_residue(self,cutoff=8.5,chain1='A',chain2='B',excludeH=False,\\n only_backbone_atoms=False,return_contact_pairs=False):\\n # get the contact atoms\\n if return_contact_pairs:\\n\\n # declare the dict\\n residue_contact_pairs = {}\\n\\n # get the contact atom pairs\\n atom_pairs = self.get_contact_atoms(cutoff=cutoff,chain1=chain1,chain2=chain2,\\n only_backbone_atoms=only_backbone_atoms,\\n excludeH=excludeH,\\n return_contact_pairs=True)\\n\\n # loop over the atom pair dict\\n for iat1,atoms2 in atom_pairs.items():\\n\\n # get the res info of the current atom\\n data1 = tuple(self.get('chainID,resSeq,resName',rowID=[iat1])[0])\\n\\n # create a new entry in the dict if necessary\\n if data1 not in residue_contact_pairs:\\n residue_contact_pairs[data1] = set()\\n\\n # get the res info of the atom in the other chain\\n data2 = self.get('chainID,resSeq,resName',rowID=atoms2)\\n\\n # store that in the dict without double\\n for resData in data2:\\n residue_contact_pairs[data1].add(tuple(resData))\\n\\n for resData in residue_contact_pairs.keys():\\n residue_contact_pairs[resData] = sorted(residue_contact_pairs[resData])\\n\\n return residue_contact_pairs\\n\\n else:\\n\\n # get the contact atoms\\n contact_atoms = self.get_contact_atoms(cutoff=cutoff,chain1=chain1,chain2=chain2,return_contact_pairs=False)\\n\\n # get the residue info\\n data1 = self.get('chainID,resSeq,resName',rowID=contact_atoms[0])\\n data2 = self.get('chainID,resSeq,resName',rowID=contact_atoms[1])\\n\\n # take only unique\\n residue_contact_A = sorted(set([tuple(resData) for resData in data1]))\\n residue_contact_B = sorted(set([tuple(resData) for resData in data2]))\\n\\n return residue_contact_A,residue_contact_B\",\n \"def getResonanceResidue(resonance):\\n\\n residue = None\\n if resonance.resonanceSet:\\n residue = resonance.resonanceSet.findFirstAtomSet().findFirstAtom().residue\\n \\n return residue\",\n \"def test_from_pdb_t4_n_residues(self):\\n expected_n_residues = 164 # noqa\\n raise NotImplementedError\",\n \"def assignResonanceResidue(resonance, residue):\\n\\n\\n #print 'assignResonanceResidue', makeResonanceGuiName(resonance), residue.seqId\\n if residue:\\n # we could be setting the residue to None\\n if not setAssignmentMolSystem(residue, resonance=resonance):\\n return\\n \\n resonanceSet = resonance.resonanceSet\\n if resonanceSet:\\n assignNames = set()\\n \\n for atomSet in resonanceSet.atomSets:\\n assignNames.add(atomSet.name)\\n \\n else:\\n assignNames = set(resonance.assignNames)\\n \\n assignedResidue = getResonanceResidue(resonance)\\n \\n if assignNames and (assignedResidue is not residue):\\n resonance.setAssignNames(assignNames)\\n \\n if residue:\\n atomSets = []\\n isotopeCode = resonance.isotopeCode\\n if ('HA' in assignNames) and (residue.ccpCode == 'Gly'):\\n assignNames.add('HA2')\\n assignNames.add('HA3')\\n \\n for atom in residue.atoms:\\n element = atom.chemAtom.elementSymbol\\n \\n if isotopeCode[-len(element):] != element:\\n continue\\n \\n atomSet = atom.atomSet\\n if atomSet:\\n if atomSet.name in assignNames:\\n if atomSet not in atomSets:\\n atomSets.append(atomSet)\\n \\n if resonanceSet:\\n resonanceSet.delete()\\n \\n if atomSets:\\n # might not always find atom sets\\n # e.g. if changing residue types\\n assignAtomsToRes(atomSets,resonance,None)\\n else:\\n if resonanceSet:\\n resonanceSet.delete()\\n #updateResonanceAnnotation(resonance)\\n\\n if not resonance.resonanceGroup:\\n nmrProject = resonance.nmrProject\\n spinSystem = None\\n molResidue = residue.molResidue\\n ccpCode = molResidue.ccpCode\\n molType = molResidue.molType\\n spinSystems = nmrProject.findAllResonanceGroups(ccpCode=ccpCode,\\n molType=molType)\\n \\n for extantSpinSystem in spinSystems:\\n if extantSpinSystem.residue is residue:\\n spinSystem = extantSpinSystem\\n break\\n \\n if not spinSystem:\\n spinSystem = nmrProject.newResonanceGroup()\\n assignSpinSystemResidue(spinSystem,residue)\\n \\n if resonance not in spinSystem.resonances:\\n spinSystem.addResonance(resonance)\\n updateResonanceAnnotation(resonance)\\n \\n else:\\n updateResonanceAnnotation(resonance)\",\n \"def test_perceive_residues_sorting(self, strict_chirality):\\n molecule = Molecule.from_file(get_data_file_path(\\\"proteins/ace-a10-nme.sdf\\\"))\\n\\n molecule.perceive_residues(strict_chirality=strict_chirality)\\n\\n for index, residue in enumerate(molecule.residues):\\n found = residue.residue_number\\n expected = str(index + 1)\\n\\n assert isinstance(found, str)\\n assert found == expected\",\n \"def test_boolean_complex_selection(self):\\n\\n # The residue selection loop.\\n sel = list(mol_res_spin.residue_loop(\\\"#Ap4Aase:4 & :Pro | #RNA\\\"))\\n\\n # Residue names and numbers.\\n names = ['Pro', None, None]\\n numbers = [4, -5, -4]\\n\\n # The residues.\\n self.assertEqual(len(sel), 3)\\n for i in range(3):\\n self.assertEqual(sel[i].name, names[i])\\n self.assertEqual(sel[i].num, numbers[i])\",\n \"def test_run_molecule(self, single_mol_system):\\n sequence = \\\"ABCDE\\\"\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_molecule(single_mol_system.molecules[0])\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def read_resfile(filename):\\n def place_constraints(constraint, init_seq):\\n \\\"\\\"\\\"\\n places the constraints in the appropriate dicts \\n -initial_seq for building the initial sequence with TPIKAA and TNOTAA\\n -constraints for restricting the conditional model with PIKAA, NOTAA, ALLAA, POLAR, etc.\\n \\\"\\\"\\\"\\n if not init_seq:\\n constraints[res_id] = constraint\\n else:\\n initial_seq[res_id] = constraint\\n\\n constraints = dict() # amino acids to restrict in the design\\n header, start_id = check_for_header(filename) # amino acids to use as default for those not specified in constraints\\n initial_seq = dict() # amino acids to use when initializing the sequence\\n\\n with open(filename, \\\"r\\\") as f:\\n # iterate over the lines and extract arguments (residue id, command)\\n lines = f.readlines()\\n for line in lines[start_id + 1:]:\\n args = [arg.strip() for arg in line.split(\\\" \\\")]\\n is_integer(args[0]) # the res id needs to be an integer\\n assert isinstance(args[1], str), \\\"the resfile command needs to be a string\\\"\\n \\n res_id = int(args[0]) - 1\\n if args[1] == \\\"-\\\": # if given a range of residue ids (ex. 31 - 33 NOTAA)\\n is_integer(args[2]) # the res id needs to be an integer\\n for res_id in range(res_id, int(args[2])):\\n constraint, init_seq = check_for_commands(args, 3, 4)\\n place_constraints(constraint, init_seq)\\n else: # if not given a range (ex. 31 NOTAA CA)\\n constraint, init_seq = check_for_commands(args, 1, 2)\\n place_constraints(constraint, init_seq)\\n \\n # update the initial seq dictionary to only have one element per residue id (at random)\\n initial_seq = {res_id : (common.atoms.resfile_commands[\\\"ALLAAwc\\\"] - restricted_aa).pop() for res_id, restricted_aa in initial_seq.items()}\\n\\n return constraints, header, initial_seq\",\n \"def getResidue(self, resname):\\n if self.hasResidue(resname):\\n return self.map[resname]\\n else:\\n return None\",\n \"def test_single_molecule(self, single_mol_system, sequence):\\n expected = list(itertools.chain(*([element] * 3 for element in sequence)))\\n processor = dssp.AnnotateResidues(\\\"test\\\", sequence)\\n processor.run_system(single_mol_system)\\n found = self.sequence_from_system(single_mol_system, \\\"test\\\")\\n assert found == expected\",\n \"def getResidue(self, resi):\\n\\n\\t\\tif self.numChains == 0:\\n\\t\\t\\tprint \\\"WARNING: Molecule has no chains\\\"\\n\\t\\t\\treturn None\\n\\n\\t\\tresi = int(resi)\\n\\t\\tfor chn in self.chain:\\n\\t\\t\\tfor res in chn.residue:\\n\\t\\t\\t\\tif int(res.file_id) == resi:\\n\\t\\t\\t\\t\\treturn res\\n\\n\\t\\treturn None\",\n \"def test_ipam_rirs_list(self):\\n pass\",\n \"def test_perceive_residues_natoms_mainchain_arginine(self, strict_chirality):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/MainChain_ARG.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def returnData(self):\\r\\n return self.returnRes\",\n \"def get_residue(self, resnum, chain):\\n res_chain = self.get_chain(chain)\\n residue = []\\n for line in res_chain.split(\\\"\\\\n\\\"):\\n if str(resnum) == str(line[22:26].strip()):\\n residue.append(line)\\n return \\\"\\\\n\\\".join(residue)\",\n \"def test_residues_perceived_dipeptide(self):\\n from openff.toolkit._tests.create_molecules import (\\n dipeptide_residues_perceived as create_dipeptide,\\n )\\n\\n dipeptide_residues_perceived = create_dipeptide()\\n\\n assert \\\"ACE\\\" == dipeptide_residues_perceived.atoms[0].metadata[\\\"residue_name\\\"]\\n assert \\\"1\\\" == dipeptide_residues_perceived.atoms[0].metadata[\\\"residue_number\\\"]\\n assert \\\" \\\" == dipeptide_residues_perceived.atoms[0].metadata[\\\"insertion_code\\\"]\\n\\n assert \\\"ALA\\\" == dipeptide_residues_perceived.atoms[10].metadata[\\\"residue_name\\\"]\\n assert \\\"2\\\" == dipeptide_residues_perceived.atoms[10].metadata[\\\"residue_number\\\"]\\n assert \\\" \\\" == dipeptide_residues_perceived.atoms[10].metadata[\\\"insertion_code\\\"]\\n\\n assert isinstance(dipeptide_residues_perceived.residues[0], HierarchyElement)\\n with pytest.raises(AttributeError):\\n type(dipeptide_residues_perceived.chains[0])\",\n \"def test_find_surface_residues():\\n atom_dict_0 = find_surface_residues(protein, max_dist=0, scaling=1)\\n atom_dict_1 = find_surface_residues(protein, max_dist=2, scaling=1)\\n atom_dict_2 = find_surface_residues(protein, max_dist=3, scaling=1)\\n atom_dict_3 = find_surface_residues(protein, max_dist=None, scaling=1)\\n atom_dict_4 = find_surface_residues(protein, max_dist=None, scaling=2)\\n\\n assert atom_dict_0.size == 0\\n assert len(atom_dict_1) > len(atom_dict_0), ('Increasing max_dist should '\\n 'result in more/equal number '\\n 'of atoms found')\\n\\n assert len(atom_dict_2) >= len(atom_dict_1), ('Increasing max_dist should '\\n 'result in more/equal number '\\n 'of atoms found')\\n assert_array_equal(np.intersect1d(atom_dict_1['id'], atom_dict_2['id']), atom_dict_1['id'])\\n\\n if oddt.toolkit.backend == 'ob':\\n ref_len_1 = 762\\n ref_len_2 = 968\\n ref_len_3 = 654\\n ref_len_4 = 379\\n elif oddt.toolkit.backend == 'rdk' and oddt.toolkits.rdk.__version__ >= '2019.09':\\n ref_len_1 = 762\\n ref_len_2 = 968\\n ref_len_3 = 664\\n ref_len_4 = 393\\n else:\\n ref_len_1 = 759\\n ref_len_2 = 966\\n ref_len_3 = 735\\n ref_len_4 = 489\\n\\n assert len(atom_dict_1) == ref_len_1\\n assert len(atom_dict_2) == ref_len_2\\n assert len(atom_dict_3) == ref_len_3\\n assert len(atom_dict_4) == ref_len_4\\n\\n # Adding hydrogen atoms should have no effect on the result\\n protein.addh()\\n atom_dict_addh = find_surface_residues(protein, max_dist=2, scaling=1)\\n assert_array_equal(atom_dict_addh['id'], atom_dict_1['id'])\\n\\n with pytest.raises(TypeError):\\n find_surface_residues(molecule=1)\\n with pytest.raises(ValueError):\\n find_surface_residues(molecule=protein, max_dist='a')\\n with pytest.raises(ValueError):\\n find_surface_residues(molecule=protein, max_dist=[1, 1, 1])\",\n \"def test_return_spin_pipe_fail(self):\\n\\n # Try to get a spin from a missing data pipe.\\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_spin, spin_id=':2', pipe='new')\",\n \"def getResonanceAtomTuple(resonance):\\n from ccpnmr.analysis.core.MoleculeBasic import getResidueCode\\n \\n molSystemCode = ''\\n chainCode = ''\\n res = ''\\n name = getResonanceName(resonance)\\n\\n if resonance.resonanceSet:\\n residue = getResonanceResidue(resonance)\\n chain = residue.chain\\n chainCode = chain.code\\n molSystemCode = chain.molSystem.code\\n res = str(residue.seqCode) + getResidueCode(residue)\\n \\n elif hasattr(resonance, 'resonanceGroup'): # Not FixedResonance\\n spinSystem = resonance.resonanceGroup\\n \\n if spinSystem:\\n residue = spinSystem.residue\\n ccpCode = spinSystem.ccpCode\\n residueProbs = [rp for rp in spinSystem.residueProbs if rp.weight > 0.0]\\n \\n if residue:\\n sysChain = residue.chain\\n chainCode = sysChain.code\\n molSystemCode = sysChain.molSystem.code\\n res = str(residue.seqCode) + getResidueCode(residue)\\n\\n elif residueProbs:\\n resTexts = []\\n resSeqs = []\\n resCodes = set()\\n \\n for residueProb in residueProbs:\\n residue = residueProb.possibility\\n seq = residue.seqCode\\n code = getResidueCode(residue)\\n \\n resTexts.append('%d?%s' % (seq,code))\\n resSeqs.append('%d?' % seq)\\n resCodes.add(code)\\n \\n if len(resCodes) == 1:\\n res = '/'.join(resSeqs) + resCodes.pop()\\n else:\\n res = '/'.join(resTexts)\\n \\n elif ccpCode:\\n res = '{%d}%s' % (spinSystem.serial,ccpCode)\\n\\n elif spinSystem.name:\\n res = '{%d:%s}' % (spinSystem.serial,spinSystem.name)\\n \\n else:\\n res = '{%d}' % (spinSystem.serial)\\n \\n return (molSystemCode, chainCode, res, name)\",\n \"def test_molecule_loop(self):\\n\\n # Loop over the molecules.\\n for mol in mol_res_spin.molecule_loop('#RNA'):\\n # Test the molecule name.\\n self.assertEqual(mol.name, 'RNA')\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1)\",\n \"def get_next_residue(self):\\n rawline = self.f.readline()\\n while rawline:\\n rematch = self.reslinere.match(rawline)\\n if rematch:\\n return (rematch.groups()[0], int(rematch.groups()[1]),\\n float(rematch.groups()[2]), float(rematch.groups()[3]),\\n float(rematch.groups()[4]), int(rematch.groups()[5]))\\n # If we make it to a blank line, keep skipping forward until we hit\\n # another CUMULATIVE record\\n elif not rawline.strip():\\n rematch2 = self.my_re.match(rawline)\\n while not rematch2:\\n rawline = self.f.readline()\\n # Check if we hit EOF\\n if not rawline: return None\\n rematch2 = self.my_re.match(rawline)\\n # end while not rematch2\\n rawline = self.f.readline()\\n # If we hit here, we are out of lines, or something\\n return None\",\n \"def test_call_wrapped_function(self):\\r\\n\\r\\n # adapted from test_app.test_cd_hit.test_cdhit_clusters_from_seqs\\r\\n\\r\\n exp = {'0': 'R27DLI_4812',\\r\\n '1': 'U1PLI_7889',\\r\\n '2': 'W3Cecum_4858',\\r\\n '3': 'R27DLI_3243',\\r\\n }\\r\\n app = GenericRepSetPicker(params={'Algorithm': 'most_abundant',\\r\\n 'ChoiceF': make_most_abundant, 'ChoiceFRequiresSeqs': True})\\r\\n obs = app(self.tmp_seq_filepath, self.tmp_otu_filepath)\\r\\n self.assertEqual(obs, exp)\",\n \"def test_resids(self):\\n cr = CaseReader(self.filename)\\n last_case = cr.get_case(-1)\\n self.assertIsNone(last_case.resids,\\n \\\"Case erroneously contains resids.\\\")\",\n \"def select_perturbation_residues(molecule):\\n # Validte the length of the molecule\\n validate_molecule_length(molecule)\\n # Set the maximum allowed perturbation numbers\\n maxNum = 3\\n # Select a random number between 1 and maxNum\\n ranNum = random.randint(1, maxNum)\\n # Define the perturbed list to hold the perturbed residue name\\n perturbed = []\\n count = 0\\n while count < ranNum:\\n # Random select a residue number in the molecule \\n index = random.randint(1, len(molecule))\\n perturbed.append([molecule.name, index, molecule[index].name])\\n count += 1\\n\\n return perturbed\",\n \"def getCharmmParams(residue, name):\\n resname = residue.get(\\\"name\\\")\\n atomname = name\\n\\n # Nucleic Acid Substitutions\\n\\n if residue.get(\\\"type\\\") == 4:\\n resname = resname[0]\\n if resname == \\\"A\\\":\\n resname = \\\"ADE\\\"\\n elif resname == \\\"C\\\":\\n resname = \\\"CYT\\\"\\n elif resname == \\\"G\\\":\\n resname = \\\"GUA\\\"\\n elif resname == \\\"T\\\":\\n resname = \\\"THY\\\"\\n if atomname == \\\"C7\\\":\\n atomname = \\\"C5M\\\"\\n elif atomname == \\\"H71\\\":\\n atomname = \\\"H51\\\"\\n elif atomname == \\\"H72\\\":\\n atomname = \\\"H52\\\"\\n elif atomname == \\\"H73\\\":\\n atomname = \\\"H53\\\"\\n elif resname == \\\"U\\\":\\n resname = \\\"URA\\\"\\n\\n if atomname == \\\"H5'1\\\":\\n atomname = \\\"H5'\\\"\\n elif atomname == \\\"H5'2\\\":\\n atomname = \\\"H5''\\\"\\n elif atomname == \\\"H2'1\\\":\\n atomname = \\\"H2'\\\"\\n elif atomname in [\\\"H2'2\\\", \\\"HO'2\\\"]:\\n atomname = \\\"H2''\\\"\\n\\n if residue.getAtom(\\\"O2'\\\") is None:\\n if atomname in [\\\"C2'\\\", \\\"H2'\\\", \\\"H2''\\\"]: resname = \\\"DEO1\\\"\\n\\n if residue.getAtom(\\\"H5T\\\") is not None:\\n if atomname in [\\\"H5T\\\", \\\"O5'\\\", \\\"C5'\\\"]: resname = \\\"5TER\\\"\\n if residue.getAtom(\\\"H3T\\\") is not None:\\n if atomname in [\\\"H3T\\\", \\\"O3'\\\", \\\"C3'\\\"]: resname = \\\"3TER\\\"\\n\\n # Terminal/Water Substitutions\\n\\n if residue.get(\\\"isNterm\\\"):\\n if resname == \\\"GLY\\\" and atomname in [\\\"N\\\", \\\"H\\\", \\\"H2\\\", \\\"H3\\\", \\\"CA\\\", \\\"HA2\\\", \\\"HA3\\\"]:\\n resname = \\\"GLYP\\\"\\n if atomname == \\\"H\\\":\\n atomname = \\\"HT1\\\"\\n elif atomname == \\\"H2\\\":\\n atomname = \\\"HT2\\\"\\n elif atomname == \\\"H3\\\":\\n atomname = \\\"HT3\\\"\\n elif resname == \\\"PRO\\\" and atomname in [\\\"N\\\", \\\"HN1\\\", \\\"HN2\\\", \\\"CD\\\", \\\"CA\\\", \\\"HD1\\\", \\\"HD2\\\", \\\"HA\\\", \\\"H2\\\", \\\"H3\\\"]:\\n resname = \\\"PROP\\\"\\n if atomname == \\\"H2\\\":\\n atomname = \\\"HN1\\\"\\n elif atomname == \\\"H3\\\":\\n atomname = \\\"HN2\\\"\\n elif resname == \\\"ACE\\\":\\n if atomname == \\\"CH3\\\":\\n atomname = \\\"CAY\\\"\\n elif atomname == \\\"HH31\\\":\\n atomname = \\\"HY1\\\"\\n elif atomname == \\\"HH32\\\":\\n atomname = \\\"HY2\\\"\\n elif atomname == \\\"HH33\\\":\\n atomname = \\\"HY3\\\"\\n elif atomname == \\\"C\\\":\\n atomname = \\\"CY\\\"\\n elif atomname == \\\"O\\\":\\n atomname = \\\"OY\\\"\\n else:\\n if atomname in [\\\"N\\\", \\\"H\\\", \\\"H2\\\", \\\"H3\\\", \\\"CA\\\", \\\"HA\\\"]:\\n resname = \\\"NTER\\\"\\n if atomname == \\\"H\\\":\\n atomname = \\\"HT1\\\"\\n elif atomname == \\\"H2\\\":\\n atomname = \\\"HT2\\\"\\n elif atomname == \\\"H3\\\":\\n atomname = \\\"HT3\\\"\\n elif residue.get(\\\"isCterm\\\"):\\n if atomname in [\\\"O\\\", \\\"OXT\\\", \\\"C\\\"]:\\n resname = \\\"CTER\\\"\\n if atomname == \\\"O\\\":\\n atomname = \\\"OT1\\\"\\n elif atomname == \\\"OXT\\\":\\n atomname = \\\"OT2\\\"\\n elif residue.get(\\\"type\\\") == 3:\\n resname = \\\"TP3M\\\"\\n if atomname == \\\"O\\\": atomname = \\\"OH2\\\"\\n\\n # Residue substitutions\\n\\n if resname == \\\"ILE\\\":\\n if atomname == \\\"CD1\\\":\\n atomname = \\\"CD\\\"\\n elif atomname == \\\"HD11\\\":\\n atomname = \\\"HD1\\\"\\n elif atomname == \\\"HD12\\\":\\n atomname = \\\"HD2\\\"\\n elif atomname == \\\"HD13\\\":\\n atomname = \\\"HD3\\\"\\n elif atomname == \\\"HG12\\\":\\n atomname = \\\"HG11\\\"\\n elif atomname == \\\"HG13\\\":\\n atomname = \\\"HG12\\\"\\n elif resname == \\\"CYS\\\" and \\\"HG\\\" not in residue.get(\\\"map\\\"):\\n resname = \\\"CYS\\\"\\n if atomname == \\\"CB\\\":\\n resname = \\\"DISU\\\"\\n atomname = \\\"1CB\\\"\\n elif atomname == \\\"SG\\\":\\n resname = \\\"DISU\\\"\\n atomname = \\\"1SG\\\"\\n elif resname == \\\"HIS\\\":\\n if \\\"HD1\\\" in residue.get(\\\"map\\\") and \\\"HE2\\\" in residue.get(\\\"map\\\"):\\n resname = \\\"HSP\\\"\\n elif \\\"HD1\\\" in residue.get(\\\"map\\\"):\\n resname = \\\"HSD\\\"\\n elif \\\"HE2\\\" in residue.get(\\\"map\\\"):\\n resname = \\\"HSE\\\"\\n elif resname == \\\"GLU\\\" or resname == \\\"GLH\\\":\\n if \\\"HE1\\\" in residue.get(\\\"map\\\"):\\n if atomname == \\\"HE1\\\":\\n atomname = \\\"HE2\\\"\\n elif atomname == \\\"OE1\\\":\\n atomname = \\\"OE2\\\"\\n elif atomname == \\\"OE2\\\":\\n atomname = \\\"OE1\\\"\\n if atomname in [\\\"CG\\\", \\\"HG3\\\", \\\"HG1\\\", \\\"HG2\\\", \\\"CD\\\", \\\"OE1\\\", \\\"OE2\\\", \\\"HE2\\\"]:\\n resname = \\\"GLUP\\\"\\n else:\\n resname = \\\"GLU\\\"\\n elif \\\"HE2\\\" in residue.get(\\\"map\\\"):\\n if atomname in [\\\"CG\\\", \\\"HG3\\\", \\\"HG1\\\", \\\"HG2\\\", \\\"CD\\\", \\\"OE1\\\", \\\"OE2\\\", \\\"HE2\\\"]:\\n resname = \\\"GLUP\\\"\\n else:\\n resname = \\\"GLU\\\"\\n elif resname == \\\"ASP\\\" or resname == \\\"ASH\\\":\\n if \\\"HD1\\\" in residue.get(\\\"map\\\"):\\n if atomname == \\\"HD1\\\":\\n atomname = \\\"HD2\\\"\\n elif atomname == \\\"OD1\\\":\\n atomname = \\\"OD2\\\"\\n elif atomname == \\\"OD2\\\":\\n atomname = \\\"OD1\\\"\\n if atomname in [\\\"CB\\\", \\\"HB3\\\", \\\"HB1\\\", \\\"HB2\\\", \\\"CG\\\", \\\"OD1\\\", \\\"OD2\\\", \\\"HD2\\\"]:\\n resname = \\\"ASPP\\\"\\n else:\\n resname = \\\"ASP\\\"\\n elif \\\"HD2\\\" in residue.get(\\\"map\\\"):\\n if atomname in [\\\"CB\\\", \\\"HB3\\\", \\\"HB1\\\", \\\"HB2\\\", \\\"CG\\\", \\\"OD1\\\", \\\"OD2\\\", \\\"HD2\\\"]:\\n resname = \\\"ASPP\\\"\\n else:\\n resname = \\\"ASP\\\"\\n\\n # HETATM Substitutions\\n\\n if resname == \\\"ACE\\\":\\n if atomname == \\\"CH3\\\":\\n atomname = \\\"CAY\\\"\\n elif atomname == \\\"HH31\\\":\\n atomname = \\\"HY1\\\"\\n elif atomname == \\\"HH32\\\":\\n atomname = \\\"HY2\\\"\\n elif atomname == \\\"HH33\\\":\\n atomname = \\\"HY3\\\"\\n elif atomname == \\\"C\\\":\\n atomname = \\\"CY\\\"\\n elif atomname == \\\"O\\\":\\n atomname = \\\"OY\\\"\\n elif resname == \\\"ADP\\\":\\n atomname = atomname.replace(\\\"*\\\", \\\"\\\\'\\\")\\n elif resname == \\\"NME\\\":\\n resname = \\\"CT3\\\"\\n if atomname == \\\"HH31\\\":\\n atomname = \\\"HT1\\\"\\n elif atomname == \\\"HH32\\\":\\n atomname = \\\"HT2\\\"\\n elif atomname == \\\"HH33\\\":\\n atomname = \\\"HT3\\\"\\n elif atomname == \\\"CH3\\\":\\n atomname = \\\"CAT\\\"\\n elif atomname == \\\"N\\\":\\n atomname = \\\"NT\\\"\\n elif atomname == \\\"H\\\":\\n atomname = \\\"HNT\\\"\\n\\n # Hydrogen Substitutions\\n\\n if atomname == \\\"H\\\":\\n atomname = \\\"HN\\\"\\n elif atomname == \\\"HA2\\\":\\n atomname = \\\"HA1\\\"\\n elif atomname == \\\"HA3\\\":\\n atomname = \\\"HA2\\\"\\n elif atomname == \\\"HB2\\\" and resname not in [\\\"ALA\\\"]:\\n atomname = \\\"HB1\\\"\\n elif atomname == \\\"HB3\\\" and resname not in [\\\"ALA\\\"]:\\n atomname = \\\"HB2\\\"\\n elif atomname == \\\"HD2\\\" and resname not in [\\\"HSP\\\", \\\"HSE\\\", \\\"HSD\\\", \\\"ASPP\\\"]:\\n atomname = \\\"HD1\\\"\\n elif atomname == \\\"HD3\\\" and resname not in [\\\"HIS\\\", \\\"HSE\\\", \\\"HSD\\\"]:\\n atomname = \\\"HD2\\\"\\n elif atomname == \\\"HE2\\\" and resname not in [\\\"TRP\\\", \\\"HSP\\\", \\\"HSE\\\", \\\"HSD\\\", \\\"GLUP\\\"]:\\n atomname = \\\"HE1\\\"\\n elif atomname == \\\"HE3\\\" and resname not in [\\\"TRP\\\", \\\"HSP\\\", \\\"HSE\\\", \\\"HSD\\\"]:\\n atomname = \\\"HE2\\\"\\n elif atomname == \\\"HG2\\\":\\n atomname = \\\"HG1\\\"\\n elif atomname == \\\"HG3\\\":\\n atomname = \\\"HG2\\\"\\n elif atomname == \\\"HG\\\" and resname in [\\\"SER\\\", \\\"CYS\\\"]:\\n atomname = \\\"HG1\\\"\\n\\n return resname, atomname\",\n \"def calculate_returns(data):\\n pass\",\n \"def test_generate_spin_id_data_array1(self):\\n\\n # The data.\\n data = ['1', 'GLY']\\n\\n # The ID.\\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\\n\\n # Test the string.\\n self.assertEqual(id, ':1')\",\n \"def coords_to_residue(self, rnext: bool = ...) -> None:\\n ...\",\n \"def getResidueInformation(self, resIDs=None, atomIDs=None):\\n if resIDs is None:\\n resIDs = set ()\\n else:\\n resIDs = set (resIDs)\\n\\n if atomIDs is not None:\\n for i in atomIDs:\\n resIDs.add (self._atomInfo[i][\\\"residue\\\"])\\n return self.getResidueInformation (resIDs=resIDs)\\n\\n resIDs = list (resIDs)\\n resIDs.sort ()\\n str=''\\n for res in resIDs:\\n str=str+self._residueInfo[res][\\\"name\\\"]\\n print self._shortenResidue (str)\\n str = ''\\n return dict ((resID, self._residueInfo[resID]) for resID in resIDs)\",\n \"def is_standard_residue(self):\\n return True\",\n \"def is_standard_residue(self):\\n return True\",\n \"def residuez(b, a, tol=1e-3, rtype='avg'):\\n\\n if (cupy.issubdtype(b.dtype, cupy.complexfloating)\\n or cupy.issubdtype(a.dtype, cupy.complexfloating)):\\n b = b.astype(complex)\\n a = a.astype(complex)\\n else:\\n b = b.astype(float)\\n a = a.astype(float)\\n\\n b = cupy.trim_zeros(cupy.atleast_1d(b), 'b')\\n a = cupy.trim_zeros(cupy.atleast_1d(a), 'b')\\n\\n if a.size == 0:\\n raise ValueError(\\\"Denominator `a` is zero.\\\")\\n elif a[0] == 0:\\n raise ValueError(\\\"First coefficient of determinant `a` must be \\\"\\n \\\"non-zero.\\\")\\n\\n poles = roots(a)\\n if b.size == 0:\\n return cupy.zeros(poles.shape), _cmplx_sort(poles)[0], cupy.array([])\\n\\n b_rev = b[::-1]\\n a_rev = a[::-1]\\n\\n if len(b_rev) < len(a_rev):\\n k_rev = cupy.empty(0)\\n else:\\n k_rev, b_rev = _polydiv(b_rev, a_rev)\\n\\n unique_poles, multiplicity = unique_roots(poles, tol=tol, rtype=rtype)\\n unique_poles, order = _cmplx_sort(unique_poles)\\n multiplicity = multiplicity[order]\\n\\n residues = _compute_residues(1 / unique_poles, multiplicity, b_rev)\\n\\n index = 0\\n powers = cupy.empty(len(residues), dtype=int)\\n for pole, mult in zip(unique_poles, multiplicity):\\n poles[index:index + mult] = pole\\n powers[index:index + mult] = 1 + cupy.arange(int(mult))\\n index += mult\\n\\n residues *= (-poles) ** powers / a_rev[0]\\n\\n return residues, poles, k_rev[::-1]\",\n \"def _result_wrapper(self, result, _pymatgen) -> List[ase.atoms.Atoms]:\\n if _pymatgen:\\n _, fname = tempfile.mkstemp(text=True)\\n with open(fname, \\\"w\\\") as f:\\n f.write(result.to(\\\"poscar\\\"))\\n return ase.io.read(fname, index=':', format=\\\"vasp\\\")\\n else:\\n import json\\n result = json.load(result)\\n if result[\\\"valid_response\\\"]:\\n _, fname = tempfile.mkstemp(text=True)\\n with open(fname, \\\"w\\\") as f:\\n f.write(result[\\\"response\\\"][0][\\\"cif\\\"])\\n return ase.io.read(fname, index=':', format=\\\"cif\\\")\\n elif not result[\\\"api_key_valid\\\"]:\\n raise ValueError(f\\\"Invalid API_KEY: {self.API_KEY}. Check your API_KEY at https://www.materialsproject.org/open!\\\")\",\n \"def test_perceive_residues_natoms_t4(self, strict_chirality):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/T4-protein.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def get_residue_coords(self, resnum):\\n return\",\n \"def endElement(self, name):\\n if name == \\\"residue\\\":\\n if self.oldresname is not None: # Make a new residue hook\\n\\n newreslist = self.findMatchingNames(self.newresname, self.reference)\\n if self.oldresname.find(\\\"$group\\\") >= 0: # Multiple new residues\\n for resitem in newreslist:\\n resname = resitem.string\\n group = resitem.group(1)\\n fromname = self.oldresname.replace(\\\"$group\\\", group)\\n if fromname in self.map:\\n self.updateMap(resname, fromname, self.map)\\n\\n else: # Work with a single new residue name\\n oldreslist = self.findMatchingNames(self.oldresname, self.map)\\n for resitem in newreslist:\\n resname = resitem.string\\n self.updateMap(resname, self.oldresname, self.map)\\n\\n # If this was only a residue conversion, exit\\n\\n if self.atommap == {}:\\n self.oldresname = None\\n self.newresname = None\\n return\\n\\n # Apply atom conversions for all appropriate residues\\n\\n resmatchlist = self.findMatchingNames(self.newresname, self.map)\\n for resitem in resmatchlist:\\n residue = self.map[resitem.string]\\n for newname in self.atommap:\\n oldname = self.atommap[newname]\\n if oldname not in residue.atoms: continue\\n self.updateMap(newname, oldname, residue.atoms)\\n\\n # Clean up\\n\\n self.oldresname = None\\n self.newresname = None\\n self.atommap = {}\\n\\n elif name == \\\"atom\\\":\\n\\n self.atommap[self.newatomname] = self.oldatomname\\n self.oldatomname = None\\n self.newatomname = None\\n\\n else: # Just free the current element namespace\\n self.curelement = \\\"\\\"\\n\\n return self.map\",\n \"def residueList(self):\\n\\n\\t\\trl = []\\n\\t\\tfor chain in self.chain:\\n\\t\\t\\tfor res in chain.residue:\\n\\t\\t\\t\\trl.append(res)\\n\\n\\t\\treturn rl\",\n \"def test_return_all(self):\\n self.data.return_all()\",\n \"def test_rsun(eit_map):\\n assert u.allclose(eit_map.rsun_obs, 979.0701*u.arcsec)\",\n \"def test_futures_loan_collateral_repay_result():\\n\\n client = Client(key, secret)\\n response = client.futures_loan_collateral_repay_result(**params)\\n response.should.equal(mock_item)\",\n \"def testrescorr():\\n tau = np.zeros((2,50))\\n tau[0,25] = 2\\n tau[1,23] = 3\\n tau2 = spec_utils.res_corr(tau, 2, 8)\\n #Check flux conserved\\n assert np.abs(np.sum(tau2[0,:])/ np.sum(tau[0,:]) -1) < 1e-6\\n assert np.abs(np.sum(tau2[1,:])/ np.sum(tau[1,:]) -1) < 1e-6\\n #Check expanded by expected amount\\n for i in (0,1):\\n assert np.size(np.where(tau2[i,:]> 0)) == 15\",\n \"def test_vault_get_vault_item(self):\\n pass\",\n \"def test_assign_resources_to_tmc_subarray_in_mid():\",\n \"def setUp(self):\\n\\n # Add a data pipe to the data store.\\n ds.add(pipe_name='orig', pipe_type='mf')\\n\\n # Name the first molecule.\\n cdp.mol[0].name = 'Ap4Aase'\\n\\n # Add a second molecule to the system.\\n cdp.mol.add_item(mol_name='RNA')\\n\\n # Add two more residues to the first molecule (and set the residue number of the first).\\n cdp.mol[0].res[0].num = 1\\n cdp.mol[0].res.add_item(res_num=2, res_name='Glu')\\n cdp.mol[0].res.add_item(res_num=4, res_name='Pro')\\n\\n # Add some spin info to this molecule.\\n cdp.mol[0].res[0].spin[0].name = 'NH'\\n cdp.mol[0].res[0].spin[0].num = 60\\n cdp.mol[0].res[1].spin[0].name = 'NH'\\n cdp.mol[0].res[1].spin[0].num = 63\\n\\n # Add one more residue to the second molecule (and set the residue number of the first).\\n cdp.mol[1].res[0].num = -5\\n cdp.mol[1].res.add_item(res_num=-4)\\n\\n # Add a second set of spins to the second molecule (naming the first set first).\\n cdp.mol[1].res[0].spin[0].name = 'C8'\\n cdp.mol[1].res[1].spin[0].name = 'C8'\\n cdp.mol[1].res[0].spin.add_item(spin_name='N5')\\n cdp.mol[1].res[1].spin.add_item(spin_name='N5')\\n cdp.mol[1].res[1].spin.add_item(spin_name='2H', spin_num=132)\\n\\n # Deselect a number of spins.\\n cdp.mol[0].res[0].spin[0].select = 0\\n cdp.mol[0].res[2].spin[0].select = 0\\n cdp.mol[1].res[0].spin[0].select = 0\\n cdp.mol[1].res[1].spin[1].select = 0\\n\\n # Update the metadata.\\n mol_res_spin.metadata_update()\",\n \"def is_standard_residue(self):\\n return False\",\n \"def test_xyzp_qm_7b():\\n subject = subject7\\n\\n with pytest.raises(qcelemental.MoleculeFormatError):\\n final, intermed = qcelemental.molparse.from_string(subject, return_processed=True, dtype='xyz')\",\n \"def test_rescore_unmask(self):\\r\\n module = CapaFactory.create(xml=self.common_shuffle_xml)\\r\\n get_request_dict = {CapaFactory.input_key(): 'mask_0'}\\r\\n module.check_problem(get_request_dict)\\r\\n # On rescore, state/student_answers should use unmasked names\\r\\n with patch.object(module.runtime, 'track_function') as mock_track_function:\\r\\n module.rescore_problem()\\r\\n mock_call = mock_track_function.mock_calls[0]\\r\\n event_info = mock_call[1][1]\\r\\n self.assertEquals(mock_call[1][0], 'problem_rescore')\\r\\n self.assertEquals(event_info['state']['student_answers'][CapaFactory.answer_key()], 'choice_2')\\r\\n self.assertIsNotNone(event_info['permutation'][CapaFactory.answer_key()])\",\n \"def test_get_solution(self):\\n pass\",\n \"async def test_get_chr_assembly(test_db):\\n resp = await test_db.get_chr_assembly(\\\"NC_000007.13\\\")\\n assert resp == (\\\"chr7\\\", \\\"GRCh37\\\")\\n\\n resp = await test_db.get_chr_assembly(\\\"NC_000007.14\\\")\\n assert resp is None\",\n \"def __call__(self, mol):\\n return self.choose(mol)\",\n \"def residLike(self):\\n\\n # --------------------------------------------------------------------------------------------- #\\n # Compute the residuals\\n if self.csys == 'GAL':\\n # Redo some file computations with this coordinate system\\n self.outbinexp = os.path.join(self.workpath, 'BinExpMapGAL'+self.suffix+'.fits')\\n self.outbincub = os.path.join(self.workpath, 'BinCubeGAL'+self.suffix+'.fits')\\n self.outsrcmap = os.path.join(self.workpath, 'SrcMapsGAL'+self.suffix+'.fits')\\n self.outresid = os.path.join(self.workpath, 'ResidGAL'+self.suffix+'.fits')\\n self.outresig = os.path.join(self.workpath, 'ResSigmaGAL'+self.suffix+'.fits')\\n\\n self._gtExpmap()\\n self._gtBincube()\\n self._gtSrcmap()\\n else:\\n # Nothing to add\\n pass\\n \\n self._gtBinmap()\\n self._gtModel()\\n # Create the residual count map (count_map - model_map)\\n if not os.path.isfile(self.outresid):\\n os.popen(\\\"farith {} {} {} ops=SUB\\\".format(self.outbinmap, self.outgtmod,\\n self.outresid))\\n # Create the sigma-residual map (residual_map/sqrt(model_map))\\n if not os.path.isfile(self.outresig):\\n os.popen(\\\"ftpixcalc {} '(a-b)/sqrt(b)' a={} b={}\\\".format(self.outresig,\\n self.outbinmap, self.outgtmod))\\n\\n # --------------------------------------------------------------------------------------------- #\\n # Get the sources to overplot\\n srcs = self.getSrc()\\n srcs = srcs[(srcs['Separation'] <= 3.) & ([not i.endswith('c') for i in srcs['Name']])]\\n # Plot the residuals\\n resplt1 = FermiMap()\\n resplt1.savepath = self.workpath\\n resplt1.image = self.outresig\\n resplt1.figname = 'ResSigma.pdf'\\n dmin, dmax = np.abs(resplt1.datamin), resplt1.datamax\\n resplt1.datamin = - min(dmin, dmax)\\n resplt1.datamax = + min(dmin, dmax)\\n resplt1.cbarlabel = r'Residual $\\\\sigma$/pixel'\\n resplt1.mapSky()\\n resplt1.srcSky(srcs['RA'], srcs['DEC'], srcs['Name'])\\n resplt1.save()\\n print(\\\"\\\\t=== Figure '{}' created ===\\\".format( os.path.join(resplt1.savepath, resplt1.figname) ))\\n\\n resplt2 = FermiMap()\\n resplt2.savepath = self.workpath\\n resplt2.image = self.outresid\\n resplt2.figname = 'Residuals.pdf'\\n dmin, dmax = np.abs(resplt2.datamin), resplt2.datamax\\n resplt2.datamin = - min(dmin, dmax)\\n resplt2.datamax = + min(dmin, dmax)\\n resplt2.cbarlabel = r'Residual counts/pixel'\\n resplt2.mapSky()\\n resplt2.srcSky(srcs['RA'], srcs['DEC'], srcs['Name'])\\n resplt2.save()\\n print(\\\"\\\\t=== Figure '{}' created ===\\\".format( os.path.join(resplt2.savepath, resplt2.figname) ))\\n return\",\n \"def test_molecule_loop_no_selection(self):\\n\\n # Molecule data.\\n name = ['Ap4Aase', 'RNA']\\n\\n # Loop over the molecules.\\n i = 0\\n for mol in mol_res_spin.molecule_loop():\\n # Test the molecule names.\\n self.assertEqual(mol.name, name[i])\\n\\n # Increment i.\\n i = i + 1\\n\\n # Test loop length.\\n self.assertEqual(len(list(mol_res_spin.molecule_loop())), 2)\",\n \"def test_rotamer_library_builder(self):\\n LIGAND_PATH = 'ligands/oleic_acid.pdb'\\n\\n ligand_path = get_data_file_path(LIGAND_PATH)\\n molecule = Molecule(ligand_path, exclude_terminal_rotamers=False)\\n\\n # rotamer_library = RotamerLibrary(molecule)\\n\\n rotamers_per_branch = molecule.rotamers\\n\\n assert len(rotamers_per_branch) == 2, \\\"Found an invalid number \\\" + \\\\\\n \\\"of branches: {}\\\".format(len(rotamers_per_branch))\\n\\n atom_list_1 = list()\\n atom_list_2 = list()\\n\\n rotamers = rotamers_per_branch[0]\\n for rotamer in rotamers:\\n atom_list_1.append(set([rotamer.index1, rotamer.index2]))\\n\\n rotamers = rotamers_per_branch[1]\\n for rotamer in rotamers:\\n atom_list_2.append(set([rotamer.index1, rotamer.index2]))\\n\\n EXPECTED_INDICES_1 = [set([9, 10]), set([8, 9]), set([7, 8]),\\n set([6, 7]), set([5, 6]), set([2, 5]),\\n set([0, 2]), set([0, 1])]\\n\\n EXPECTED_INDICES_2 = [set([12, 11]), set([12, 13]), set([13, 14]),\\n set([14, 15]), set([15, 16]), set([16, 17]),\\n set([17, 18]), set([18, 19])]\\n\\n where_1 = list()\\n for atom_pair in atom_list_1:\\n if atom_pair in EXPECTED_INDICES_1:\\n where_1.append(1)\\n elif atom_pair in EXPECTED_INDICES_2:\\n where_1.append(2)\\n else:\\n where_1.append(0)\\n\\n where_2 = list()\\n for atom_pair in atom_list_2:\\n if atom_pair in EXPECTED_INDICES_1:\\n where_2.append(1)\\n elif atom_pair in EXPECTED_INDICES_2:\\n where_2.append(2)\\n else:\\n where_2.append(0)\\n\\n assert (all(i == 1 for i in where_1)\\n and all(i == 2 for i in where_2)) or \\\\\\n (all(i == 2 for i in where_1)\\n and all(i == 1 for i in where_2)), \\\"Invalid rotamer library \\\" + \\\\\\n \\\"{}, {}\\\".format(where_1, where_2)\\n\\n assert (all(i == 1 for i in where_1)\\n and all(i == 2 for i in where_2)\\n and len(where_1) == len(EXPECTED_INDICES_1)\\n and len(where_2) == len(EXPECTED_INDICES_2)) or \\\\\\n (all(i == 2 for i in where_1)\\n and all(i == 1 for i in where_2)\\n and len(where_1) == len(EXPECTED_INDICES_2)\\n and len(where_2) == len(EXPECTED_INDICES_1)), \\\"Unexpected \\\" + \\\\\\n \\\"number of rotamers\\\"\",\n \"def test_perceive_residues_natoms_mainchain_charged_glutamic_acid(\\n self, strict_chirality\\n ):\\n offmol = Molecule.from_file(get_data_file_path(\\\"proteins/MainChain_GLH.sdf\\\"))\\n # Perceive residue substructures\\n offmol.perceive_residues(strict_chirality=strict_chirality)\\n counter = 0 # matched atom counter\\n for atom in offmol.atoms:\\n if atom.metadata:\\n counter += 1\\n assert counter == offmol.n_atoms\",\n \"def test_xyzp_qm_7a():\\n subject = subject7\\n\\n with pytest.raises(qcelemental.MoleculeFormatError):\\n final, intermed = qcelemental.molparse.from_string(subject, return_processed=True, dtype='psi4')\",\n \"def determine_matched_residue_positions(match_pdb_path):\\n positions_block = os.path.basename(os.path.normpath(match_pdb_path)).split('_')[2]\\n resnames = [a for a in re.split(\\\"[0-9]*\\\", positions_block) if a]\\n resnums = [int(a) for a in re.split(\\\"[a-zA-Z]*\\\", positions_block) if a]\\n\\n return [(a, b) for a, b in zip(resnames, resnums)]\",\n \"def test_check_map_primer_pool(self):\\r\\n s = \\\"\\\"\\\"#SampleID\\\\tBarcodeSequence\\\\tLinkerPrimerSequence\\\\tX\\\\tDescription\\r\\n#fake data\\r\\nx\\\\tAA\\\\tAC\\\\t3\\\\tsample_x\\r\\ny\\\\t\\\"AC\\\"\\\\tAT,DC\\\\t4\\\\t\\\"sample_y\\\"\\r\\nz\\\\tGG\\\\tGC\\\\t5\\\\tsample_z\\\"\\\"\\\"\\r\\n f = StringIO(s)\\r\\n f.name = 'test.xls'\\r\\n headers, id_map, barcode_to_sample_id, warnings, errors, \\\\\\r\\n primer_seqs_lens, all_primers = check_map(f,\\r\\n disable_primer_check=False)\\r\\n\\r\\n self.assertEqual(\\r\\n barcode_to_sample_id,\\r\\n {'AA': 'x',\\r\\n 'AC': 'y',\\r\\n 'GG': 'z'})\\r\\n self.assertEqual(errors, [])\\r\\n self.assertEqual(warnings, [])\\r\\n\\r\\n # Returns all possible primers with lengths associated.\\r\\n expected_all_primers = {'AC': 2, 'GC': 2, 'AT': 2, 'TC': 2}\\r\\n self.assertEqual(all_primers, expected_all_primers)\\r\\n\\r\\n # Returns all primers associated with each barcode.\\r\\n expected_primer_seqs_lens = {'AA': {'AC': 2}, 'GG': {'GC': 2},\\r\\n 'AC': {'AC': 2, 'GC': 2, 'AT': 2, 'TC': 2}}\\r\\n\\r\\n self.assertEqual(primer_seqs_lens, expected_primer_seqs_lens)\",\n \"def test_2_return(self):\\n plan = list(astar(self.mapp_1_s,\\n lambda s : s == self.mapp_1_s,\\n MAPPDistanceSum(self.mapp_1_s)))\\n self.assertEqual(len(plan),0)\",\n \"def torchani(ret_data):\\n\\n import numpy as np\\n import torch\\n import torchani\\n\\n device = torch.device('cpu')\\n builtin = torchani.neurochem.Builtins()\\n\\n # Failure flag\\n ret_data[\\\"success\\\"] = False\\n\\n # Build model\\n model = get_model(ret_data[\\\"model\\\"][\\\"method\\\"])\\n if model is False:\\n ret_data[\\\"error_message\\\"] = \\\"run_torchani only accepts the ANI1 method.\\\"\\n return ret_data\\n\\n # Build species\\n species = \\\"\\\".join(ret_data[\\\"molecule\\\"][\\\"symbols\\\"])\\n unknown_sym = set(species) - {\\\"H\\\", \\\"C\\\", \\\"N\\\", \\\"O\\\"}\\n if unknown_sym:\\n ret_data[\\\"error_message\\\"] = \\\"The '{}' model does not support symbols: {}.\\\".format(\\n ret_data[\\\"model\\\"][\\\"method\\\"], unknown_sym)\\n return ret_data\\n\\n species = builtin.consts.species_to_tensor(species).to(device).unsqueeze(0)\\n\\n # Build coord array\\n geom_array = np.array(ret_data[\\\"molecule\\\"][\\\"geometry\\\"]).reshape(1, -1, 3) * units.bohr_to_angstrom\\n coordinates = torch.tensor(geom_array.tolist(), requires_grad=True, device=device)\\n\\n _, energy = model((species, coordinates))\\n ret_data[\\\"properties\\\"] = {\\\"return_energy\\\": energy.item()}\\n\\n if ret_data[\\\"driver\\\"] == \\\"energy\\\":\\n ret_data[\\\"return_result\\\"] = ret_data[\\\"properties\\\"][\\\"return_energy\\\"]\\n elif ret_data[\\\"driver\\\"] == \\\"gradient\\\":\\n derivative = torch.autograd.grad(energy.sum(), coordinates)[0].squeeze()\\n ret_data[\\\"return_result\\\"] = np.asarray(derivative / units.bohr_to_angstrom).ravel().tolist()\\n else:\\n ret_data[\\\"error_message\\\"] = \\\"run_torchani did not understand driver method '{}'.\\\".format(ret_data[\\\"driver\\\"])\\n return ret_data\\n\\n ret_data[\\\"provenance\\\"] = {\\\"creator\\\": \\\"torchani\\\", \\\"version\\\": \\\"unknown\\\", \\\"routine\\\": \\\"torchani.builtin.aev_computer\\\"}\\n\\n ret_data[\\\"schema_name\\\"] = \\\"qc_schema_output\\\"\\n ret_data[\\\"success\\\"] = True\\n\\n return ret_data\",\n \"def _get_2D_by_pubchem(self, code, mol):\\n try:\\n template_path = self._get_pubchem_template_path(code)\\n if template_path:\\n template = self._load_template(template_path)\\n\\n if mol.HasSubstructMatch(template):\\n AllChem.GenerateDepictionMatching2DStructure(mol, template)\\n flaws = DepictionValidator(mol).depiction_score()\\n return DepictionResult(\\n source=DepictionSource.PubChem,\\n template_name=code,\\n mol=mol,\\n score=flaws,\\n )\\n except Exception as e:\\n print(str(e), file=sys.stderr)\\n\\n return DepictionResult(\\n source=DepictionSource.Failed, template_name=None, mol=None, score=1000\\n )\",\n \"def test_ipam_rirs_read(self):\\n pass\",\n \"def test_get_primers(self):\\r\\n\\r\\n # Raise error if ReversePrimer not supplied\\r\\n header = ['SampleID', 'BarcodeSequence', 'LinkerPrimerSequence',\\r\\n 'Description']\\r\\n mapping_data = [['s1', 'ATCG', 'TTGGCC,TTGGWC', 'ATRCCTA']]\\r\\n self.assertRaises(IndexError, get_primers, header, mapping_data)\\r\\n\\r\\n header = ['SampleID', 'BarcodeSequence', 'LinkerPrimerSequence',\\r\\n 'ReversePrimer', 'Description']\\r\\n forward_primers, reverse_primers = get_primers(header, mapping_data)\\r\\n\\r\\n forward_primers = set([seq.pattern for seq in forward_primers])\\r\\n reverse_primers = set([seq.pattern for seq in reverse_primers])\\r\\n\\r\\n expected_forward_primers = set(['TTGGCC', 'TAGG[CT]AT', 'TTGG[AT]C'])\\r\\n expected_reverse_primers = set(['GGCCAA', 'AT[AG]CCTA', 'G[AT]CCAA'])\\r\\n\\r\\n self.assertEqual(forward_primers, expected_forward_primers)\\r\\n self.assertEqual(reverse_primers, expected_reverse_primers)\",\n \"def __init__(self, atomlist):\\n\\n self.residues = []\\n\\n current_res = atomlist[0].res_id\\n\\n temp_res =[]\\n\\n for i in atomlist:\\n if i.res_id == current_res:\\n temp_res.append(i)\\n else:\\n self.residues.append(PDB_residue(temp_res))\\n temp_res = []\\n current_res = i.res_id\\n temp_res.append(i)\\n \\n \\n\\n self.residues.append(PDB_residue(temp_res)) # get final residue\\n\\n if len(self.residues) > 0: \\n self.chain_name = self.residues[0].chain\\n else:\\n self.chain_name = None\\n \\n chain_local_id = 1 \\n\\n ## CHAIN LOCAL ID variables in atom and residue\\n ## objects are set here!\\n ##\\n for res in self.residues:\\n for atom in res.atoms:\\n atom.chain_local_id = chain_local_id\\n res.chain_local_id = chain_local_id\\n chain_local_id=chain_local_id+1\",\n \"def residue_subsystem():\\n net = residue_network()\\n state = (0, 0, 0, 0, 0)\\n return Subsystem(net, state)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.75668174","0.6807258","0.6658924","0.6526883","0.641903","0.6259072","0.62291884","0.6145257","0.61449796","0.60818225","0.6001908","0.594091","0.5885459","0.58385515","0.57113373","0.5641675","0.5627909","0.5625898","0.5486544","0.54508084","0.5426877","0.5367023","0.53659254","0.53621954","0.5358915","0.53535926","0.53200406","0.530653","0.529304","0.5292819","0.52584624","0.5251825","0.5202984","0.5200533","0.51945037","0.5168026","0.51530194","0.5143462","0.5091296","0.50831115","0.50631875","0.50619984","0.5049677","0.5035657","0.5019582","0.4995958","0.4995307","0.49948746","0.49542153","0.49523795","0.49439156","0.494122","0.49364084","0.49230328","0.49179766","0.49080336","0.4894175","0.48811406","0.48545963","0.48429996","0.4802061","0.4796111","0.47926527","0.4792077","0.47895765","0.47845525","0.47845525","0.47652662","0.4764863","0.47617522","0.4741797","0.47402355","0.47325128","0.47216275","0.47196105","0.471844","0.4714126","0.47113794","0.47039703","0.47025886","0.46969867","0.4691926","0.4684896","0.46813726","0.4678291","0.46714467","0.4669716","0.4666595","0.46598375","0.46546555","0.46540058","0.46539187","0.4653687","0.46532363","0.46515876","0.4651326","0.46511537","0.46403497","0.46395606","0.46312177"],"string":"[\n \"0.75668174\",\n \"0.6807258\",\n \"0.6658924\",\n \"0.6526883\",\n \"0.641903\",\n \"0.6259072\",\n \"0.62291884\",\n \"0.6145257\",\n \"0.61449796\",\n \"0.60818225\",\n \"0.6001908\",\n \"0.594091\",\n \"0.5885459\",\n \"0.58385515\",\n \"0.57113373\",\n \"0.5641675\",\n \"0.5627909\",\n \"0.5625898\",\n \"0.5486544\",\n \"0.54508084\",\n \"0.5426877\",\n \"0.5367023\",\n \"0.53659254\",\n \"0.53621954\",\n \"0.5358915\",\n \"0.53535926\",\n \"0.53200406\",\n \"0.530653\",\n \"0.529304\",\n \"0.5292819\",\n \"0.52584624\",\n \"0.5251825\",\n \"0.5202984\",\n \"0.5200533\",\n \"0.51945037\",\n \"0.5168026\",\n \"0.51530194\",\n \"0.5143462\",\n \"0.5091296\",\n \"0.50831115\",\n \"0.50631875\",\n \"0.50619984\",\n \"0.5049677\",\n \"0.5035657\",\n \"0.5019582\",\n \"0.4995958\",\n \"0.4995307\",\n \"0.49948746\",\n \"0.49542153\",\n \"0.49523795\",\n \"0.49439156\",\n \"0.494122\",\n \"0.49364084\",\n \"0.49230328\",\n \"0.49179766\",\n \"0.49080336\",\n \"0.4894175\",\n \"0.48811406\",\n \"0.48545963\",\n \"0.48429996\",\n \"0.4802061\",\n \"0.4796111\",\n \"0.47926527\",\n \"0.4792077\",\n \"0.47895765\",\n \"0.47845525\",\n \"0.47845525\",\n \"0.47652662\",\n \"0.4764863\",\n \"0.47617522\",\n \"0.4741797\",\n \"0.47402355\",\n \"0.47325128\",\n \"0.47216275\",\n \"0.47196105\",\n \"0.471844\",\n \"0.4714126\",\n \"0.47113794\",\n \"0.47039703\",\n \"0.47025886\",\n \"0.46969867\",\n \"0.4691926\",\n \"0.4684896\",\n \"0.46813726\",\n \"0.4678291\",\n \"0.46714467\",\n \"0.4669716\",\n \"0.4666595\",\n \"0.46598375\",\n \"0.46546555\",\n \"0.46540058\",\n \"0.46539187\",\n \"0.4653687\",\n \"0.46532363\",\n \"0.46515876\",\n \"0.4651326\",\n \"0.46511537\",\n \"0.46403497\",\n \"0.46395606\",\n \"0.46312177\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.84991"},"document_rank":{"kind":"string","value":"0"}}}],"truncated":false,"partial":true},"paginationData":{"pageIndex":814,"numItemsPerPage":100,"numTotalItems":95772,"offset":81400,"length":100}},"jwt":"eyJhbGciOiJFZERTQSIsImtpZCI6IjVHZDBvd0g5MTM2eDZjc1FvbE1zcktNWUZoRVFoUm5PVVVybEpjOUhaUEEifQ.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc4NjE2NTUyOCwianRpIjoiODA3NTRjMjktNDNhNC00MmJhLWI5YjYtMzBkZTdlNzA3NGYwIiwic3ViIjoiL2RhdGFzZXRzL25vbWljLWFpL2Nvcm5zdGFjay1weXRob24tdjEiLCJleHAiOjE3ODYxNjkxMjgsImlzcyI6Imh0dHBzOi8vaHVnZ2luZ2ZhY2UuY28ifQ.n5PmUsTZiApm79huh2e4mf-FjPjyUdnIqkkte1SHhg0WfL7DcLwHwyBqJMLg_GL3q1CV-Fn8DbT1xBLVJC8PBw","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":95772,"numBytesParquet":1928375891}]},"discussionsStats":{"closed":1,"open":1,"total":2},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
query stringlengths 9 3.4k | document stringlengths 9 87.4k | metadata dict | negatives listlengths 4 101 | negative_scores listlengths 4 101 | document_score stringlengths 3 10 | document_rank stringclasses 102
values |
|---|---|---|---|---|---|---|
Converts a unified CSV row to a SVM feature matrix (numbers only!) | def row_to_features(self, row):
sequence = unify_sequence(row["Sequence"])
charge = field_to_float(row["Charge"])
score = field_to_bayes_float(row[self.col_for_sorting])
calc_mz, exp_mz, calc_mass, exp_mass = get_mz_values(row)
# calc_mz = field_to_float( row['Calc m/z'] ) # cal... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def csvRowToVector(self, csvRow, questionIds, csvTitles):\n if len(csvTitles) != len(csvRow): \n raise ValueError(\"Length of titles list is different to that of csvRow\")\n \n numFields = len(questionIds)\n egoRow = numpy.zeros(numFields) \n\n for i in range(0, numFie... | [
"0.65499526",
"0.649871",
"0.6260098",
"0.6239809",
"0.622896",
"0.6216122",
"0.6206421",
"0.615319",
"0.6141482",
"0.6021808",
"0.60132277",
"0.6011888",
"0.59874713",
"0.5967463",
"0.59497404",
"0.5932906",
"0.5924142",
"0.5853456",
"0.5838096",
"0.58369327",
"0.581172",
... | 0.0 | -1 |
parses a unified csv file and collects features from each row | def collect_data(self):
categories = []
list_of_feature_lists = []
feature_sets = set()
with open(self.csv_path, "r") as f:
reader = csv.DictReader(f)
# collecting some stats for FDR calculation:
self.PSM_count = 0
self.decoy_count = 0
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def loadCSV(input_file):",
"def parse_prefeaturized_csv_data(features_file_path):\n objects = []\n with open(features_file_path) as f:\n # First line contains column titles\n keys = f.readline().strip().split(',')\n for line in f:\n vals = line.strip().split(\",\")\n ... | [
"0.70052725",
"0.67813885",
"0.67507994",
"0.671795",
"0.66744685",
"0.65594405",
"0.6549073",
"0.6524705",
"0.65231276",
"0.6494231",
"0.6469768",
"0.6439672",
"0.6422604",
"0.6382351",
"0.63786244",
"0.6309739",
"0.6285347",
"0.62765247",
"0.6273016",
"0.62624663",
"0.62614... | 0.70409966 | 0 |
Determines whether a PSM (csv row) should be used as a negative or positive training example. returns 1 highscoring target (positive training example) 0 nothighscoring target (not usable for training) 1 decoy (negative training example) | def get_psm_category(self, row):
category = 0 # unknown (mix of true positives and false positives)
self.PSM_count += 1 # for FDR calculation
sequence = unify_sequence(row["Sequence"])
psm_FDR = calc_FDR(self.PSM_count, self.decoy_count)
if row_is_decoy(row):
self.... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def classify_snp_prediction(row):\n\n if row['true_snp'] == True and row['prediction'] == True:\n return 'true_positive'\n elif row['true_snp'] == False and row['prediction'] == True:\n return 'false_positive'\n elif row['true_snp'] == False and row['prediction'] == False... | [
"0.6114877",
"0.6008109",
"0.5968435",
"0.577627",
"0.5707403",
"0.5707228",
"0.55909485",
"0.5569505",
"0.55581737",
"0.55474263",
"0.5519808",
"0.55175203",
"0.5470294",
"0.5445095",
"0.5436541",
"0.5433641",
"0.5433556",
"0.54277265",
"0.54233503",
"0.5411494",
"0.5403636"... | 0.58807063 | 3 |
Set up the standard conformer filter | def _apply_init(self, result: ComponentResult) -> None:
if self.rms_cutoff is not None:
self._cache["cutoff"] = self.rms_cutoff * unit.angstrom
else:
self._cache["cutoff"] = None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def testUsingFilterTool(self):\n pass",
"def __init__(self, filter: ghidra.program.util.ProgramMergeFilter):\n ...",
"def filter(self, filters):",
"def __init__(self, standardize=True, hdr_alpha=0.05, tr=0.720, low_pass=None, high_pass=None, s_filter=False):\n\n self.standardize = standa... | [
"0.6870899",
"0.6385693",
"0.637626",
"0.63454145",
"0.6275047",
"0.6240758",
"0.61316156",
"0.6117365",
"0.60983324",
"0.6065666",
"0.6034638",
"0.5999396",
"0.59849596",
"0.59578615",
"0.5918277",
"0.58771527",
"0.58769166",
"0.5844637",
"0.5836335",
"0.5813589",
"0.5770331... | 0.0 | -1 |
Generate conformers for the molecules using the selected toolkit backend. | def _apply(self, molecules: List[Molecule]) -> ComponentResult:
# create the toolkit
toolkit = self._toolkits[self.toolkit]()
result = self._create_result()
rms_cutoff = self._cache["cutoff"]
for molecule in molecules:
try:
# assume input is angstr... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def generate_conformers(self, mol):\n mol = Chem.AddHs(mol)\n mol = self._embed_conformers(mol)\n\n if self.force_field:\n energies = self._minimize_conformers(mol, self.force_field)\n mol = self._prune_conformers(mol, energies)\n\n if self.align_templates:\n ... | [
"0.5587314",
"0.5390047",
"0.5389015",
"0.5304018",
"0.5105989",
"0.50054854",
"0.49886605",
"0.4986325",
"0.490982",
"0.49074492",
"0.4867412",
"0.48475558",
"0.4822304",
"0.48166752",
"0.48095068",
"0.47933137",
"0.47610325",
"0.47103268",
"0.47037166",
"0.46839568",
"0.468... | 0.50706977 | 5 |
Verify OAuth2 and Basic Auth Credentials for CrowdStrike | def selftest_function(opts):
try:
LOG.info("Verifying app.config values for %s", CrowdStrikeHelper.app_config_section)
app_configs = opts.get(CrowdStrikeHelper.app_config_section, {})
cs_helper = CrowdStrikeHelper(app_configs)
LOG.info("Verifying OAuth2 Credentials...")
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def check_auth():",
"def identify_auth():\r\n from requests.auth import HTTPBasicAuth\r\n from requests.auth import HTTPDigestAuth\r\n # HTTPBasicAuth Auth Method\r\n response = requests.get(base_url + '/basic-auth/51zxw/8888', auth=HTTPBasicAuth('51zxw', '8888'))\r\n print(response.status_code)\r... | [
"0.6982856",
"0.6764704",
"0.6455922",
"0.64511263",
"0.6441798",
"0.6441798",
"0.6441798",
"0.6441798",
"0.6441798",
"0.6441798",
"0.6441798",
"0.6441798",
"0.6441798",
"0.6441798",
"0.6441798",
"0.6441798",
"0.6441798",
"0.6441798",
"0.6441798",
"0.6441798",
"0.6441798",
... | 0.0 | -1 |
Thresholds the values in the GFF file infn and exports the results to the BED file outbed. | def GFFthreshold(infn,outbed):
converterd = {'probe':nodate,'a':nodate,'b':nodate}
logging.debug('reading GFF into record array')
a = csv2rec(infn,
delimiter='\t',
names=('chr','prog','id','start','stop','ratio','a','b','probe'),
converterd=converterd)
l... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def main(inFilepath, outFilepath):\n\n gff_df=read_gff(inFilepath, additional_lst=[\"ID\"])\n attribute_lst=[]\n for _, row in gff_df.iterrows():\n orfId = \"{}_{}\".format(row[\"seqname\"], row[\"ID\"].split(\"_\")[-1])\n att = \"{};orf_id={}\".format(row[\"attribute\"], orfId)\n att... | [
"0.57636285",
"0.5452764",
"0.5443643",
"0.54257494",
"0.5339823",
"0.5275607",
"0.5164848",
"0.51557857",
"0.5153393",
"0.51523715",
"0.509349",
"0.50704485",
"0.5037733",
"0.5014071",
"0.50115407",
"0.49746937",
"0.4944627",
"0.4939648",
"0.49357095",
"0.49293602",
"0.49289... | 0.70352584 | 0 |
Clean and shape node or way XML element to Python dict | def shape_element(element, node_attr_fields=NODE_FIELDS,
way_attr_fields=WAY_FIELDS,
problem_chars=PROBLEMCHARS,
default_tag_type='regular'):
node_attribs = {}
way_attribs = {}
way_nodes = []
tags = []
def get_tags(element):
"""get tags... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def elem2dict(node):\n result = {}\n\n for element in node.iterchildren():\n # Remove namespace prefix\n key = element.tag.split('}')[1] if '}' in element.tag else element.tag\n key = key[:1].lower() + key[1:]\n\n # Process element as tree element if the inner XML contains non-whi... | [
"0.7497333",
"0.7103926",
"0.69807535",
"0.6878571",
"0.68709517",
"0.6814094",
"0.677641",
"0.67453074",
"0.67044884",
"0.6668514",
"0.665151",
"0.6613812",
"0.6592377",
"0.6582121",
"0.6580767",
"0.6556343",
"0.636651",
"0.63367105",
"0.6273763",
"0.6259617",
"0.62185",
"... | 0.56999934 | 48 |
get tags under nodes and ways into proper format | def get_tags(element):
tags = []
id_num = element.attrib['id']
for child in element.iter('tag'):
attr = child.attrib
# check for problematic characters first and skip if matches
if PROBLEMCHARS.search(attr['k']):
continue
child_di... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def tags():",
"def nodes_to_nags(self, nags):\n out = []\n for n in nags:\n out.append(n.text.strip(' '))\n return out",
"def get_tags(self, root):\n tags = root.xpath(self.path)\n return tags if self.many else tags[:1]",
"def tags(self):\n # See also. Sen... | [
"0.66982424",
"0.61945075",
"0.6123378",
"0.61216927",
"0.60466504",
"0.6027082",
"0.58852315",
"0.5872097",
"0.58477205",
"0.58027965",
"0.5772606",
"0.5757173",
"0.57448596",
"0.5741053",
"0.57295",
"0.5729347",
"0.5726202",
"0.5711139",
"0.57031196",
"0.5689136",
"0.566932... | 0.5371315 | 43 |
Yield element if it is the right type of tag | def get_element(osm_file, tags=('node', 'way', 'relation')):
context = ET.iterparse(osm_file, events=('start', 'end'))
_, root = next(context)
for event, elem in context:
if event == 'end' and elem.tag in tags:
yield elem
root.clear() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def iterchildren(self, tag: Optional[str] = None) -> Iterator[E]:\n if tag == '*':\n tag = None\n for child in self:\n if tag is None or child.is_matching(tag):\n yield child",
"def iter(self, tag: Optional[str] = None) -> Iterator[E]:\n def safe_iter(ele... | [
"0.63753164",
"0.60972255",
"0.60102105",
"0.59415174",
"0.58363974",
"0.55872273",
"0.5578602",
"0.5544091",
"0.5525566",
"0.5525566",
"0.550221",
"0.550221",
"0.550221",
"0.549343",
"0.54807174",
"0.5473522",
"0.5439183",
"0.53977484",
"0.53914195",
"0.53841794",
"0.5373682... | 0.5498705 | 17 |
Raise ValidationError if element does not match schema | def validate_element(element, validator, schema=SCHEMA):
if validator.validate(element, schema) is not True:
field, errors = next(validator.errors.iteritems())
message_string = \
"\nElement of type '{0}' has the following errors:\n{1}"
error_string = pprint.pformat(errors)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _validate(self):\n fields, schema = self.__dict__, self._def.default\n extra_fields = fields.viewkeys() - schema.viewkeys()\n if len(extra_fields) > 0:\n raise AttributeError('Fields found that are not in the schema: %r' % (list(extra_fields)))\n for key in fields.iterkey... | [
"0.6917677",
"0.6829546",
"0.6765086",
"0.6688886",
"0.6621969",
"0.6621969",
"0.6621969",
"0.6621969",
"0.6598295",
"0.6589527",
"0.6505747",
"0.64963084",
"0.6438894",
"0.64136946",
"0.63809",
"0.6356894",
"0.6352081",
"0.6347782",
"0.63391244",
"0.63356936",
"0.6332507",
... | 0.65517884 | 10 |
Iteratively process each XML element and write to csv(s) | def process_map(file_in, validate):
with codecs.open(NODES_PATH, 'w') as nodes_file, \
codecs.open(NODE_TAGS_PATH, 'w') as nodes_tags_file, \
codecs.open(WAYS_PATH, 'w') as ways_file, \
codecs.open(WAY_NODES_PATH, 'w') as way_nodes_file, \
codecs.open(WAY_TAGS_PATH, ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def process_document(as_xml, as_csv):\n tree = ET.parse(as_xml)\n lists = xml_to_list(tree.getroot())\n list_to_csv(lists, as_csv)\n # raise NotImplementedError()\n pass",
"def write_data_to_csv(xml_files, csv_file):\n output = {}\n for xml_file in xml_files:\n with open(xml_file, 'r'... | [
"0.7012709",
"0.6700947",
"0.6297407",
"0.59716314",
"0.58779824",
"0.5822816",
"0.57374775",
"0.5690835",
"0.56382555",
"0.5521618",
"0.5448036",
"0.5382776",
"0.53448856",
"0.53337634",
"0.53160036",
"0.530577",
"0.5304252",
"0.5286421",
"0.5284995",
"0.5283285",
"0.5185278... | 0.0 | -1 |
Initializes the TRPO agent. | def __init__(self, sess, state_dim, encode_dim, action_dim, actions_output_dim, filepath):
#
# Initialize Network
#
self.dir_path = filepath
self.seed = seed_initialize(filepath, self.config.seed)
print(self.seed)
# TODO: tf to pyTorch
self.sess = sess
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def agent_init(self):\n pass",
"def initialize(self):\n self._setup_simulation_from_parameters()\n if \"orrb\" in self.constants.observation_providers:\n self._reset()\n self._goal = self._next_goal()\n self.update_goal_info()\n\n self.observer = self._build_o... | [
"0.7680569",
"0.7075661",
"0.70310503",
"0.69604135",
"0.6932689",
"0.6915156",
"0.67658997",
"0.66978145",
"0.66117245",
"0.66038847",
"0.6591837",
"0.65475047",
"0.65472716",
"0.65404785",
"0.6506784",
"0.64253426",
"0.64153105",
"0.6413088",
"0.6406444",
"0.63784635",
"0.6... | 0.0 | -1 |
Returns a policy from expert based on the task var for a given (s,a) | def get_policy_encode(self, state, action, encodes):
policy = np.zeros(self.action_dim, dtype=np.float32)
G_policy = \
self.sess.run(
self.action_dist_mu,
{self.state: state, self.encodes: encodes}
# {state, encodes}
)
mu ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def extract_policy(env, v, GAMMA=1.0):\r\n policy = np.zeros(env.nS)\r\n for s in range(env.nS):\r\n q_sa = np.zeros(env.nA)\r\n for a in range(env.nA):\r\n q_sa[a] = sum([p*(r+GAMMA*v[s_]) for p, s_, r, _ in env.P[s][a]])\r\n policy[s] = np.argmax(q_sa)\r\n return policy",... | [
"0.5840355",
"0.5825589",
"0.57298046",
"0.5645543",
"0.56205803",
"0.5619291",
"0.5573069",
"0.5508011",
"0.5464358",
"0.542903",
"0.5403647",
"0.5371436",
"0.5299",
"0.5299",
"0.5250383",
"0.5200065",
"0.518749",
"0.5182148",
"0.51795244",
"0.51595765",
"0.5146109",
"0.51... | 0.0 | -1 |
Impl. of SGAIL learning procedure. In each iter. generates trajs from G and updates G (via TRPO; based on value fun extimate) and D (Adam optimizer; Based on classification error). | def learn(self, state_expert, action_expert, action_expert_ori, s_max, s_min, a_max, a_min, new_dir_path):
#
# Information Writing
#
file_path = new_dir_path + "/Readme.txt"
f_read = open(file_path, "a")
f_read.write("paths_per_collect:\n" + str(self.config.paths_per_co... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def train(model, gt_adjacency, gt_interv, train_data, test_data, opt, metrics_callback, plotting_callback):\n first_stop = 0\n second_stop = 0\n thresholded = False\n\n patience = opt.train_patience\n patience_thresh = opt.train_patience_post\n best_nll_val = np.inf\n best_lagrangian_val = np.... | [
"0.6723436",
"0.66920716",
"0.6676073",
"0.6527702",
"0.6476373",
"0.6435898",
"0.641563",
"0.6395276",
"0.6364404",
"0.63341355",
"0.63299733",
"0.632058",
"0.6317122",
"0.6303805",
"0.6303732",
"0.6287278",
"0.6263957",
"0.6256631",
"0.6253903",
"0.62500715",
"0.6217582",
... | 0.0 | -1 |
If the filename is of the format YYYYMMDD_hhmmss | def get_date_from_filename(filepath):
print "debug: %s" % filepath
fname = os.path.basename(filepath)
print "debug: %s" % fname
date = fname.split("_")[0]
if len(date) != 8:
print "debug: %s" % date
print "debug: date len != 8"
return None
try:
int(date) # will ra... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _safe_filename(filename):\n date = datetime.datetime.utcnow().strftime(\"%Y-%m-%d-%H%M%S\")\n basename, extension = filename.rsplit('.', 1)\n return \"{0}-{1}.{2}\".format(basename, date, extension)",
"def time_key(file_name):\n splits = file_name.split('/')\n [date] = re.findall(r'(\\d{4}_\\d... | [
"0.6922858",
"0.67721564",
"0.66523653",
"0.66341877",
"0.6627839",
"0.66261584",
"0.6525038",
"0.65032446",
"0.6415359",
"0.63129514",
"0.6286169",
"0.6285519",
"0.62379235",
"0.62240267",
"0.61937743",
"0.6186371",
"0.614045",
"0.60972834",
"0.6082455",
"0.6059182",
"0.6048... | 0.6285025 | 12 |
Convert raw ADC counts into SI units as per datasheets | def processData(self, data):
# Skip bad reads
if len(data) != 2:
return
global lastTemp, lastRH, lastTimestamp
tempCts = int(data[0])
rhCts = int(data[1])
rhVolts = rhCts * 0.0048828125
# 10mV/degree, 1024 count/5V
temp = tempCts * 0.4882812... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def convert_frequency_2_internal_u(self,val):\n return val*conversion_facs_frequency[self.current_units[\"frequency\"]]",
"def convert_frequency_2_current_u(self,val):\n return val/conversion_facs_frequency[self.current_units[\"frequency\"]]",
"def convert_units(self):\n for prod in (\"ier... | [
"0.61268955",
"0.6116247",
"0.5842502",
"0.58094406",
"0.57919526",
"0.5777237",
"0.575389",
"0.57444954",
"0.56433296",
"0.5555081",
"0.55548817",
"0.55385494",
"0.5536834",
"0.5532951",
"0.5483744",
"0.54682785",
"0.544294",
"0.54411733",
"0.543857",
"0.5397938",
"0.5390165... | 0.0 | -1 |
print_in_block prints a message fancy | def print_in_block(message):
print("|", message) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def print_in_block(message):\n print(\"=\"*4, message)",
"def do_block():\n print_column()\n print_rows()",
"def do_block():\n print_column()\n print_rows()",
"def print_block():\n do_twice(do_block)\n do_twice(do_block)\n print_column()",
"def print_block():\n do_twice(do_block)... | [
"0.82680213",
"0.72581327",
"0.72581327",
"0.72422236",
"0.72410613",
"0.65806854",
"0.6528688",
"0.64682865",
"0.644541",
"0.64331144",
"0.63909894",
"0.61803967",
"0.61426616",
"0.600337",
"0.6001629",
"0.59299904",
"0.5875311",
"0.58397245",
"0.58374274",
"0.58373517",
"0.... | 0.8424028 | 0 |
Create account in db for testing | def create_test_account(self):
if not hasattr(self, "headers"):
self.headers = {"Content-Type": "application/json"}
self.account = {
"account_number": "11223344",
"pin": "1234",
"first_name": "John",
"last_name": "Doe",
"opening_bal... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def setUp(self):\n account_models.User.objects.create_user(email='mrtest@mypapaya.io', password='WhoAmI', username='aov1')",
"def test_create_user(self):\n pass",
"def test_create_user(self):\n pass",
"def test_create_user(self):\n pass",
"def account():\n\n bank_test = Bank.... | [
"0.7464342",
"0.73190993",
"0.73190993",
"0.73190993",
"0.7251022",
"0.72328395",
"0.7218017",
"0.71607393",
"0.7132524",
"0.71249807",
"0.71243155",
"0.71232057",
"0.70938474",
"0.7090275",
"0.7054926",
"0.7043996",
"0.6997264",
"0.69949186",
"0.69774175",
"0.69712317",
"0.6... | 0.7687588 | 0 |
Login and add Authorization headers | def add_auth_to_headers(self):
if not hasattr(self, "headers"):
self.headers = {"Content-Type": "application/json"}
login = {"account_number": self.account["account_number"],
"pin": self.account["pin"]}
token = json.loads(self.client.post(
"/accounts/log... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _login(self, username, password):\n\n auth_token_header_name = \"X-AuthToken\"\n if auth_token_header_name not in self.headers:\n login_response = self._send(\"/auth/login\", \"POST\", {\n \"username\": username,\n \"password\": password\n })\n ... | [
"0.7459252",
"0.71714276",
"0.7051584",
"0.697408",
"0.6925245",
"0.67969096",
"0.678197",
"0.6740072",
"0.6695989",
"0.66357434",
"0.6629826",
"0.6582317",
"0.65689564",
"0.6558543",
"0.6489001",
"0.6484532",
"0.6425403",
"0.64215344",
"0.6419265",
"0.6415041",
"0.6412059",
... | 0.7460721 | 0 |
The kmlWriter function writes JPEG and TIFF EXIF GPS data to a Google Earth KML file. This file can be opened in Google Earth and will use the GPS coordinates to create 'pins' on the map of the taken photo's location. | def kmlWriter(output_data, output_dir, output_name):
msg = 'Writing ' + output_name + ' KML output.'
print '[+]', msg
logging.info(msg)
# Instantiate a Kml object and pass along the output filename
kml = simplekml.Kml(name=output_name)
for exif in output_data:
if 'Latitude' in exif.keys(... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def saveKML(kmlFile):\n\n tilePath = os.path.basename('map-NYC_heatmap.png')\n north = topLeftLat\n south = bottomRightLat\n east = topLeftLon\n west = bottomRightLon\n \n bytes = KML % (tilePath, north, south, east, west)\n file(kmlFile, \"w\").write(bytes)"... | [
"0.7272041",
"0.70665",
"0.6839336",
"0.6782229",
"0.67590886",
"0.6627731",
"0.6027612",
"0.5821973",
"0.5808136",
"0.5792859",
"0.5754415",
"0.5609513",
"0.55759126",
"0.5573969",
"0.5561544",
"0.555536",
"0.54809815",
"0.5467511",
"0.5448434",
"0.5412696",
"0.533536",
"0... | 0.75549674 | 0 |
Build a dict of functions to transform from a timestamp into a relative offset. E.g. | def build_run_time_transformers(ranges, buckets=250):
funcs = {}
def f(t, min_, max_):
#return "%0.2f" % ((t-min_) * (1/(max_-min_)))
key = (t-min_) * (1/(max_-min_))
return "%0.3f" % (int(buckets*key) / (buckets / 100.0))
for run, range_ in ranges.items():
funcs[run] = fun... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def with_calculated(funs):\n def with_calculated_funs(a_dict):\n return updated_with(a_dict, to_dict(funs)(a_dict))\n return with_calculated_funs",
"def get_time_attr_map(t):\n now = datetime.datetime.now()\n if t + datetime.timedelta(hours=3) > now:\n return get_map(\"main_list_white\"... | [
"0.52797824",
"0.5149295",
"0.5143466",
"0.5121843",
"0.51101065",
"0.5044267",
"0.50194275",
"0.5009638",
"0.4988149",
"0.49848637",
"0.49679974",
"0.4934628",
"0.4894539",
"0.4892821",
"0.48880813",
"0.48834634",
"0.4878724",
"0.4828654",
"0.47740626",
"0.47482517",
"0.4743... | 0.501486 | 7 |
Take a move ('color', (row,col)). where row, col are 0indexed (from sgfmill) Figure out which corner it's in Transform it to be in the upper right corner; Returns [corners, move] | def move_to_corner(move):
color, m = move
if not m:
return (None, move)
y, x = m
corners = []
if (x >= 9 and y >= 9):
corners.append(0)
elif (x >= 9 and y <= 9):
corners.append(1)
elif (x <= 9 and y <= 9):
corners.append(2)
elif (x <= 9 and y >= 9):
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def move(self, board):\n\n if board.get_number_of_moves() == 0:\n random_row = randint(0, 2)\n random_column = randint(0, 2)\n\n if random_row == 1 or random_column == 1:\n random_row = 1\n random_column = 1\n elif random_row == 2:\n ... | [
"0.64972967",
"0.63445497",
"0.6259929",
"0.6193406",
"0.6146919",
"0.6122342",
"0.61185247",
"0.60586184",
"0.604872",
"0.60303676",
"0.60222936",
"0.5930572",
"0.58977294",
"0.58832806",
"0.5881443",
"0.5868172",
"0.585934",
"0.58571357",
"0.585504",
"0.5842502",
"0.5817029... | 0.77939284 | 0 |
In addition to the corner information returned, we also add the winner, returning a tuple of ((sequence_counts, nextmove_counts), winner) where `winner` == 1 for B win, 0 otherwise. | def extract_from_game(game_path):
with open(game_path) as sgf_file:
game_data = sgf_file.read().encode('utf-8')
try:
g = sgf.Sgf_game.from_bytes(game_data)
_, moves = sgf_moves.get_setup_and_moves(g)
except BaseException:
print("bad file: ", game_path)
return Counter... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def winner(board):\n black_count = board.count(-1)\n white_count = board.count(1)\n if black_count > white_count:\n #if black_count + white_count != 64:\n # black_count += (64 - black_count - white_count)\n return (-1, black_count, white_count)\n elif white_count > black_count:\... | [
"0.6933734",
"0.67717934",
"0.6493579",
"0.6132359",
"0.60990435",
"0.6084213",
"0.60838664",
"0.6075124",
"0.5997574",
"0.59872484",
"0.5982879",
"0.5978751",
"0.59727734",
"0.5944895",
"0.5942834",
"0.59083647",
"0.5867989",
"0.5861778",
"0.58603925",
"0.58582777",
"0.58547... | 0.0 | -1 |
Parses all .sgfs in `directory` and updates database accordingly. `directory` is assumed to be a path ending in 'YYYYmmddHH'. e.g. /path/to/games/2019070100/ | def analyze_dir(directory):
counts = Counter()
next_moves = defaultdict(Counter)
example_sgfs = {}
b_wins = Counter()
sgf_files = [os.path.join(directory, p)
for p in os.listdir(directory) if p.endswith('.sgf')]
amt = int(len(sgf_files) * FLAGS.sample_frac)
if FLAGS.sample_... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def usagestats_parse(dirpath):\r\n # Create database\r\n # TODO: change to an easier format, probably json.\r\n db, cursor = create_table()\r\n\r\n # Some vars for logging\r\n processed = 0\r\n err = 0\r\n\r\n # Iterate through the /usagestats/ directory and fetch all files\r\n for root, di... | [
"0.53457755",
"0.5272943",
"0.522",
"0.5175559",
"0.5155737",
"0.51370525",
"0.5131457",
"0.5120154",
"0.5110887",
"0.51071286",
"0.5103022",
"0.51002693",
"0.5084197",
"0.506192",
"0.5057502",
"0.50454944",
"0.5033248",
"0.50327975",
"0.5024265",
"0.5013997",
"0.5005775",
... | 0.62088275 | 0 |
That's a very nice function detecting all local minima and maxima and computing their coordinates. The method is based on derivatives. | def detect_min_max(arr):
max_value = max(np.absolute(np.reshape(arr, -1)))
peaks_max = []
peaks_min = []
x_max = []
y_max = []
z_max = []
x_min = []
y_min = []
z_min = []
for j1 in range(10, arr.shape[0]-10):
for j2 in range(1... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getMaxima(x, y):\n# mx_x = (np.abs(np.min(x)) + np.max(x)) / 2\n# mx_y = (np.abs(np.min(y)) + np.max(y)) / 2\n# \n mx_x = np.max(x)\n mx_y = np.max(y)\n return mx_x, mx_y",
"def find_local_minima(self, arr):\n\n # walks through array, finding local minima ranges\n\n # hacky wa... | [
"0.64929116",
"0.6011464",
"0.59649295",
"0.5955771",
"0.5748925",
"0.57336473",
"0.5702977",
"0.5701539",
"0.56934154",
"0.56354034",
"0.562641",
"0.55739635",
"0.55384916",
"0.5537082",
"0.5524504",
"0.55112046",
"0.5501972",
"0.55000186",
"0.54938585",
"0.54908246",
"0.547... | 0.54925483 | 19 |
Read the wave function of Nth state from the file numbered by jjjj | def read_from_file(jjjj, N, path='/data/users/mklymenko/science/H2_100/programing/dis/v0/'):
p1 = np.loadtxt(path+'ff_'+str(jjjj)+'.dat')
a = []
a = np.where(
((p1[:, 1] == 111) & (p1[:, 2] == 111) & (p1[:, 3] == 111)))[0]
n1 = N
X = np.array(p1[a[n1]+1:a[n1+1], 0]... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def readNextGenSpectrum(fname=''):\n\n print('Reading : ', fname)\n\n with open(fname, 'r') as rfile:\n dum = rfile.readline()\n sdum = dum.split()\n teff = float(sdum[0])\n logg = float(sdum[1])\n mph = float(sdum[2])\n dum = rfile.readline()\n nwav = float(d... | [
"0.6181482",
"0.5862029",
"0.56960034",
"0.5677018",
"0.56482685",
"0.56220466",
"0.5604546",
"0.5573163",
"0.5567389",
"0.55650276",
"0.5486313",
"0.547349",
"0.54472053",
"0.5439266",
"0.54381114",
"0.5421353",
"0.5416626",
"0.54019856",
"0.53966343",
"0.53939825",
"0.53676... | 0.63657975 | 0 |
Save Gaussian functions coefficients to the file | def save(self):
if (self._save != '0'):
p = self._save+self._path[-3:-1]+'_'+str(self._qn)+'.dat'
np.savetxt(p, self._gf)
else:
sys.exit("Wrong path to save") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def save(self, exp_file, gat_file):\n\t\tto_save = np.stack((self.b, self.sigma)) #(2, K)\n\t\tto_save = np.concatenate((self.W,to_save) , axis = 0) #(D+2,K)\n\t\tnp.savetxt(exp_file, to_save)\n\t\tself.gating.save(gat_file)\n\t\treturn",
"def saveCoefficients(self):\n path = self.directory + \"/\" + self... | [
"0.6887294",
"0.6386368",
"0.5855118",
"0.5557168",
"0.55372137",
"0.5516496",
"0.54990965",
"0.54429656",
"0.5438885",
"0.54104203",
"0.54090834",
"0.536263",
"0.5352562",
"0.5349766",
"0.5345404",
"0.53397816",
"0.5333403",
"0.53292924",
"0.53191966",
"0.53074473",
"0.52777... | 0.5314649 | 19 |
The model function represented by a sum of the Gaussian functions with variable positions, widths and amplitudes | def modelfun1(self, x, *par):
g = np.zeros(len(x[0]))
for j in range(len(par)/5):
x1 = par[j*5]
x2 = par[j*5+1]
x3 = par[j*5+2]
w = par[j*5+3]
a = par[j*5+4]
r1 = pow((x[0]-x1), 2)+pow((x[1]-x2), 2)+pow((x[2]-x3), 2)
#... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def Gaussian(x, mu=0, sigma=26.4, A=1, y0=0):\r\n #width = sigma*(2*np.sqrt(2*np.log(2)))\r\n b = 1/(sigma*np.sqrt(2*np.pi))\r\n f = b*np.power(np.e, -(((x-mu)**2)/(2*sigma**2)))\r\n return A*f + y0",
"def gaussian(x, *parameters):\n position, sigma, amplitude, background = parameters\n return ... | [
"0.66367567",
"0.6560433",
"0.65372294",
"0.653147",
"0.646325",
"0.6463125",
"0.6366298",
"0.63595486",
"0.6355874",
"0.6349452",
"0.6348714",
"0.63399464",
"0.6332683",
"0.62884027",
"0.62640566",
"0.62518823",
"0.6249206",
"0.6184604",
"0.6174887",
"0.6136336",
"0.6109296"... | 0.5969462 | 42 |
Computes the value of the wave function in points stored in the vector x using fitting parameters and the model functions. | def show_func(self, x):
if (self._flag == 1):
g = self.modelfun(x, *self._gf)
elif (self._flag == 2):
g = self.modelfun1(x, *self._gf)
elif ((self._flag == 0) & (self._load != '0')):
pass
else:
# pass
sys.exit("Wrong flag in do... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def wavefunction(self, x):\n return ( float(1) / math.pi**(float(1)/4)) * math.exp( x**2 / float(-2))",
"def f(self, x: np.array) -> float:\n return np.dot(x, self._w) + self._b",
"def get_value(self, x):\n return np.dot(self.w, x)",
"def __call__(self, x):\n if self.W.data is Non... | [
"0.7227406",
"0.68093836",
"0.6625069",
"0.6607957",
"0.6584455",
"0.64573056",
"0.6423362",
"0.6364259",
"0.63284844",
"0.6268312",
"0.6254425",
"0.61995685",
"0.61708206",
"0.61386824",
"0.61219203",
"0.61038744",
"0.6098201",
"0.6074191",
"0.605777",
"0.6016525",
"0.601011... | 0.0 | -1 |
Same as show_func(self,x) but returns decomposed primitive Gaussian functions | def show_gf(self, x):
g = np.zeros((len(x[0]), self._num_fu), dtype=np.float64)
for j in range(self._num_fu):
x1 = self._gf[j*5]
x2 = self._gf[j*5+1]
x3 = self._gf[j*5+2]
w = self._gf[j*5+3]
a = self._gf[j*5+4]
r1 = pow((x[0]-x1), 2... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def show_func(self, x):\n\n if (self._flag == 1):\n g = self.modelfun(x, *self._gf)\n elif (self._flag == 2):\n g = self.modelfun1(x, *self._gf)\n elif ((self._flag == 0) & (self._load != '0')):\n pass\n else:\n # pass\n sys.exit(\"... | [
"0.6923806",
"0.61165667",
"0.58499724",
"0.578721",
"0.5772432",
"0.572566",
"0.5708594",
"0.56611586",
"0.5646653",
"0.56375355",
"0.5631954",
"0.562097",
"0.5598726",
"0.55861354",
"0.5576355",
"0.55678403",
"0.55473655",
"0.55415136",
"0.55403167",
"0.5530078",
"0.5522108... | 0.6513373 | 1 |
Returns (height, x, y, width_x, width_y) the gaussian parameters of a 2D distribution by calculating its moments | def moments(data):
data = np.absolute(data)
total = data.sum()
X = np.indices(data.shape)
x = (X*data).sum()/total
width = np.sqrt((((X-x)**2)*data).sum()/data.sum())
m_max = data.max()
m_min = data.min()
if np.absolute(m_max) >= np.absolute(m_min):
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def gaussian(height, center_x, center_y, width_x, width_y):\n width_x = float(width_x)\n width_y = float(width_y)\n return lambda x,y: height*np.exp(\n -(((center_x-x)/width_x)**2+((center_y-y)/width_y)**2)/2)",
"def gaussian(height, center_x, center_y, width_x, width_y):\n width_x = f... | [
"0.6980863",
"0.6980863",
"0.6980863",
"0.695399",
"0.69327515",
"0.6924225",
"0.67132115",
"0.6643802",
"0.66222733",
"0.6582163",
"0.6523381",
"0.64445627",
"0.6374211",
"0.63356495",
"0.6284357",
"0.6257092",
"0.624982",
"0.6249254",
"0.6249254",
"0.6245236",
"0.6215857",
... | 0.6313388 | 14 |
The function does the fitting procedure | def do_fit(self):
if (self._flag == 1):
self._gf = [0.2]
self._gf = self.par*(self._num_fu*len(self._sites)*2)
x, F = self.read_from_file(
self._sn, self._qn, self._path) # read data from the file
# ,ftol=1.0e-7,xtol=1.0e-8)
popt, pco... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fit():\n pass",
"def fit(self, X):",
"def fit(self, x):\n pass",
"def fit(self, X, y=...):\n ...",
"def fit(self, X, y=...):\n ...",
"def fit(self, X, y=...):\n ...",
"def fit(self, X, y=...):\n ...",
"def fit(self, X, y=...):\n ...",
"def fit(se... | [
"0.83682567",
"0.81361425",
"0.79078686",
"0.7716284",
"0.7716284",
"0.7716284",
"0.7716284",
"0.7716284",
"0.7716284",
"0.7716284",
"0.7716284",
"0.7716284",
"0.7716284",
"0.7701683",
"0.7701683",
"0.7701683",
"0.76664245",
"0.75478643",
"0.7520859",
"0.74977016",
"0.7411296... | 0.693916 | 34 |
This function is responsible for hitting the solr endpoint and returning the results back. | def search_simple_index(query, offset, count, draw):
results = SOLR_SIMPLEINDEX.search(q=query, **{
'start': int(offset),
'rows': int(count)
})
print("Saw {0} result(s) for query {1}.".format(len(results), query))
formatted_hits = []
for hit in results.doc... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def solr_query(config, solr_host, fq, solr_collection_name):\n # solr_collection_name = config['solr_collection_name']\n\n getVars = {'q': '*:*',\n 'fq': fq,\n 'rows': 300000}\n\n url = f'{solr_host}{solr_collection_name}/select?'\n response = requests.get(url, params=getVar... | [
"0.7272182",
"0.7217205",
"0.68685675",
"0.6716241",
"0.6716241",
"0.6543741",
"0.64756453",
"0.63854057",
"0.63058704",
"0.62296706",
"0.6182412",
"0.6172993",
"0.60816866",
"0.6062186",
"0.6048523",
"0.60386133",
"0.6022621",
"0.59974325",
"0.5983618",
"0.5973377",
"0.59657... | 0.5627814 | 53 |
This function is responsible for hitting the solr endpoint and returning the results back. | def search_entity_aware_index(query, offset, count, draw, qf):
results = SOLR_ENTITYAWAREINDEX.search(q=query, **{
'start': int(offset),
'rows': int(count),
'qf': qf
})
print("Saw {0} result(s) for query {1}.".format(len(results), query))
formatted_hit... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def solr_query(config, solr_host, fq, solr_collection_name):\n # solr_collection_name = config['solr_collection_name']\n\n getVars = {'q': '*:*',\n 'fq': fq,\n 'rows': 300000}\n\n url = f'{solr_host}{solr_collection_name}/select?'\n response = requests.get(url, params=getVar... | [
"0.7272182",
"0.7217205",
"0.68685675",
"0.6716241",
"0.6716241",
"0.6543741",
"0.64756453",
"0.63854057",
"0.63058704",
"0.62296706",
"0.6182412",
"0.6172993",
"0.60816866",
"0.6062186",
"0.6048523",
"0.60386133",
"0.6022621",
"0.59974325",
"0.5983618",
"0.5973377",
"0.59657... | 0.5488242 | 75 |
A helper to load any app's submodule by its name | def load_module(self, name, quiet=True):
full_name = '%s.%s' % (self.name, name)
try:
return import_module(full_name)
except ImportError:
if quiet:
return None
raise | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def load_app_modules(apps, submodules):\n for app in apps:\n mod = import_module(app)\n for submodule in submodules:\n import_submodule(mod, app, submodule)",
"def init_app(app):\n app.load_extension(__name__)",
"def findModule(name):",
"def loadapp(self, app, params=None):\n ... | [
"0.6744178",
"0.6379068",
"0.6354267",
"0.6203909",
"0.611294",
"0.6102048",
"0.60686713",
"0.60368586",
"0.5984119",
"0.5932818",
"0.5903442",
"0.5897478",
"0.58476454",
"0.58268327",
"0.58212805",
"0.58017206",
"0.5801174",
"0.578524",
"0.57665443",
"0.5766239",
"0.5740579"... | 0.0 | -1 |
Returns the list of URL patterns which have to be added to main urls.py By default returns a sigle URL pattern which mounts app's urls.py as under the app's label path. Most likely you don't need to edit this function. | def urlpatterns(self):
regex = r'^%s/' % self.label
urls_module = '%s.urls' % self.name
ns = self.label
return [url(regex, include(urls_module, namespace=ns, app_name=ns))] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def discover_urls():\n urlpatterns = []\n\n for app in settings.INSTALLED_APPS:\n try:\n _temp = __import__(f'{app}.urls', globals(), locals(), ['urlpatterns'], 0)\n urlpatterns += _temp.urlpatterns\n\n except ModuleNotFoundError:\n pass\n\n return urlpattern... | [
"0.78666055",
"0.76514953",
"0.75988424",
"0.74951446",
"0.7466889",
"0.7462883",
"0.7424311",
"0.72087145",
"0.7128712",
"0.71177673",
"0.7090256",
"0.70579743",
"0.6972757",
"0.69723296",
"0.6950012",
"0.6892247",
"0.6667635",
"0.6659763",
"0.66339105",
"0.6629913",
"0.6492... | 0.84036785 | 0 |
A signal called by the constructor once the app instance is ready (once it's registered) | def ready(self):
# export app settings
self.export_settings()
# import the submodule with signal handlers
self.load_module('signals') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def ready(self):\n import main.signals # noqa",
"def on_startup(self) -> None:\n ...",
"def ready(self):\n\n from . import signals # noqa",
"def on_start(self):\n App.on_start(self)\n self.root.register()",
"def on_start(self):\n self.init()",
"def ready(self):... | [
"0.74507123",
"0.73261684",
"0.73054254",
"0.72979665",
"0.7194798",
"0.71527547",
"0.71152693",
"0.70625466",
"0.702905",
"0.68536276",
"0.68536276",
"0.68536276",
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"0.68536276",
"0.68536276",
"0.683485",
"0.68191284",
"0.68191147",
"... | 0.7368948 | 1 |
A decorator to add a periodic task. Decorated function has to accept | def periodic_task(cls, delta, name=None):
if isinstance(delta, int):
delta = datetime.timedelta(seconds=delta)
def decorator(func):
registry_name = name or '%s.%s' % (func.__module__, func.__name__)
cls.periodic_tasks[registry_name] = PeriodicTaskFun(func, delta, reg... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def setup_periodic_tasks(sender, **kwargs):\n sender.add_periodic_task(60, scheduled_task.s(), name='A scheduled task')",
"def Schedule(interval=3600):\n # TODO:: if func need to return something\n def schedule(func):\n @wraps(func)\n def wrapper(*args, **kwargs):\n while True:\... | [
"0.67738533",
"0.6409797",
"0.63915294",
"0.63910186",
"0.63910186",
"0.63910186",
"0.63910186",
"0.63910186",
"0.63910186",
"0.63910186",
"0.63910186",
"0.63910186",
"0.63910186",
"0.6348526",
"0.6347841",
"0.6334383",
"0.6309153",
"0.625314",
"0.62467635",
"0.61627775",
"0.... | 0.7903502 | 0 |
Uses Gibbs sampling to segment an image into foreground and background. Inputs | def gibbs_segmentation(image, burn_in, collect_frequency, n_samples):
(Nx, Ny, _) = image.shape
distribution = np.zeros( (Nx, Ny) )
# Initialize binary estimates at every pixel randomly.
estimates = (np.random.random( (Nx, Ny) ) > .5).astype(int)
total_iterations = burn_in + (collect_frequency *... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def img_process(fgMask):\n backSub = cv.createBackgroundSubtractorKNN()\n kernel1 = cv.getStructuringElement(shape=cv.MORPH_ELLIPSE, ksize=(2,2))\n kernel2 = cv.getStructuringElement(shape=cv.MORPH_ELLIPSE, ksize=(2,2))\n #kernel1 = np.ones((3,3),np.uint8)\n #kernel2 = np.ones((3,3), np.uint8)\n\n ... | [
"0.60925585",
"0.59579676",
"0.5944388",
"0.5910497",
"0.5808057",
"0.5794726",
"0.57745075",
"0.57592636",
"0.5752392",
"0.5752392",
"0.5737282",
"0.572165",
"0.5718988",
"0.56727695",
"0.56688863",
"0.5667283",
"0.5656513",
"0.56523293",
"0.5646415",
"0.564283",
"0.5639516"... | 0.6486014 | 0 |
Returns values of the grid at points neighboring (x,y) Inputs | def get_neighbors(grid, x, y):
out = []
if x > 0:
out.append(grid[x-1, y])
if y > 0:
out.append(grid[x, y-1])
if y < grid.shape[1] - 1:
out.append(grid[x, y+1])
if x < grid.shape[0] - 1:
out.append(grid[x+1, y])
return out | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_xy(self, x, y):\r\n\t\treturn self.grid[y, x]",
"def get_xy_grid(nx, ny):\n\tfor n in [nx, ny]:\n\t\tif not isodd(n):\n\t\t\traise Exception(\"[get_xy_grid] only accept odd number\")\n\n\tx, y = np.mgrid[-(nx-1)/2:(nx+1)/2, -(ny-1)/2:(ny+1)/2]\n\n\treturn x, y",
"def neighbours(x, y):\n n = []\n ... | [
"0.7048819",
"0.6988485",
"0.6886183",
"0.6840988",
"0.6834184",
"0.6812989",
"0.6711071",
"0.66918945",
"0.66904217",
"0.6687271",
"0.6672603",
"0.66403353",
"0.6630548",
"0.6619971",
"0.6610192",
"0.6555865",
"0.6553371",
"0.6549096",
"0.6524648",
"0.6524648",
"0.649784",
... | 0.7839016 | 0 |
Computes the probability of observing a set of RGB intensities for a given label. Inputs | def observation_model(intensities, label):
idxs = enumerate(intensities)
return np.prod([dist[label, i, intensity] for (i, intensity) in idxs]) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def compute_color_for_labels(label):\n color = [int((p * (label ** 2 - label + 1)) % 255) for p in palette]\n return tuple(color)",
"def compute_color_for_labels(label):\n color = [int((p * (label ** 2 - label + 1)) % 255) for p in palette]\n return tuple(color)",
"def compute_color_for_labels(labe... | [
"0.60875475",
"0.60875475",
"0.60875475",
"0.60875475",
"0.60744995",
"0.6039619",
"0.5823827",
"0.5799188",
"0.5729159",
"0.57266355",
"0.56977594",
"0.5687674",
"0.5687674",
"0.5659029",
"0.5646229",
"0.56302005",
"0.5624872",
"0.56243336",
"0.56099576",
"0.5598231",
"0.559... | 0.5677279 | 13 |
Given the values at two pixels, returns the edge potential between those two pixels. | def edge_model(label1, label2):
if label1 == label2:
return ALPHA
else:
return 1-ALPHA | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def edge_between_neighbors(cell_a, cell_b):\n edge = np.logical_and(dilate_simple(cell_a), dilate_simple(cell_b))\n return edge",
"def find_complete_edge(v1, v2):\n if v2 < v1:\n v1, v2 = v2, v1\n return v1 + v2 * (v2 - 1) // 2",
"def getEdge(self, v1, v2):\n for e in self.edges:\n ... | [
"0.7079424",
"0.6260533",
"0.614386",
"0.60064805",
"0.5930904",
"0.58217674",
"0.57802707",
"0.5778961",
"0.57789373",
"0.5767245",
"0.5729393",
"0.57185256",
"0.5709799",
"0.56502026",
"0.56246686",
"0.5592777",
"0.5570452",
"0.5570447",
"0.55511206",
"0.55267125",
"0.55116... | 0.5323 | 43 |
Derivative of objective function | def func_deriv(x,remain):
#df_x0 = -1*remain[0]/x[0]**2
#df_x1 = -1*remain[2]/x[1]**2
#df_x2 = -1*remain[1]/x[2]**2
return np.array(-1*remain/x**2) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def deriv(self, x, d=None):\n if self.weights is None:\n self.compute_weights()\n\n val = 0.0\n for i in range(self.M):\n val += self.weights[i]*self.model_list[i].deriv(x, d)\n return val",
"def objective_function_derivative(\n terms,\n overlap_penalty,\n ... | [
"0.695038",
"0.6901204",
"0.68689436",
"0.67938876",
"0.67433965",
"0.6723132",
"0.6718581",
"0.67118424",
"0.6699861",
"0.6609691",
"0.6604677",
"0.66040355",
"0.6575055",
"0.65495205",
"0.65025395",
"0.64683104",
"0.6449893",
"0.6427921",
"0.6427921",
"0.64193326",
"0.64159... | 0.60648674 | 59 |
This function loads two files as input and return merged files | def load_data(messages_filepath, categories_filepath):
#load messages file
messages = pd.read_csv(messages_filepath)
#load categories file
categories = pd.read_csv(categories_filepath)
#merge these two datasets
df = messages.merge(categories, how='inner', on= 'id')
return df | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def merge(file_a, file_b):\n res = []\n a = read_bin_file_in_full(file_a)\n b = read_bin_file_in_full(file_b)\n pa = 0\n pb = 0\n while pa < len(a) and pb < len(b):\n if a[pa] < b[pb]:\n res.append(a[pa])\n pa += 1\n else:\n res.append(b[pb])\n ... | [
"0.7331378",
"0.7132421",
"0.6835498",
"0.6799099",
"0.66699827",
"0.6610325",
"0.6533628",
"0.65293807",
"0.6524281",
"0.6505234",
"0.6429747",
"0.64011747",
"0.63752604",
"0.6368189",
"0.63059515",
"0.6287107",
"0.6269712",
"0.6246524",
"0.6194321",
"0.6161838",
"0.61496097... | 0.0 | -1 |
Options callback for DSAIR. | def async_get_options_flow(
config_entry: ConfigEntry,
) -> DsAirOptionsFlowHandler:
return DsAirOptionsFlowHandler(config_entry) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def initialize_options(self):",
"def set_options(self, options):\n self.options = options",
"def _options(self):\n return",
"def initialize_options(self):\n pass",
"def options(self, parser):\n pass",
"def scanOptions(self, options):",
"def register_options(cls, register):",
"def ... | [
"0.66560775",
"0.6543463",
"0.6489074",
"0.6467768",
"0.6431175",
"0.6387198",
"0.63495994",
"0.63028973",
"0.6291787",
"0.62798554",
"0.62798554",
"0.62676454",
"0.62281305",
"0.62281305",
"0.62199026",
"0.62199026",
"0.61435634",
"0.60815954",
"0.6069882",
"0.6067049",
"0.6... | 0.0 | -1 |
Creates a desired number of sets of masks for MADE. | def gen_masks(num_masks, features, hidden_layers, hidden_units):
# This array should contain numbers 1-784
features_indices = []
for i in range(features):
features_indices.append(i + 1)
masks = []
indices = []
for i in range(num_masks):
set_masks = [] # Will contain all masks f... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def createMaks(self):\n mask = np.zeros((self.height, self.width)) # (H, W)\n center = self.width // 2\n\n for lat in range(self.height):\n count = int(self.counts[lat])\n # print(lat, count)\n # print(center - count, center, center + count)\n mask[lat][center: center + count] = 1\n ... | [
"0.69497967",
"0.63979864",
"0.63291293",
"0.62540984",
"0.6075182",
"0.60407674",
"0.6014026",
"0.59925056",
"0.59683883",
"0.59295285",
"0.57517284",
"0.57473755",
"0.57148474",
"0.5689238",
"0.56375664",
"0.5568423",
"0.5564914",
"0.555798",
"0.5554419",
"0.55477774",
"0.5... | 0.5952679 | 9 |
Generate autoencoded images and samples using the highestperforming variants of the model. | def compare_masks(model, num_examples, data, indices, masks,
masks_history, fname=None):
# Ensure that data is a numpy array
if tf.is_tensor(data):
data.numpy()
# Compute the number of different masks to be used
num_masks = math.floor(math.sqrt(num_examples))
plot_side = m... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def build_examples():\n build_models([\n \"VGG_16\",\n \"VGG_19\",\n \"RESNET_50\",\n \"MOBILENET\",\n #\"INCEPTION_V3\",\n #\"INCEPTION_RESNET\",\n #\"DENSENET_121\",\n #\"DENSENET_169\",\n #\"DENSENET_201\"])\n ])",
"def sample_final_tier... | [
"0.6182725",
"0.6160187",
"0.61424756",
"0.61398923",
"0.60936207",
"0.60548085",
"0.60506153",
"0.6010686",
"0.59838",
"0.59792376",
"0.5966361",
"0.5953654",
"0.59395534",
"0.592701",
"0.5913982",
"0.5891453",
"0.5865974",
"0.58577037",
"0.5855368",
"0.58507276",
"0.5829841... | 0.0 | -1 |
This function prints the values of the pixel with index 1 generated from num_samples different instances of noise. In a properly autoregressive network, these values will be equal, because the output node indicating the predicted probability of the first pixel's activation doesn't have any connections. | def ar_test(model, num_samples, indices):
samples = np.random.rand(num_samples, 28, 28)
i = 1
index = indices.index(i)
x_out = model.predict(samples, batch_size=num_samples)
row = index // 28
col = index % 28
print(x_out[:, row, col]) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def print_samples(num=10):\n X_init = torch.zeros(num, 1, dtype=torch.long).to(args.device)\n top_k = args.top_k if args.top_k != -1 else None\n steps = train_dataset.get_output_length() - 1 # -1 because we already start with <START> token (index 0)\n X_samp = generate(model, X_init, steps, top_k=top_k... | [
"0.5568828",
"0.5551278",
"0.5541915",
"0.5498311",
"0.5442604",
"0.5351635",
"0.5320976",
"0.531449",
"0.5227196",
"0.5210755",
"0.52081746",
"0.52046764",
"0.5169416",
"0.5149908",
"0.51466405",
"0.5116766",
"0.51054716",
"0.508762",
"0.5068448",
"0.5055635",
"0.5052395",
... | 0.47255567 | 98 |
Main function of Quick Sort | def quick_sort(l):
return _quick_sort(l, 0, len(l) - 1) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def quick_sort(array, pivot_type):\n\n def partition(array, left, right):\n global counter\n counter += right - left \n\n \n if pivot_type == 'median':\n \tmedian = get_median(array, left, right)\n \tarray[left], array[median] = array[median], array[left]\n\n eli... | [
"0.7489234",
"0.73037255",
"0.7263377",
"0.7248187",
"0.7244165",
"0.72246665",
"0.72138345",
"0.7182466",
"0.7112789",
"0.70957726",
"0.70957106",
"0.7094222",
"0.7061047",
"0.7031038",
"0.70136863",
"0.70048517",
"0.6961541",
"0.69505847",
"0.69396096",
"0.69392663",
"0.693... | 0.65747607 | 65 |
Helper function of Quick Sort | def _quick_sort(l, start, end):
if start < end:
split_point = partition(l, start, end)
_quick_sort(l, start, split_point - 1)
_quick_sort(l, split_point + 1, end)
return l | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def quick_sort(items):\n if len(items) > 1:\n pivot_index = len(items) / 2\n smaller_items = []\n larger_items = []\n \n for i, val in enumerate(items):\n if i != pivot_index:\n if val < i... | [
"0.7760281",
"0.7721993",
"0.76885456",
"0.7677915",
"0.7651931",
"0.7591512",
"0.7565072",
"0.75632894",
"0.7554661",
"0.75349593",
"0.7512256",
"0.7479444",
"0.7468108",
"0.7460778",
"0.7458644",
"0.74480146",
"0.7427353",
"0.7420264",
"0.73737925",
"0.7369719",
"0.73560107... | 0.74366266 | 16 |
Check FPU mode was not changed during the test. | def check_fpu_mode(request):
old_mode = get_fpu_mode()
yield
new_mode = get_fpu_mode()
if old_mode != new_mode:
warnings.warn("FPU mode changed from {0:#x} to {1:#x} during "
"the test".format(old_mode, new_mode),
category=FPUModeChangeWarning, stackl... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_test_mode(self):\n\n # Ensure that we default to test mode off\n self.assertFalse(self.driver._test_mode)\n\n exception = False\n try:\n self.driver.set_test_mode(False)\n self.driver.test_force_state(state=1)\n\n except TestModeException:\n ... | [
"0.6161543",
"0.6077402",
"0.602634",
"0.5968215",
"0.59399635",
"0.5799107",
"0.5782805",
"0.5766817",
"0.56953335",
"0.5690476",
"0.567844",
"0.55987924",
"0.5596079",
"0.55791",
"0.5551743",
"0.55079734",
"0.5506978",
"0.5492651",
"0.5483458",
"0.5458876",
"0.5451956",
"... | 0.83218914 | 0 |
Calculate distance between two vectors using pearson method | def pearson_distance(vector1, vector2) :
sum1 = sum(vector1)
sum2 = sum(vector2)
sum1Sq = sum([pow(v,2) for v in vector1])
sum2Sq = sum([pow(v,2) for v in vector2])
pSum = sum([vector1[i] * vector2[i] for i in range(len(vector1))])
num = pSum - (sum1*sum2/len(vector1))
den = math.sqrt((su... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _vector_dist(self, vec1, vec2):\r\n return sqrt(sum([(float(v1) - float(v2)) ** 2 for v1, v2 in\r\n zip(vec1, vec2)]))",
"def distance(p1, p2):\n return np.linalg.norm(p2-p1)",
"def distance(p1, p2):\n return np.linalg.norm(np.array(p1) - np.array(p2))",
"def distance... | [
"0.7294797",
"0.7278467",
"0.7270707",
"0.70065033",
"0.6940717",
"0.6914079",
"0.687906",
"0.6853775",
"0.68429995",
"0.6828889",
"0.6796051",
"0.6794433",
"0.67713475",
"0.67655015",
"0.6764504",
"0.67617387",
"0.6739371",
"0.67008483",
"0.6689883",
"0.66892594",
"0.6667814... | 0.82104915 | 0 |
generate k clusters randomly | def kmeans(matrix, k) :
clusters = [0 for i in range(k)]
lastcluster=[0 for i in range(k)]
min_=0
max_=matrix.__len__()
print "len",max_
cluster = [0 for i in range(k)]
for i in range(k) :
cluster[i]=int(random.random() * (max_ - min_) + min_)
clusters[i]=matrix[cluster[i]]
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def initialize_clusters(points, k):\r\n return points[np.random.randint(points.shape[0], size=k)]",
"def generateClustersRandomly(k=2, scale=1, num_clusters=1, points_per_cluster=20):\n rands = [[np.random.uniform(-scale, scale) * np.random.rand() for _ in range(k)] for i in range(num_clusters)]\n point... | [
"0.8382873",
"0.81803024",
"0.78525186",
"0.7692448",
"0.7688887",
"0.76144856",
"0.74655944",
"0.7380468",
"0.7282572",
"0.72800666",
"0.71585906",
"0.71396697",
"0.713959",
"0.71369356",
"0.7134352",
"0.71260124",
"0.7118058",
"0.71011895",
"0.70912254",
"0.7076738",
"0.703... | 0.6394023 | 67 |
Return number of iterations taken to get to 1. | def collatz(n):
iterCount = 0
while(n != 1):
if(n & 1):
n = 3 * n + 1
else:
n //= 2
iterCount += 1
return iterCount | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def number_of_iterations(self) -> int:\n pass",
"def number_of_iterations(self) -> int:\n return self._solution.info.iter",
"def number_of_iterations(self) -> int:\n return self._stats[\"iter_count\"]",
"def number_of_iterations(self):\n return self._solution.nit",
"def getNIter... | [
"0.78124964",
"0.74823964",
"0.72896755",
"0.7144956",
"0.70778865",
"0.70778865",
"0.6886788",
"0.6828246",
"0.6690062",
"0.6689765",
"0.66271555",
"0.6603668",
"0.65433306",
"0.65433306",
"0.65174437",
"0.6474691",
"0.6438922",
"0.6409205",
"0.6398579",
"0.6361549",
"0.6349... | 0.0 | -1 |
data loader for mnist data | def load_mnist(dataset_name='mnist', **kwargs):
dataset_name = dataset_name.strip().lower().replace('minist', 'mnist')
if dataset_name.lower() not in ['mnist', 'fashion-mnist']:
raise ValueError('Only mnist or fashion-mnist are valid dataset_name.')
base = 'http://yann.lecun.com/exdb/mnist/'
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def load_dataset():\n temp = gzip.open('mnist.pkl.gz')\n train, val , test = pickle.load(temp,encoding='latin1')\n temp.close()\n train_inp = [np.reshape(x, (784,1)) for x in train[0]]\n train_outp = [one_hot(y) for y in train[1]]\n training_data = zip(train_inp, train_outp)\n validation_inp =... | [
"0.79639393",
"0.79220957",
"0.7809936",
"0.77620274",
"0.7741267",
"0.77089685",
"0.77075154",
"0.76809376",
"0.7589876",
"0.7587508",
"0.7579602",
"0.7560688",
"0.75594527",
"0.7546023",
"0.753031",
"0.75233907",
"0.7508495",
"0.7488156",
"0.74859476",
"0.74364215",
"0.7397... | 0.74054974 | 20 |
data loader for mnist data | def load_cifar(dataset_name='cifar10'):
dataset_name = dataset_name.strip().lower().replace(' ', '')
if dataset_name.lower() not in ['cifar10', 'cifar100']:
raise ValueError('Only cifar10 or cifar100 are valid dataset_name.')
baseURL = 'https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz'
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def load_dataset():\n temp = gzip.open('mnist.pkl.gz')\n train, val , test = pickle.load(temp,encoding='latin1')\n temp.close()\n train_inp = [np.reshape(x, (784,1)) for x in train[0]]\n train_outp = [one_hot(y) for y in train[1]]\n training_data = zip(train_inp, train_outp)\n validation_inp =... | [
"0.79644245",
"0.7922395",
"0.7810252",
"0.7762534",
"0.7741613",
"0.77093273",
"0.7708081",
"0.7681307",
"0.7590164",
"0.75880253",
"0.7579777",
"0.75611156",
"0.75599843",
"0.7546466",
"0.753079",
"0.752396",
"0.7508959",
"0.7488553",
"0.7486288",
"0.7436546",
"0.74058455",... | 0.0 | -1 |
data loader for AllanYiin deep learning course exsample data | def load_examples_data(dataset_name):
dataset_name = dataset_name.strip().lower()
if dataset_name.lower() not in ['pokemon', 'hanzi', 'animals', 'nsfw', 'simpsons', 'horse2zebra', 'people',
'autodrive', 'superresolution', 'anpr', 'beauty','antisproofing','facelandmarks','dogs... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def load_data(self):\n params = self.params\n catg = params.data_category\n langs = ['en', params.target_lang]\n data = {lang: {splt: {} for splt in (['train', 'valid'] if lang == 'en' else ['test'])} for lang in langs}\n clf_dataset_path = {\n lang: {\n ... | [
"0.6882167",
"0.6877698",
"0.6874206",
"0.68331033",
"0.6818233",
"0.6786491",
"0.6765132",
"0.6740958",
"0.6734389",
"0.66937464",
"0.66903794",
"0.6689039",
"0.6681287",
"0.66398233",
"0.66133606",
"0.66025066",
"0.65917754",
"0.658308",
"0.6580977",
"0.65651095",
"0.655459... | 0.0 | -1 |
Main hook entry point | def execute(self, tasks, work_template, comment, thumbnail_path, sg_task, primary_task, primary_publish_path, progress_cb, **kwargs):
results = []
default_thumb = not os.path.exists(thumbnail_path)
alembic_jobs = []
alembic_publish_tasks = []
# publish all tasks:
for t... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def entry_point():",
"def entry_point():",
"def entry_point():",
"def _hook(self):",
"def on_hook(self) -> None:",
"def setup_hooks(self):\n pass",
"def main():\n pass",
"def main(self):\r\n pass",
"def _post_hooks(self):",
"def main():\n PLUGIN_ENTRY().run(\"\")",
"def ... | [
"0.7423908",
"0.7423908",
"0.7423908",
"0.73854935",
"0.7256732",
"0.7225447",
"0.7175162",
"0.71340764",
"0.7110802",
"0.7008554",
"0.7006415",
"0.6989436",
"0.6963864",
"0.6871478",
"0.6857729",
"0.67905015",
"0.67806673",
"0.6760804",
"0.6760804",
"0.6760804",
"0.6760804",... | 0.0 | -1 |
Publish an Alembic cache file for the scene and publish it to Shotgun. | def __publish_alembic_cache(self, item, output, work_template, primary_publish_path,
sg_task, comment, thumbnail_path, progress_cb):
# determine the publish info to use
#
progress_cb(10, "Determining publish details")
# get the current scene path ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __publish_geocache(self, item, output, work_template, primary_publish_path,\n sg_task, comment, thumbnail_path, progress_cb):\n # determine the publish info to use\n #\n progress_cb(10, \"Determining publish details\")\n\n # get the current sce... | [
"0.6180006",
"0.58817565",
"0.5879691",
"0.5615526",
"0.55755055",
"0.5549456",
"0.5518195",
"0.5488557",
"0.53738135",
"0.5355673",
"0.53469515",
"0.53295285",
"0.5316194",
"0.5295457",
"0.52651227",
"0.5242149",
"0.5208094",
"0.519602",
"0.51877934",
"0.51724315",
"0.516887... | 0.65435106 | 0 |
Export an OBJ geo file for the scene and publish it to Shotgun. | def __publish_obj(self, item, output, work_template, primary_publish_path,
sg_task, comment, thumbnail_path, progress_cb):
# determine the publish info to use
#
progress_cb(10, "Determining publish details")
# get the current scene path and extrac... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __make_geo(self):\n # gmsh freecad_part.iges -o out_iges.geo -0\n fname_list = self.__fname.split('.')\n geo_file = fname_list[0]+'.geo'\n runstr = \"%s %s -o %s -0\" % (environment.GMSH, self.__fname, geo_file)\n print(runstr)\n subprocess.call(runstr, shell=True)\n ... | [
"0.6160985",
"0.60075134",
"0.5905908",
"0.5900655",
"0.5871399",
"0.5855076",
"0.58512455",
"0.58496916",
"0.5741153",
"0.5695086",
"0.56631285",
"0.5657295",
"0.5654158",
"0.565178",
"0.5648279",
"0.56455564",
"0.5628589",
"0.5552822",
"0.54969823",
"0.5480505",
"0.54628605... | 0.5423219 | 24 |
Publish an Alembic cache file for the scene and publish it to Shotgun. | def __publish_geocache(self, item, output, work_template, primary_publish_path,
sg_task, comment, thumbnail_path, progress_cb):
# determine the publish info to use
#
progress_cb(10, "Determining publish details")
# get the current scene path and e... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __publish_alembic_cache(self, item, output, work_template, primary_publish_path,\n sg_task, comment, thumbnail_path, progress_cb):\n # determine the publish info to use\n #\n progress_cb(10, \"Determining publish details\")\n\n # get the curren... | [
"0.65446615",
"0.58813435",
"0.587966",
"0.5616056",
"0.5576552",
"0.55503",
"0.5517325",
"0.54890555",
"0.53740954",
"0.53564984",
"0.5346136",
"0.53308266",
"0.5318086",
"0.5296485",
"0.5264278",
"0.524097",
"0.5208991",
"0.5195995",
"0.5189076",
"0.5173123",
"0.5169205",
... | 0.61809075 | 1 |
Publish an Alembic cache file for the scene and publish it to Shotgun. | def __publish_yeticache(self, item, output, work_template, primary_publish_path,
sg_task, comment, thumbnail_path, progress_cb):
# determine the publish info to use
#
progress_cb(10, "Determining publish details")
# the file and folder name is derived from th... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __publish_alembic_cache(self, item, output, work_template, primary_publish_path,\n sg_task, comment, thumbnail_path, progress_cb):\n # determine the publish info to use\n #\n progress_cb(10, \"Determining publish details\")\n\n # get the curren... | [
"0.65444964",
"0.6181592",
"0.58802617",
"0.5877373",
"0.56138086",
"0.55472326",
"0.5520058",
"0.5490468",
"0.53768396",
"0.5357921",
"0.5348515",
"0.5328552",
"0.53159",
"0.5297584",
"0.5266048",
"0.52403307",
"0.5207243",
"0.5193524",
"0.51886195",
"0.5176134",
"0.5167291"... | 0.5576275 | 5 |
Export a Maya file for the camera and publish it to Shotgun. | def __publish_mayacamera(self, item, output, work_template, primary_publish_path,
sg_task, comment, thumbnail_path, progress_cb):
# determine the publish info to use
#
progress_cb(10, "Determining publish details")
# get the current scene path and... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def export_camera(progress_controller=None):\n if progress_controller is None:\n progress_controller = ProgressControllerBase()\n progress_controller.maximum = 7\n\n from stalker import Task, Version\n from anima.dcc import mayaEnv\n\n m = mayaEnv.Maya()\n v = m.get_current_version()\n ... | [
"0.6774113",
"0.6170067",
"0.6094196",
"0.5807592",
"0.5593866",
"0.5566821",
"0.55538255",
"0.5492313",
"0.5441863",
"0.5441394",
"0.54356366",
"0.5406046",
"0.540113",
"0.53069115",
"0.5299804",
"0.52989906",
"0.52933705",
"0.52650744",
"0.52415776",
"0.5216365",
"0.5212121... | 0.6862812 | 0 |
Export an Alembic file for the camera and publish it to Shotgun. | def __publish_alembiccamera(self, item, output, work_template, primary_publish_path,
sg_task, comment, thumbnail_path, progress_cb):
# determine the publish info to use
#
progress_cb(10, "Determining publish details")
# get the current scene path ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def export_camera(progress_controller=None):\n if progress_controller is None:\n progress_controller = ProgressControllerBase()\n progress_controller.maximum = 7\n\n from stalker import Task, Version\n from anima.dcc import mayaEnv\n\n m = mayaEnv.Maya()\n v = m.get_current_version()\n ... | [
"0.6083645",
"0.5946963",
"0.57567835",
"0.5715746",
"0.5713011",
"0.5650772",
"0.55849946",
"0.555498",
"0.54727066",
"0.5459543",
"0.54370785",
"0.5400925",
"0.5385602",
"0.53685206",
"0.5327392",
"0.5321729",
"0.5304796",
"0.5301103",
"0.5287265",
"0.5260967",
"0.52580863"... | 0.6043398 | 1 |
Find the animation range from the current scene. | def _find_scene_animation_range(self):
# look for any animation in the scene:
animation_curves = cmds.ls(typ="animCurve")
# if there aren't any animation curves then just return
# a single frame:
if not animation_curves:
return (1, 1)
# something in the scen... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getCurrentAnimRange():\n return int(oma.MAnimControl.minTime().value), int(oma.MAnimControl.maxTime().value)",
"def get_frame_range(self):\n #self._root = self.get_root_node()\n #startFrame = int(self._root.knob('first_frame').value())\n #endFrame = int(self._root.knob('last_frame').v... | [
"0.71858317",
"0.6609152",
"0.6361358",
"0.6292253",
"0.6262991",
"0.6139651",
"0.6130778",
"0.6130778",
"0.61261404",
"0.61125124",
"0.6087573",
"0.6052101",
"0.59913844",
"0.5926955",
"0.58776486",
"0.58599156",
"0.58571494",
"0.58331656",
"0.5719528",
"0.56707656",
"0.5669... | 0.8159036 | 0 |
Returns the game result and wage Earned. Plays One Round of BlackJack | def play_blackjack(wager, max_wager):
game = BlackJack(wager=wager, max_wager=max_wager, allow_split=True, allow_dd=True)
player = game.players[0]
print('\nYour Hand %s has %s points. Your wager is: %d' % (player['hand'], game.player_hand_value(), player['wager']))
print("Dealer's upcard is: ", game.ge... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def evaluate_game(self):\n self.dealer.hit_until_hold()\n message = self.bold_message(self.dealer.final_str_with_hand()+ \"\\n\")\n if self.dealer.has_blackjack():\n message += \"The Dealer has Blackjack. All players without blackjack will lose the round.\\n\\n\"\n for pl... | [
"0.74676996",
"0.7168184",
"0.6733583",
"0.6671142",
"0.6599137",
"0.6537235",
"0.6495052",
"0.648471",
"0.6455073",
"0.63855594",
"0.6383431",
"0.63688266",
"0.6352971",
"0.6303885",
"0.6285994",
"0.62824136",
"0.62114704",
"0.62050974",
"0.6204267",
"0.6198414",
"0.6196291"... | 0.7301225 | 1 |
Returns the action choice made by the Player. Player can choose to Hit(1), Stand(2) or Double Down (3) | def get_player_input(allow_double_down=True):
choices_avail = ['h', '1', '2']
msg = 'Select: help (h), hit (1), stand (2)'
if allow_double_down:
choices_avail.append('3')
msg += ' ,double down (3)'
msg += ' :'
choice = 0
while choice not in choices_avail:
choice = input(m... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_action(player):\n print_action(player)\n chosen_action_index = int(input('Please indicate your selection from the following list by inputting the number: '))\n return player.available_actions[chosen_action_index]",
"def get_player_action(self) -> None:\n print(f\"\\nYou have: {self.user.h... | [
"0.7664304",
"0.76305485",
"0.7418116",
"0.7145675",
"0.71054864",
"0.7077956",
"0.70766556",
"0.70766556",
"0.70401573",
"0.6945828",
"0.69291",
"0.68862695",
"0.682164",
"0.68153846",
"0.6801916",
"0.6727821",
"0.67192125",
"0.6679106",
"0.66654944",
"0.66654944",
"0.666165... | 0.6747504 | 15 |
Retuns the wager the player chooses for this round. It cannot exceed the maximum available. | def get_wager_input(max_chips, min_chips=1):
chips = 0
while chips < min_chips or chips > max_chips:
chips = input('How many chips do you wager? (min %d, max %d): ' % (min_chips, max_chips))
try:
chips = int(chips)
except:
chips = 0
return chips | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def round_based_alien_limitation(self):\n if self.num_round < 5:\n return 1\n elif self.num_round < 10:\n return 2\n else:\n return 3",
"def take(self, desired_amount):\n if self.amount >= desired_amount:\n grab = desired_amount\n els... | [
"0.607354",
"0.60145956",
"0.5848289",
"0.58172387",
"0.57498705",
"0.5735455",
"0.5721542",
"0.56717646",
"0.5671178",
"0.5665499",
"0.5651265",
"0.5645929",
"0.5634616",
"0.55988336",
"0.55921286",
"0.559142",
"0.55852073",
"0.55724007",
"0.55680674",
"0.5562452",
"0.555093... | 0.52707225 | 51 |
Returns the initialized player attributes. This function is called just once, but the player dict is updated on each round | def _initialize_game(wager_credits):
player = {}
player['chips'] = wager_credits
player['round'] = 0
player['blackjack'] = 0
player['won'] = 0
player['lost'] = 0
player['push'] = 0
player['bust'] = 0
return player | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_player_attributes(self):\n return Player_Attributes.read_by_player_fifa_api_id(self.player_fifa_api_id)",
"def __init__(self):\r\n self.players = {}",
"def player_properties(self):\n return self.properties.GetAll(self.player_interface)",
"def get_players():\n return {\"X\": pl... | [
"0.7445393",
"0.6738495",
"0.6638327",
"0.6635758",
"0.6523638",
"0.64918613",
"0.6424853",
"0.6402643",
"0.63063866",
"0.6300941",
"0.61768234",
"0.6132734",
"0.6125309",
"0.61147493",
"0.6112685",
"0.6096234",
"0.609568",
"0.60428095",
"0.5956577",
"0.59536284",
"0.5951785"... | 0.6587913 | 4 |
Set up some molecules, residues, and spins for testing. | def setUp(self):
# Add a data pipe to the data store.
ds.add(pipe_name='orig', pipe_type='mf')
# Name the first molecule.
cdp.mol[0].name = 'Ap4Aase'
# Add a second molecule to the system.
cdp.mol.add_item(mol_name='RNA')
# Add two more residues to the first m... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def setup(self):\n insts = []\n for i in range(5):\n insts.append(pysat.Instrument('pysat', 'testing',\n clean_level='clean'))\n self.testC = pysat.Constellation(instruments=insts)\n self.testI = pysat.Instrument('pysat', 'testing', cl... | [
"0.68977237",
"0.68746495",
"0.65944415",
"0.6475946",
"0.64491606",
"0.6416783",
"0.63493866",
"0.6320015",
"0.62843525",
"0.62730145",
"0.62586296",
"0.621708",
"0.62119216",
"0.6208113",
"0.618722",
"0.61871713",
"0.61690503",
"0.60853016",
"0.6070992",
"0.60702187",
"0.60... | 0.6524442 | 3 |
Test that the number of spins can be properly counted. The function tested is pipe_control.mol_res_spin.count_spins(). | def test_count_spins(self):
# Test the number of spins counted.
self.assertEqual(mol_res_spin.count_spins(), 4)
self.assertEqual(mol_res_spin.count_spins(skip_desel=False), 8)
self.assertEqual(mol_res_spin.count_spins(selection='@N5'), 1)
self.assertEqual(mol_res_spin.count_spin... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_count_no_spins(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 0)",
"def test_count_spins_no_pipe(self)... | [
"0.8216668",
"0.79208726",
"0.6061253",
"0.59907717",
"0.5961885",
"0.59412616",
"0.59404606",
"0.59132665",
"0.5879472",
"0.5839816",
"0.5767341",
"0.57627225",
"0.5760211",
"0.5658254",
"0.5647766",
"0.56327945",
"0.5631395",
"0.5559625",
"0.55477506",
"0.5539356",
"0.54946... | 0.87852323 | 0 |
Test that the number of spins (zero) can be properly counted. The function tested is pipe_control.mol_res_spin.count_spins(). | def test_count_no_spins(self):
# Reset relax.
reset()
# Add a data pipe to the data store.
ds.add(pipe_name='orig', pipe_type='mf')
# Test the number of spins counted.
self.assertEqual(mol_res_spin.count_spins(), 0) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_count_spins(self):\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 4)\n self.assertEqual(mol_res_spin.count_spins(skip_desel=False), 8)\n self.assertEqual(mol_res_spin.count_spins(selection='@N5'), 1)\n self.assertEqual(mol_res_spin... | [
"0.8364899",
"0.80283797",
"0.63442856",
"0.609039",
"0.6043598",
"0.6036848",
"0.6035397",
"0.5966873",
"0.58482337",
"0.58064646",
"0.57407767",
"0.56835514",
"0.56486934",
"0.563143",
"0.5597956",
"0.55912817",
"0.55141515",
"0.546807",
"0.54593736",
"0.5443237",
"0.544082... | 0.846338 | 0 |
Test that the counting of the number of spins raises an error when no pipe exists. The function tested is pipe_control.mol_res_spin.count_spins(). | def test_count_spins_no_pipe(self):
# Reset relax.
reset()
# Test for the error.
self.assertRaises(RelaxNoPipeError, mol_res_spin.count_spins) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_count_no_spins(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Test the number of spins counted.\n self.assertEqual(mol_res_spin.count_spins(), 0)",
"def test_count_spins(self):\n\n ... | [
"0.8297968",
"0.7812048",
"0.67697406",
"0.61876446",
"0.6167623",
"0.6036055",
"0.58979064",
"0.58179224",
"0.5769859",
"0.57561326",
"0.5715153",
"0.5708538",
"0.5594331",
"0.5509007",
"0.54806995",
"0.5468505",
"0.54357624",
"0.54193336",
"0.5419145",
"0.5415963",
"0.53699... | 0.88973 | 0 |
Test the function for determining if moleculeresiduespin data exists. The function tested is pipe_control.mol_res_spin.exists_mol_res_spin_data(). | def test_exists_mol_res_spin_data(self):
# This should be True.
self.failUnless(mol_res_spin.exists_mol_res_spin_data()) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())",
"def test_exists_mol_res... | [
"0.86498624",
"0.8171099",
"0.8008126",
"0.7832109",
"0.7612232",
"0.74061805",
"0.7374406",
"0.64998114",
"0.6273386",
"0.6179472",
"0.5896734",
"0.58264905",
"0.5745269",
"0.57218933",
"0.57177144",
"0.5715544",
"0.5627069",
"0.56219554",
"0.56199694",
"0.55988914",
"0.5454... | 0.91275215 | 0 |
Determine if moleculeresiduespin data exists (with data for a single molecule). The function tested is pipe_control.mol_res_spin.exists_mol_res_spin_data(). | def test_exists_mol_res_spin_data_single_mol(self):
# Reset relax.
reset()
# Add a data pipe to the data store.
ds.add(pipe_name='orig', pipe_type='mf')
dp = pipes.get_pipe('orig')
# Name the first molecule.
dp.mol[0].name = 'TOM40'
# This should be Tr... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())",
"def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='or... | [
"0.84925765",
"0.8205755",
"0.81849754",
"0.7938019",
"0.78887266",
"0.75465906",
"0.6573173",
"0.63930625",
"0.56609166",
"0.5556357",
"0.5478604",
"0.53835493",
"0.5380998",
"0.53788584",
"0.53724927",
"0.5332502",
"0.5311545",
"0.52456486",
"0.52142644",
"0.52067447",
"0.5... | 0.8367752 | 1 |
Determine if moleculeresiduespin data exists (when a single residue is named). The function tested is pipe_control.mol_res_spin.exists_mol_res_spin_data(). | def test_exists_mol_res_spin_data_single_res_name(self):
# Reset relax.
reset()
# Add a data pipe to the data store.
ds.add(pipe_name='orig', pipe_type='mf')
dp = pipes.get_pipe('orig')
# Name the first residue.
dp.mol[0].res[0].name = 'Lys'
# This sho... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Name the first molecule.\n dp.mol[0].name = 'TOM40'\n\n # ... | [
"0.8420557",
"0.83105195",
"0.8121444",
"0.81118304",
"0.807993",
"0.7950876",
"0.6401373",
"0.6279278",
"0.6215082",
"0.591349",
"0.5806613",
"0.5639699",
"0.5575356",
"0.54308885",
"0.5376391",
"0.53730816",
"0.53661835",
"0.5356303",
"0.5276748",
"0.5268216",
"0.52539533",... | 0.8232994 | 2 |
Determine if moleculeresiduespin data exists (when a single residue is numbered). The function tested is pipe_control.mol_res_spin.exists_mol_res_spin_data(). | def test_exists_mol_res_spin_data_single_res_num(self):
# Reset relax.
reset()
# Add a data pipe to the data store.
ds.add(pipe_name='orig', pipe_type='mf')
dp = pipes.get_pipe('orig')
# Number the first residue.
dp.mol[0].res[0].num = 1
# This should ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_exists_mol_res_spin_data_single_spin_num(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n dp = pipes.get_pipe('orig')\n\n # Number the first spin.\n dp.mol[0].res[0].spin[0].num = 234\... | [
"0.84456354",
"0.82298267",
"0.8103048",
"0.79645956",
"0.79151535",
"0.77068615",
"0.6438838",
"0.6125528",
"0.6099552",
"0.5864683",
"0.57085097",
"0.5695363",
"0.5664928",
"0.55890244",
"0.55634105",
"0.5563084",
"0.5443872",
"0.5368424",
"0.53031784",
"0.52392286",
"0.519... | 0.8403741 | 1 |
Determine if moleculeresiduespin data exists (when a single spin is named). The function tested is pipe_control.mol_res_spin.exists_mol_res_spin_data(). | def test_exists_mol_res_spin_data_single_spin_name(self):
# Reset relax.
reset()
# Add a data pipe to the data store.
ds.add(pipe_name='orig', pipe_type='mf')
dp = pipes.get_pipe('orig')
# Name the first spin.
dp.mol[0].res[0].spin[0].name = 'NH'
# Thi... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())",
"def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name=... | [
"0.83926356",
"0.83922964",
"0.8218184",
"0.81590086",
"0.8031726",
"0.7876572",
"0.6523379",
"0.6487321",
"0.5793478",
"0.566882",
"0.5593635",
"0.5562465",
"0.55435604",
"0.5511731",
"0.54539114",
"0.54490983",
"0.5361425",
"0.535502",
"0.53494656",
"0.53312635",
"0.5321676... | 0.8426691 | 0 |
Determine if moleculeresiduespin data exists (when a single spin is numbered). The function tested is pipe_control.mol_res_spin.exists_mol_res_spin_data(). | def test_exists_mol_res_spin_data_single_spin_num(self):
# Reset relax.
reset()
# Add a data pipe to the data store.
ds.add(pipe_name='orig', pipe_type='mf')
dp = pipes.get_pipe('orig')
# Number the first spin.
dp.mol[0].res[0].spin[0].num = 234
# This... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())",
"def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name=... | [
"0.8392751",
"0.823386",
"0.8206758",
"0.817102",
"0.8049526",
"0.75779665",
"0.6515433",
"0.63660663",
"0.5854637",
"0.57079095",
"0.5615342",
"0.55319315",
"0.552877",
"0.5456042",
"0.54262865",
"0.5386728",
"0.53743654",
"0.5337322",
"0.53064",
"0.5303351",
"0.5252378",
... | 0.8513595 | 0 |
Determine if moleculeresiduespin data exists when no data exists. The function tested is pipe_control.mol_res_spin.exists_mol_res_spin_data(). | def test_exists_mol_res_spin_data_no_data(self):
# Reset relax.
reset()
# Add a data pipe to the data store.
ds.add(pipe_name='orig', pipe_type='mf')
# This should be False.
self.failIf(mol_res_spin.exists_mol_res_spin_data()) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_exists_mol_res_spin_data(self):\n\n # This should be True.\n self.failUnless(mol_res_spin.exists_mol_res_spin_data())",
"def test_exists_mol_res_spin_data_single_mol(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name=... | [
"0.86641157",
"0.8070875",
"0.80186194",
"0.7868918",
"0.77041644",
"0.74484134",
"0.70216393",
"0.65485287",
"0.62315524",
"0.58949995",
"0.57270414",
"0.56871605",
"0.5657348",
"0.55692613",
"0.5513263",
"0.54984736",
"0.5497161",
"0.5481748",
"0.54525614",
"0.5450925",
"0.... | 0.8743408 | 0 |
Determine if moleculeresiduespin data exists when no data pipe exists. The function tested is pipe_control.mol_res_spin.exists_mol_res_spin_data(). | def test_exists_mol_res_spin_data_no_pipe(self):
# Reset relax.
reset()
# This should fail.
self.assertRaises(RelaxNoPipeError, mol_res_spin.exists_mol_res_spin_data) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_exists_mol_res_spin_data_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # This should be False.\n self.failIf(mol_res_spin.exists_mol_res_spin_data())",
"def test_exists_mol_res... | [
"0.8865291",
"0.8417973",
"0.80885214",
"0.80438846",
"0.7852497",
"0.7701418",
"0.7463378",
"0.65262586",
"0.6252962",
"0.59931844",
"0.58717984",
"0.5862831",
"0.5473991",
"0.54632425",
"0.54621637",
"0.5440022",
"0.5434693",
"0.5432748",
"0.5344402",
"0.5344402",
"0.533307... | 0.7589267 | 6 |
Test the format_info_full() function for all combinations of input. | def test_format_info_full1(self):
# The spin info and expected string - covering all possible combinations.
info = [
# 5 bits of info.
{'mol_name': 'Ubi', 'res_name': 'Ala', 'res_num': 10, 'spin_name': 'N', 'spin_num': 200, 'string': "Molecule Ubi, residue Ala 10, spin N 200... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_format_correlation_info(self):\r\n # With 999 permutations.\r\n exp = 'Correlation coefficient\\tParametric p-value\\tNonparametric ' + \\\r\n 'p-value\\tCI (lower)\\tCI (upper)\\n0.7778\\t0.0000\\t' + \\\r\n '0.000\\t0.0000\\t1.0000\\n'\r\n obs = format_corr... | [
"0.61617583",
"0.5618504",
"0.55047697",
"0.5475531",
"0.5467334",
"0.544068",
"0.5422697",
"0.54041266",
"0.5374505",
"0.53257984",
"0.5319085",
"0.53129464",
"0.5284171",
"0.5279987",
"0.52776444",
"0.52651304",
"0.52415544",
"0.51991093",
"0.51775396",
"0.5157071",
"0.5129... | 0.72220844 | 0 |
First test of the spin ID generation function. The function tested is pipe_control.mol_res_spin.generate_spin_id_data_array(). | def test_generate_spin_id_data_array1(self):
# The data.
data = ['1', 'GLY']
# The ID.
id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)
# Test the string.
self.assertEqual(id, ':1') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_generate_spin_id_data_array6(self):\n\n # The data.\n data = ['1', 'GLY', None, None]\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')",
"def test_generate_spin... | [
"0.78925526",
"0.7822347",
"0.76349664",
"0.7610406",
"0.75354004",
"0.6579472",
"0.60722893",
"0.5760644",
"0.5730065",
"0.5698617",
"0.5577793",
"0.55716354",
"0.554988",
"0.55279154",
"0.5508247",
"0.5425098",
"0.5357982",
"0.53330165",
"0.52789444",
"0.527686",
"0.527214"... | 0.8076779 | 0 |
Second test of the spin ID generation function. The function tested is pipe_control.mol_res_spin.generate_spin_id_data_array(). | def test_generate_spin_id_data_array2(self):
# The data.
data = ['1', 'GLY', '234', 'NH']
# The ID.
id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2, spin_num_col=3, spin_name_col=4)
# Test the string.
self.assertEqual(id, ':1@234') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_generate_spin_id_data_array1(self):\n\n # The data.\n data = ['1', 'GLY']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')",
"def test_generate_spin_id_data_arr... | [
"0.8086905",
"0.7927075",
"0.7615566",
"0.7598885",
"0.75597614",
"0.6486901",
"0.6055875",
"0.58638847",
"0.57211256",
"0.5610557",
"0.55860114",
"0.558456",
"0.5549974",
"0.54673797",
"0.53942615",
"0.53439724",
"0.5339024",
"0.5296352",
"0.52316296",
"0.5216718",
"0.520122... | 0.8013001 | 1 |
Third test of the spin ID generation function. The function tested is pipe_control.mol_res_spin.generate_spin_id_data_array(). | def test_generate_spin_id_data_array3(self):
# The data.
data = ['Ap4Aase', '234', 'NH']
# The ID.
id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=None, res_name_col=None, spin_num_col=2, spin_name_col=3)
# Test the string.
self.assertEq... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_generate_spin_id_data_array6(self):\n\n # The data.\n data = ['1', 'GLY', None, None]\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')",
"def test_generate_spin... | [
"0.7930686",
"0.79260224",
"0.77357745",
"0.7663863",
"0.7659892",
"0.64280635",
"0.5991729",
"0.591287",
"0.5785646",
"0.5763235",
"0.5534429",
"0.5532555",
"0.5476528",
"0.5412773",
"0.5298371",
"0.528956",
"0.52654487",
"0.523596",
"0.52343017",
"0.5201792",
"0.5143447",
... | 0.79937476 | 0 |
Fourth test of the spin ID generation function. The function tested is pipe_control.mol_res_spin.generate_spin_id_data_array(). | def test_generate_spin_id_data_array4(self):
# The data.
data = ['Ap4Aase', '1', 'GLY']
# The ID.
id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3)
# Test the string.
self.assertEqual(id, '#Ap4Aase:1') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_generate_spin_id_data_array6(self):\n\n # The data.\n data = ['1', 'GLY', None, None]\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')",
"def test_generate_spin... | [
"0.8070005",
"0.8019214",
"0.79400337",
"0.7837104",
"0.7815383",
"0.64224803",
"0.59210145",
"0.5868475",
"0.57858336",
"0.57399845",
"0.56103945",
"0.53635967",
"0.53469247",
"0.53459364",
"0.53184336",
"0.5314746",
"0.5255449",
"0.5224802",
"0.5213441",
"0.515649",
"0.5151... | 0.80017376 | 2 |
Fifth test of the spin ID generation function. The function tested is pipe_control.mol_res_spin.generate_spin_id_data_array(). | def test_generate_spin_id_data_array5(self):
# The data.
data = ['Ap4Aase', '1', 'GLY', '234', 'NH']
# The ID.
id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5)
# Test the string.
self.as... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_generate_spin_id_data_array6(self):\n\n # The data.\n data = ['1', 'GLY', None, None]\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)\n\n # Test the string.\n self.assertEqual(id, ':1')",
"def test_generate_spin... | [
"0.815962",
"0.80106467",
"0.781097",
"0.7796662",
"0.77246344",
"0.6556488",
"0.5972483",
"0.596083",
"0.5889257",
"0.58199716",
"0.58112353",
"0.5503903",
"0.5457309",
"0.54131293",
"0.5382142",
"0.53779155",
"0.53478414",
"0.5337792",
"0.5311869",
"0.53046256",
"0.5285401"... | 0.80710626 | 1 |
Sixth test of the spin ID generation function. The function tested is pipe_control.mol_res_spin.generate_spin_id_data_array(). | def test_generate_spin_id_data_array6(self):
# The data.
data = ['1', 'GLY', None, None]
# The ID.
id = mol_res_spin.generate_spin_id_data_array(data, res_num_col=1, res_name_col=2)
# Test the string.
self.assertEqual(id, ':1') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_generate_spin_id_data_array5(self):\n\n # The data.\n data = ['Ap4Aase', '1', 'GLY', '234', 'NH']\n\n # The ID.\n id = mol_res_spin.generate_spin_id_data_array(data, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5)\n\n # Test the string.\n ... | [
"0.784438",
"0.7714932",
"0.7577586",
"0.757559",
"0.7561462",
"0.6163308",
"0.5690773",
"0.56745136",
"0.56711537",
"0.5610869",
"0.56024593",
"0.5324083",
"0.527502",
"0.5271551",
"0.5269606",
"0.52232736",
"0.52200073",
"0.5196732",
"0.5193356",
"0.5152407",
"0.5141934",
... | 0.8226237 | 0 |
Test the proper operation of the molecule loop with molecule selection. The function tested is pipe_control.mol_res_spin.molecule_loop(). | def test_molecule_loop(self):
# Loop over the molecules.
for mol in mol_res_spin.molecule_loop('#RNA'):
# Test the molecule name.
self.assertEqual(mol.name, 'RNA')
# Test loop length.
self.assertEqual(len(list(mol_res_spin.molecule_loop('#RNA'))), 1) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_molecule_loop_no_selection(self):\n\n # Molecule data.\n name = ['Ap4Aase', 'RNA']\n\n # Loop over the molecules.\n i = 0\n for mol in mol_res_spin.molecule_loop():\n # Test the molecule names.\n self.assertEqual(mol.name, name[i])\n\n # ... | [
"0.78410846",
"0.72731423",
"0.71487254",
"0.7066662",
"0.6906277",
"0.6623356",
"0.6518581",
"0.64826006",
"0.64725286",
"0.6450824",
"0.6367674",
"0.62304765",
"0.61855984",
"0.61084175",
"0.60988086",
"0.609054",
"0.6079127",
"0.5973447",
"0.59563404",
"0.55609775",
"0.548... | 0.75784975 | 1 |
Test the proper operation of the molecule loop when no data is present. The function tested is pipe_control.mol_res_spin.molecule_loop(). | def test_molecule_loop_no_data(self):
# Reset relax.
reset()
# Add a data pipe to the data store.
ds.add(pipe_name='orig', pipe_type='mf')
# Loop over the molecules.
i = 0
for molecule in mol_res_spin.molecule_loop():
i = i + 1
# Test loop ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_molecule_loop_no_selection(self):\n\n # Molecule data.\n name = ['Ap4Aase', 'RNA']\n\n # Loop over the molecules.\n i = 0\n for mol in mol_res_spin.molecule_loop():\n # Test the molecule names.\n self.assertEqual(mol.name, name[i])\n\n # ... | [
"0.79922223",
"0.79701054",
"0.79289037",
"0.74845135",
"0.731188",
"0.68929285",
"0.6694039",
"0.65099937",
"0.6446146",
"0.6183709",
"0.6016163",
"0.5998978",
"0.5988837",
"0.59473413",
"0.5947067",
"0.58972764",
"0.57490903",
"0.57089925",
"0.5673426",
"0.5634207",
"0.5628... | 0.88965213 | 0 |
Test the proper operation of the molecule loop when no data pipe is present. The function tested is pipe_control.mol_res_spin.molecule_loop(). | def test_molecule_loop_no_pipe(self):
# Reset relax.
reset()
# Function for the problem of catching an error in a generator function.
def fail_test():
for molecule in mol_res_spin.molecule_loop():
pass
# Test for the no pipe error.
self.asse... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n ... | [
"0.85301226",
"0.79059464",
"0.7656533",
"0.73368526",
"0.7248419",
"0.70627767",
"0.69679505",
"0.6318001",
"0.63044786",
"0.6154404",
"0.61035573",
"0.5977854",
"0.5860056",
"0.5848514",
"0.5847035",
"0.5795445",
"0.56938887",
"0.55405074",
"0.5520122",
"0.5514679",
"0.5450... | 0.84358346 | 1 |
Test the proper operation of the molecule loop when no selection is present. The function tested is pipe_control.mol_res_spin.molecule_loop(). | def test_molecule_loop_no_selection(self):
# Molecule data.
name = ['Ap4Aase', 'RNA']
# Loop over the molecules.
i = 0
for mol in mol_res_spin.molecule_loop():
# Test the molecule names.
self.assertEqual(mol.name, name[i])
# Increment i.
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_molecule_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the molecules.\n i = 0\n for molecule in mol_res_spin.molecule_loop():\n i = i + 1\n\n ... | [
"0.7604223",
"0.73143464",
"0.73025155",
"0.7007973",
"0.6872689",
"0.6866279",
"0.6847027",
"0.6842967",
"0.64472896",
"0.64401734",
"0.640884",
"0.6354868",
"0.6325706",
"0.6155382",
"0.58229405",
"0.5801081",
"0.5721982",
"0.5642657",
"0.5607593",
"0.55608016",
"0.5551149"... | 0.8007402 | 0 |
Test the proper operation of the residue loop with residue selection. The function tested is pipe_control.mol_res_spin.residue_loop(). | def test_residue_loop(self):
# Loop over the residues.
for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):
# Test the selection.
self.assertEqual(res.num, 2)
# Test loop length.
self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertE... | [
"0.81529486",
"0.7770318",
"0.7552308",
"0.6837369",
"0.674307",
"0.64884526",
"0.6445583",
"0.63936305",
"0.6344969",
"0.6327929",
"0.6228372",
"0.62093467",
"0.600957",
"0.600777",
"0.59746706",
"0.59265643",
"0.59220964",
"0.5913016",
"0.5843478",
"0.5786151",
"0.57159615"... | 0.8213552 | 0 |
Test the proper operation of the residue loop when no data is present. The function tested is pipe_control.mol_res_spin.residue_loop(). | def test_residue_loop_no_data(self):
# Reset relax.
reset()
# Add a data pipe to the data store.
ds.add(pipe_name='orig', pipe_type='mf')
# Loop over the residues.
i = 0
for residue in mol_res_spin.residue_loop():
i = i + 1
# Test loop leng... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_residue_loop_no_selection(self):\n\n # Spin data.\n num = [1, 2, 4, -5, -4]\n name = [None, 'Glu', 'Pro', None, None]\n\n # Loop over the residues.\n i = 0\n for res in mol_res_spin.residue_loop():\n # Test the residue numbers.\n self.assertE... | [
"0.8301634",
"0.82040375",
"0.7788324",
"0.7710455",
"0.7556808",
"0.72358716",
"0.70310825",
"0.6912135",
"0.66328",
"0.66025203",
"0.6565843",
"0.6549843",
"0.6462473",
"0.6374776",
"0.6350188",
"0.6347619",
"0.6336793",
"0.61492753",
"0.6104927",
"0.58747214",
"0.5848667",... | 0.8984354 | 0 |
Test the proper operation of the residue loop when no data pipe is present. The function tested is pipe_control.mol_res_spin.residue_loop(). | def test_residue_loop_no_pipe(self):
# Reset relax.
reset()
# Function for the problem of catching an error in a generator function.
def fail_test():
for residue in mol_res_spin.residue_loop():
pass
# Test for the no pipe error.
self.assertR... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n ... | [
"0.85945946",
"0.77838326",
"0.7751666",
"0.76332873",
"0.7629808",
"0.7481475",
"0.6956494",
"0.69382966",
"0.68887913",
"0.65152484",
"0.6382403",
"0.63752276",
"0.6283524",
"0.6206884",
"0.62047124",
"0.61061484",
"0.6081791",
"0.6047085",
"0.59946924",
"0.5982436",
"0.588... | 0.86027044 | 0 |
Test the proper operation of the residue loop when no selection is present. The function tested is pipe_control.mol_res_spin.residue_loop(). | def test_residue_loop_no_selection(self):
# Spin data.
num = [1, 2, 4, -5, -4]
name = [None, 'Glu', 'Pro', None, None]
# Loop over the residues.
i = 0
for res in mol_res_spin.residue_loop():
# Test the residue numbers.
self.assertEqual(res.num, n... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_residue_loop_no_data(self):\n\n # Reset relax.\n reset()\n\n # Add a data pipe to the data store.\n ds.add(pipe_name='orig', pipe_type='mf')\n\n # Loop over the residues.\n i = 0\n for residue in mol_res_spin.residue_loop():\n i = i + 1\n\n ... | [
"0.8018613",
"0.7852093",
"0.77218246",
"0.70574504",
"0.68793595",
"0.67554224",
"0.66418993",
"0.65647024",
"0.64698106",
"0.6459469",
"0.6435851",
"0.63787186",
"0.62164485",
"0.6151769",
"0.61505395",
"0.61433077",
"0.60872215",
"0.60452425",
"0.5893791",
"0.5879402",
"0.... | 0.83963245 | 0 |
Test the function for returning the desired molecule data container. The function tested is pipe_control.mol_res_spin.return_molecule(). | def test_return_molecule(self):
# Ask for a few molecules.
mol1 = mol_res_spin.return_molecule('#Ap4Aase')
mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')
# Test the data of molecule 1.
self.assertEqual(mol1.name, 'Ap4Aase')
# Test the data of molecu... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_return_molecule_pipe_fail(self):\n\n # Try to get a molecule from a missing data pipe.\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')\n self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new'... | [
"0.63652605",
"0.636043",
"0.6196237",
"0.61398995",
"0.6118704",
"0.59954035",
"0.5866117",
"0.5800223",
"0.57261777",
"0.56701607",
"0.56608844",
"0.55993",
"0.5499727",
"0.5499299",
"0.5475103",
"0.5424967",
"0.53821063",
"0.53715503",
"0.5311273",
"0.5283148",
"0.5275008"... | 0.82855994 | 0 |
Test the failure of the function for returning the desired molecule data container. The function tested is pipe_control.mol_res_spin.return_molecule(). | def test_return_molecule_pipe_fail(self):
# Try to get a molecule from a missing data pipe.
self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#Ap4Aase', pipe='new')
self.assertRaises(RelaxNoPipeError, mol_res_spin.return_molecule, selection='#RNA', pipe='new') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_return_molecule(self):\n\n # Ask for a few molecules.\n mol1 = mol_res_spin.return_molecule('#Ap4Aase')\n mol2 = mol_res_spin.return_molecule(selection='#RNA', pipe='orig')\n\n # Test the data of molecule 1.\n self.assertEqual(mol1.name, 'Ap4Aase')\n\n # Test the ... | [
"0.7752265",
"0.6388569",
"0.6297495",
"0.6286569",
"0.62686867",
"0.6196573",
"0.6173113",
"0.617114",
"0.6123175",
"0.60926574",
"0.59676576",
"0.5883313",
"0.587805",
"0.5837631",
"0.58120954",
"0.577729",
"0.5614546",
"0.56138414",
"0.56082726",
"0.55601",
"0.55297875",
... | 0.75012517 | 1 |
Test the function for returning the desired residue data container. The function tested is pipe_control.mol_res_spin.return_residue(). | def test_return_residue(self):
# Ask for a few residues.
res1 = mol_res_spin.return_residue(':1')
res2 = mol_res_spin.return_residue(selection=':2')
res4 = mol_res_spin.return_residue(selection=':4', pipe='orig')
res5 = mol_res_spin.return_residue(selection='#RNA:-5', pipe='orig... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_return_single_residue_info(self):\n\n # Ask for a few residues.\n res1 = mol_res_spin.return_single_residue_info('1')\n res2 = mol_res_spin.return_single_residue_info('2,Glu')\n res4 = mol_res_spin.return_single_residue_info('Pro,4')\n res5 = mol_res_spin.return_single_r... | [
"0.75668174",
"0.6807258",
"0.6658924",
"0.6526883",
"0.641903",
"0.6259072",
"0.62291884",
"0.6145257",
"0.61449796",
"0.60818225",
"0.6001908",
"0.594091",
"0.5885459",
"0.58385515",
"0.57113373",
"0.5641675",
"0.5627909",
"0.5625898",
"0.5486544",
"0.54508084",
"0.5426877"... | 0.84991 | 0 |
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